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Binary Options Hedging - Nadex & Markets World Platforms

submitted by mykosonai to binaryreviewpanther [link] [comments]

BTClevels - Bitcoin Binary option. Hedge your positions and never lose a mBTC.

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Hedging Binary Options for Arbitrage?

Does anyone know of any academic whitepapers or studies on this? They have a rather unique risk profile. I believe I've found +EV divergence in pricing between exchanges, however given I can only trade binary calls I'm left exposed to delta as I can't use straddles.
I'd like to hedge my delta for a more pure arbitrage opportunity. Shorting the futures won't work, due to sizing and leaving me uncapped on loss above the strike.
I'm looking for serious replies here, I know it's binary options. I believe the recent influx in retail money, small market size and regulatory risk for larger players are creating this opportunity. I'm experienced in algo-trading so if I can get some help on establishing a hedge I'd like to start making a market with what I've found after more testing.
submitted by Dumb_Nuts to options [link] [comments]

Hedging Strategy Using Binary Options by Yee Kok Siong

Hedging Strategy Using Binary Options by Yee Kok Siong submitted by yeekoksiong to u/yeekoksiong [link] [comments]

My Case Study on Hedging Binary Option (No-Touch) with Long EUR/USD Trade

My Case Study on Hedging Binary Option (No-Touch) with Long EUUSD Trade submitted by enivid to Forex [link] [comments]

Using binary options to hedge spot-trades?

Has anyone tried this?? I'd imagine it could be effective if you were quick enough with the most and or timed your trades just right. Would like to hear your inputs on this!
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Hedge against ETH< $5 by buying "no" shares in this binary option.

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Another trader's tool - Bitcoin Binary Option BTClevels. Hedge your positions and never lose a bitcoin.

submitted by BTClevels to BitcoinMarkets [link] [comments]

No gods, no kings, only NOPE - or divining the future with options flows. [Part 3: Hedge Winding, Unwinding, and the NOPE]

Hello friends!
We're on the last post of this series ("A Gentle Introduction to NOPE"), where we get to use all the Big Boy Concepts (TM) we've discussed in the prior posts and put them all together. Some words before we begin:
  1. This post will be massively theoretical, in the sense that my own speculation and inferences will be largely peppered throughout the post. Are those speculations right? I think so, or I wouldn't be posting it, but they could also be incorrect.
  2. I will briefly touch on using the NOPE this slide, but I will make a secondary post with much more interesting data and trends I've observed. This is primarily for explaining what NOPE is and why it potentially works, and what it potentially measures.
My advice before reading this is to glance at my prior posts, and either read those fully or at least make sure you understand the tl;drs:
https://www.reddit.com/thecorporation/collection/27dc72ad-4e78-44cd-a788-811cd666e32a
Depending on popular demand, I will also make a last-last post called FAQ, where I'll tabulate interesting questions you guys ask me in the comments!
---
So a brief recap before we begin.
Market Maker ("Mr. MM"): An individual or firm who makes money off the exchange fees and bid-ask spread for an asset, while usually trying to stay neutral about the direction the asset moves.
Delta-gamma hedging: The process Mr. MM uses to stay neutral when selling you shitty OTM options, by buying/selling shares (usually) of the underlying as the price moves.
Law of Surprise [Lily-ism]: Effectively, the expected profit of an options trade is zero for both the seller and the buyer.
Random Walk: A special case of a deeper probability probability called a martingale, which basically models stocks or similar phenomena randomly moving every step they take (for stocks, roughly every millisecond). This is one of the most popular views of how stock prices move, especially on short timescales.
Future Expected Payoff Function [Lily-ism]: This is some hidden function that every market participant has about an asset, which more or less models all the possible future probabilities/values of the assets to arrive at a "fair market price". This is a more generalized case of a pricing model like Black-Scholes, or DCF.
Counter-party: The opposite side of your trade (if you sell an option, they buy it; if you buy an option, they sell it).
Price decoherence ]Lily-ism]: A more generalized notion of IV Crush, price decoherence happens when instead of the FEPF changing gradually over time (price formation), the FEPF rapidly changes, due usually to new information being added to the system (e.g. Vermin Supreme winning the 2020 election).
---
One of the most popular gambling events for option traders to play is earnings announcements, and I do owe the concept of NOPE to hypothesizing specifically about the behavior of stock prices at earnings. Much like a black hole in quantum mechanics, most conventional theories about how price should work rapidly break down briefly before, during, and after ER, and generally experienced traders tend to shy away from playing earnings, given their similar unpredictability.
Before we start: what is NOPE? NOPE is a funny backronym from Net Options Pricing Effect, which in its most basic sense, measures the impact option delta has on the underlying price, as compared to share price. When I first started investigating NOPE, I called it OPE (options pricing effect), but NOPE sounds funnier.
The formula for it is dead simple, but I also have no idea how to do LaTeX on reddit, so this is the best I have:

https://preview.redd.it/ais37icfkwt51.png?width=826&format=png&auto=webp&s=3feb6960f15a336fa678e945d93b399a8e59bb49
Since I've already encountered this, put delta in this case is the absolute value (50 delta) to represent a put. If you represent put delta as a negative (the conventional way), do not subtract it; add it.
To keep this simple for the non-mathematically minded: the NOPE today is equal to the weighted sum (weighted by volume) of the delta of every call minus the delta of every put for all options chains extending from today to infinity. Finally, we then divide that number by the # of shares traded today in the market session (ignoring pre-market and post-market, since options cannot trade during those times).
Effectively, NOPE is a rough and dirty way to approximate the impact of delta-gamma hedging as a function of share volume, with us hand-waving the following factors:
  1. To keep calculations simple, we assume that all counter-parties are hedged. This is obviously not true, especially for idiots who believe theta ganging is safe, but holds largely true especially for highly liquid tickers, or tickers will designated market makers (e.g. any ticker in the NASDAQ, for instance).
  2. We assume that all hedging takes place via shares. For SPY and other products tracking the S&P, for instance, market makers can actually hedge via futures or other options. This has the benefit for large positions of not moving the underlying price, but still makes up a fairly small amount of hedges compared to shares.

Winding and Unwinding

I briefly touched on this in a past post, but two properties of NOPE seem to apply well to EER-like behavior (aka any binary catalyst event):
  1. NOPE measures sentiment - In general, the options market is seen as better informed than share traders (e.g. insiders trade via options, because of leverage + easier to mask positions). Therefore, a heavy call/put skew is usually seen as a bullish sign, while the reverse is also true.
  2. NOPE measures system stability
I'm not going to one-sentence explain #2, because why say in one sentence what I can write 1000 words on. In short, NOPE intends to measure sensitivity of the system (the ticker) to disruption. This makes sense, when you view it in the context of delta-gamma hedging. When we assume all counter-parties are hedged, this means an absolutely massive amount of shares get sold/purchased when the underlying price moves. This is because of the following:
a) Assume I, Mr. MM sell 1000 call options for NKLA 25C 10/23 and 300 put options for NKLA 15p 10/23. I'm just going to make up deltas because it's too much effort to calculate them - 30 delta call, 20 delta put.
This implies Mr. MM needs the following to delta hedge: (1000 call options * 30 shares to buy for each) [to balance out writing calls) - (300 put options * 20 shares to sell for each) = 24,000 net shares Mr. MM needs to acquire to balance out his deltas/be fully neutral.
b) This works well when NKLA is at $20. But what about when it hits $19 (because it only can go down, just like their trucks). Thanks to gamma, now we have to recompute the deltas, because they've changed for both the calls (they went down) and for the puts (they went up).
Let's say to keep it simple that now my calls are 20 delta, and my puts are 30 delta. From the 24,000 net shares, Mr. MM has to now have:
(1000 call options * 20 shares to have for each) - (300 put options * 30 shares to sell for each) = 11,000 shares.
Therefore, with a $1 shift in price, now to hedge and be indifferent to direction, Mr. MM has to go from 24,000 shares to 11,000 shares, meaning he has to sell 13,000 shares ASAP, or take on increased risk. Now, you might be saying, "13,000 shares seems small. How would this disrupt the system?"
(This process, by the way, is called hedge unwinding)
It won't, in this example. But across thousands of MMs and millions of contracts, this can - especially in highly optioned tickers - make up a substantial fraction of the net flow of shares per day. And as we know from our desk example, the buying or selling of shares directly changes the price of the stock itself.
This, by the way, is why the NOPE formula takes the shape it does. Some astute readers might notice it looks similar to GEX, which is not a coincidence. GEX however replaces daily volume with open interest, and measures gamma over delta, which I did not find good statistical evidence to support, especially for earnings.
So, with our example above, why does NOPE measure system stability? We can assume for argument's sake that if someone buys a share of NKLA, they're fine with moderate price swings (+- $20 since it's NKLA, obviously), and in it for the long/medium haul. And in most cases this is fine - we can own stock and not worry about minor swings in price. But market makers can't* (they can, but it exposes them to risk), because of how delta works. In fact, for most institutional market makers, they have clearly defined delta limits by end of day, and even small price changes require them to rebalance their hedges.
This over the whole market adds up to a lot shares moving, just to balance out your stupid Robinhood YOLOs. While there are some tricks (dark pools, block trades) to not impact the price of the underlying, the reality is that the more options contracts there are on a ticker, the more outsized influence it will have on the ticker's price. This can technically be exactly balanced, if option put delta is equal to option call delta, but never actually ends up being the case. And unlike shares traded, the shares representing the options are more unstable, meaning they will be sold/bought in response to small price shifts. And will end up magnifying those price shifts, accordingly.

NOPE and Earnings

So we have a new shiny indicator, NOPE. What does it actually mean and do?
There's much literature going back to the 1980s that options markets do have some level of predictiveness towards earnings, which makes sense intuitively. Unlike shares markets, where you can continue to hold your share even if it dips 5%, in options you get access to expanded opportunity to make riches... and losses. An options trader betting on earnings is making a risky and therefore informed bet that he or she knows the outcome, versus a share trader who might be comfortable bagholding in the worst case scenario.
As I've mentioned largely in comments on my prior posts, earnings is a special case because, unlike popular misconceptions, stocks do not go up and down solely due to analyst expectations being meet, beat, or missed. In fact, stock prices move according to the consensus market expectation, which is a function of all the participants' FEPF on that ticker. This is why the price moves so dramatically - even if a stock beats, it might not beat enough to justify the high price tag (FSLY); even if a stock misses, it might have spectacular guidance or maybe the market just was assuming it would go bankrupt instead.
To look at the impact of NOPE and why it may play a role in post-earnings-announcement immediate price moves, let's review the following cases:
  1. Stock Meets/Exceeds Market Expectations (aka price goes up) - In the general case, we would anticipate post-ER market participants value the stock at a higher price, pushing it up rapidly. If there's a high absolute value of NOPE on said ticker, this should end up magnifying the positive move since:
a) If NOPE is high negative - This means a ton of put buying, which means a lot of those puts are now worthless (due to price decoherence). This means that to stay delta neutral, market makers need to close out their sold/shorted shares, buying them, and pushing the stock price up.
b) If NOPE is high positive - This means a ton of call buying, which means a lot of puts are now worthless (see a) but also a lot of calls are now worth more. This means that to stay delta neutral, market makers need to close out their sold/shorted shares AND also buy more shares to cover their calls, pushing the stock price up.
2) Stock Meets/Misses Market Expectations (aka price goes down) - Inversely to what I mentioned above, this should push to the stock price down, fairly immediately. If there's a high absolute value of NOPE on said ticker, this should end up magnifying the negative move since:
a) If NOPE is high negative - This means a ton of put buying, which means a lot of those puts are now worth more, and a lot of calls are now worth less/worth less (due to price decoherence). This means that to stay delta neutral, market makers need to sell/short more shares, pushing the stock price down.
b) If NOPE is high positive - This means a ton of call buying, which means a lot of calls are now worthless (see a) but also a lot of puts are now worth more. This means that to stay delta neutral, market makers need to sell even more shares to keep their calls and puts neutral, pushing the stock price down.
---
Based on the above two cases, it should be a bit more clear why NOPE is a measure of sensitivity to system perturbation. While we previously discussed it in the context of magnifying directional move, the truth is it also provides a directional bias to our "random" walk. This is because given a price move in the direction predicted by NOPE, we expect it to be magnified, especially in situations of price decoherence. If a stock price goes up right after an ER report drops, even based on one participant deciding to value the stock higher, this provides a runaway reaction which boosts the stock price (due to hedging factors as well as other participants' behavior) and inures it to drops.

NOPE and NOPE_MAD

I'm going to gloss over this section because this is more statistical methods than anything interesting. In general, if you have enough data, I recommend using NOPE_MAD over NOPE. While NOPE in theory represents a "real" quantity (net option delta over net share delta), NOPE_MAD (the median absolute deviation of NOPE) does not. NOPE_MAD simply answecompare the following:
  1. How exceptional is today's NOPE versus historic baseline (30 days prior)?
  2. How do I compare two tickers' NOPEs effectively (since some tickers, like TSLA, have a baseline positive NOPE, because Elon memes)? In the initial stages, we used just a straight numerical threshold (let's say NOPE >= 20), but that quickly broke down. NOPE_MAD aims to detect anomalies, because anomalies in general give you tendies.
I might add the formula later in Mathenese, but simply put, to find NOPE_MAD you do the following:
  1. Calculate today's NOPE score (this can be done end of day or intraday, with the true value being EOD of course)
  2. Calculate the end of day NOPE scores on the ticker for the previous 30 trading days
  3. Compute the median of the previous 30 trading days' NOPEs
  4. From the median, find the 30 days' median absolute deviation (https://en.wikipedia.org/wiki/Median_absolute_deviation)
  5. Find today's deviation as compared to the MAD calculated by: [(today's NOPE) - (median NOPE of last 30 days)] / (median absolute deviation of last 30 days)
This is usually reported as sigma (σ), and has a few interesting properties:
  1. The mean of NOPE_MAD for any ticker is almost exactly 0.
  2. [Lily's Speculation's Speculation] NOPE_MAD acts like a spring, and has a tendency to reverse direction as a function of its magnitude. No proof on this yet, but exploring it!

Using the NOPE to predict ER

So the last section was a lot of words and theory, and a lot of what I'm mentioning here is empirically derived (aka I've tested it out, versus just blabbered).
In general, the following holds true:
  1. 3 sigma NOPE_MAD tends to be "the threshold": For very low NOPE_MAD magnitudes (+- 1 sigma), it's effectively just noise, and directionality prediction is low, if not non-existent. It's not exactly like 3 sigma is a play and 2.9 sigma is not a play; NOPE_MAD accuracy increases as NOPE_MAD magnitude (either positive or negative) increases.
  2. NOPE_MAD is only useful on highly optioned tickers: In general, I introduce another parameter for sifting through "candidate" ERs to play: option volume * 100/share volume. When this ends up over let's say 0.4, NOPE_MAD provides a fairly good window into predicting earnings behavior.
  3. NOPE_MAD only predicts during the after-market/pre-market session: I also have no idea if this is true, but my hunch is that next day behavior is mostly random and driven by market movement versus earnings behavior. NOPE_MAD for now only predicts direction of price movements right between the release of the ER report (AH or PM) and the ending of that market session. This is why in general I recommend playing shares, not options for ER (since you can sell during the AH/PM).
  4. NOPE_MAD only predicts direction of price movement: This isn't exactly true, but it's all I feel comfortable stating given the data I have. On observation of ~2700 data points of ER-ticker events since Mar 2019 (SPY 500), I only so far feel comfortable predicting whether stock price goes up (>0 percent difference) or down (<0 price difference). This is +1 for why I usually play with shares.
Some statistics:
#0) As a baseline/null hypothesis, after ER on the SPY500 since Mar 2019, 50-51% price movements in the AH/PM are positive (>0) and ~46-47% are negative (<0).
#1) For NOPE_MAD >= +3 sigma, roughly 68% of price movements are positive after earnings.
#2) For NOPE_MAD <= -3 sigma, roughly 29% of price movements are positive after earnings.
#3) When using a logistic model of only data including NOPE_MAD >= +3 sigma or NOPE_MAD <= -3 sigma, and option/share vol >= 0.4 (around 25% of all ERs observed), I was able to achieve 78% predictive accuracy on direction.

Caveats/Read This

Like all models, NOPE is wrong, but perhaps useful. It's also fairly new (I started working on it around early August 2020), and in fact, my initial hypothesis was exactly incorrect (I thought the opposite would happen, actually). Similarly, as commenters have pointed out, the timeline of data I'm using is fairly compressed (since Mar 2019), and trends and models do change. In fact, I've noticed significantly lower accuracy since the coronavirus recession (when I measured it in early September), but I attribute this mostly to a smaller date range, more market volatility, and honestly, dumber option traders (~65% accuracy versus nearly 80%).
My advice so far if you do play ER with the NOPE method is to use it as following:
  1. Buy/short shares approximately right when the market closes before ER. Ideally even buying it right before the earnings report drops in the AH session is not a bad idea if you can.
  2. Sell/buy to close said shares at the first sign of major weakness (e.g. if the NOPE predicted outcome is incorrect).
  3. Sell/buy to close shares even if it is correct ideally before conference call, or by the end of the after-market/pre-market session.
  4. Only play tickers with high NOPE as well as high option/share vol.
---
In my next post, which may be in a few days, I'll talk about potential use cases for SPY and intraday trends, but I wanted to make sure this wasn't like 7000 words by itself.
Cheers.
- Lily
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New to trading

Hello I am so happy I found this community! Just wanted to say happy trading and good luck to you all before I start my post. I was wondering what pairs are the best to study and trade with for someone who hasn’t found their pair yet? I trade binary options mostly, and I have been focusing on USDJPY and AUDCAD, what are some of the pairs you guys started off with studying? And have a good day!
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No gods, no kings, only NOPE - or divining the future with options flows. [Part 2: A Random Walk and Price Decoherence]

tl;dr -
1) Stock prices move continuously because different market participants end up having different ideas of the future value of a stock.
2) This difference in valuations is part of the reason we have volatility.
3) IV crush happens as a consequence of future possibilities being extinguished at a binary catalyst like earnings very rapidly, as opposed to the normal slow way.
I promise I'm getting to the good parts, but I'm also writing these as a guidebook which I can use later so people never have to talk to me again.
In this part I'm going to start veering a bit into the speculation territory (e.g. ideas I believe or have investigated, but aren't necessary well known) but I'm going to make sure those sections are properly marked as speculative (and you can feel free to ignore/dismiss them). Marked as [Lily's Speculation].
As some commenters have pointed out in prior posts, I do not have formal training in mathematical finance/finance (my background is computer science, discrete math, and biology), so often times I may use terms that I've invented which have analogous/existing terms (e.g. the law of surprise is actually the first law of asset pricing applied to derivatives under risk neutral measure, but I didn't know that until I read the papers later). If I mention something wrong, please do feel free to either PM me (not chat) or post a comment, and we can discuss/I can correct it! As always, buyer beware.
This is the first section also where you do need to be familiar with the topics I've previously discussed, which I'll add links to shortly (my previous posts:
1) https://www.reddit.com/thecorporation/comments/jck2q6/no_gods_no_kings_only_nope_or_divining_the_future/
2) https://www.reddit.com/thecorporation/comments/jbzzq4/why_options_trading_sucks_or_the_law_of_surprise/
---
A Random Walk Down Bankruptcy
A lot of us have probably seen the term random walk, maybe in the context of A Random Walk Down Wall Street, which seems like a great book I'll add to my list of things to read once I figure out how to control my ADD. It seems obvious, then, what a random walk means - when something is moving, it basically means that the next move is random. So if my stock price is $1 and I can move in $0.01 increments, if the stock price is truly randomly walking, there should be roughly a 50% chance it moves up in the next second (to $1.01) or down (to $0.99).
If you've traded for more than a hot minute, this concept should seem obvious, because especially on the intraday, it usually isn't clear why price moves the way it does (despite what chartists want to believe, and I'm sure a ton of people in the comments will tell me why fettucini lines and Batman doji tell them things). For a simple example, we can look at SPY's chart from Friday, Oct 16, 2020:

https://preview.redd.it/jgg3kup9dpt51.png?width=1368&format=png&auto=webp&s=bf8e08402ccef20832c96203126b60c23277ccc2
I'm sure again 7 different people can tell me 7 different things about why the chart shape looks the way it does, or how if I delve deeply enough into it I can find out which man I'm going to marry in 2024, but to a rationalist it isn't exactly apparent at why SPY's price declined from 349 to ~348.5 at around 12:30 PM, or why it picked up until about 3 PM and then went into precipitous decline (although I do have theories why it declined EOD, but that's for another post).
An extremely clever or bored reader from my previous posts could say, "Is this the price formation you mentioned in the law of surprise post?" and the answer is yes. If we relate it back to the individual buyer or seller, we can explain the concept of a stock price's random walk as such:
Most market participants have an idea of an asset's true value (an idealized concept of what an asset is actually worth), which they can derive using models or possibly enough brain damage. However, an asset's value at any given time is not worth one value (usually*), but a spectrum of possible values, usually representing what the asset should be worth in the future. A naive way we can represent this without delving into to much math (because let's face it, most of us fucking hate math) is:
Current value of an asset = sum over all (future possible value multiplied by the likelihood of that value)
In actuality, most models aren't that simple, but it does generalize to a ton of more complicated models which you need more than 7th grade math to understand (Black-Scholes, DCF, blah blah blah).
While in many cases the first term - future possible value - is well defined (Tesla is worth exactly $420.69 billion in 2021, and maybe we all can agree on that by looking at car sales and Musk tweets), where it gets more interesting is the second term - the likelihood of that value occurring. [In actuality, the price of a stock for instance is way more complicated, because a stock can be sold at any point in the future (versus in my example, just the value in 2021), and needs to account for all values of Tesla at any given point in the future.]
How do we estimate the second term - the likelihood of that value occurring? For this class, it actually doesn't matter, because the key concept is this idea: even with all market participants having the same information, we do anticipate that every participant will have a slightly different view of future likelihoods. Why is that? There's many reasons. Some participants may undervalue risk (aka WSB FD/yolos) and therefore weight probabilities of gaining lots of money much more heavily than going bankrupt. Some participants may have alternative data which improves their understanding of what the future values should be, therefore letting them see opportunity. Some participants might overvalue liquidity, and just want to GTFO and thereby accept a haircut on their asset's value to quickly unload it (especially in markets with low liquidity). Some participants may just be yoloing and not even know what Fastly does before putting their account all in weekly puts (god bless you).
In the end, it doesn't matter either the why, but the what: because of these diverging interpretations, over time, we can expect the price of an asset to drift from the current value even with no new information added. In most cases, the calculations that market participants use (which I will, as a Lily-ism, call the future expected payoff function, or FEPF) ends up being quite similar in aggregate, and this is why asset prices likely tend to move slightly up and down for no reason (or rather, this is one interpretation of why).
At this point, I expect the 20% of you who know what I'm talking about or have a finance background to say, "Oh but blah blah efficient market hypothesis contradicts random walk blah blah blah" and you're correct, but it also legitimately doesn't matter here. In the long run, stock prices are clearly not a random walk, because a stock's value is obviously tied to the company's fundamentals (knock on wood I don't regret saying this in the 2020s). However, intraday, in the absence of new, public information, it becomes a close enough approximation.
Also, some of you might wonder what happens when the future expected payoff function (FEPF) I mentioned before ends up wildly diverging for a stock between participants. This could happen because all of us try to short Nikola because it's quite obviously a joke (so our FEPF for Nikola could, let's say, be 0), while the 20 or so remaining bagholders at NikolaCorporation decide that their FEPF of Nikola is $10,000,000 a share). One of the interesting things which intuitively makes sense, is for nearly all stocks, the amount of divergence among market participants in their FEPF increases substantially as you get farther into the future.
This intuitively makes sense, even if you've already quit trying to understand what I'm saying. It's quite easy to say, if at 12:51 PM SPY is worth 350.21 that likely at 12:52 PM SPY will be worth 350.10 or 350.30 in all likelihood. Obviously there are cases this doesn't hold, but more likely than not, prices tend to follow each other, and don't gap up/down hard intraday. However, what if I asked you - given SPY is worth 350.21 at 12:51 PM today, what will it be worth in 2022?
Many people will then try to half ass some DD about interest rates and Trump fleeing to Ecuador to value SPY at 150, while others will assume bull markets will continue indefinitely and SPY will obviously be 7000 by then. The truth is -- no one actually knows, because if you did, you wouldn't be reading a reddit post on this at 2 AM in your jammies.
In fact, if you could somehow figure out the FEPF of all market participants at any given time, assuming no new information occurs, you should be able to roughly predict the true value of an asset infinitely far into the future (hint: this doesn't exactly hold, but again don't @ me).
Now if you do have a finance background, I expect gears will have clicked for some of you, and you may see strong analogies between the FEPF divergence I mentioned, and a concept we're all at least partially familiar with - volatility.
Volatility and Price Decoherence ("IV Crush")
Volatility, just like the Greeks, isn't exactly a real thing. Most of us have some familiarity with implied volatility on options, mostly when we get IV crushed the first time and realize we just lost $3000 on Tesla calls.
If we assume that the current price should represent the weighted likelihoods of all future prices (the random walk), volatility implies the following two things:
  1. Volatility reflects the uncertainty of the current price
  2. Volatility reflects the uncertainty of the future price for every point in the future where the asset has value (up to expiry for options)
[Ignore this section if you aren't pedantic] There's obviously more complex mathematics, because I'm sure some of you will argue in the comments that IV doesn't go up monotonically as option expiry date goes longer and longer into the future, and you're correct (this is because asset pricing reflects drift rate and other factors, as well as certain assets like the VIX end up having cost of carry).
Volatility in options is interesting as well, because in actuality, it isn't something that can be exactly computed -- it arises as a plug between the idealized value of an option (the modeled price) and the real, market value of an option (the spot price). Additionally, because the makeup of market participants in an asset's market changes over time, and new information also comes in (thereby increasing likelihood of some possibilities and reducing it for others), volatility does not remain constant over time, either.
Conceptually, volatility also is pretty easy to understand. But what about our friend, IV crush? I'm sure some of you have bought options to play events, the most common one being earnings reports, which happen quarterly for every company due to regulations. For the more savvy, you might know of expected move, which is a calculation that uses the volatility (and therefore price) increase of at-the-money options about a month out to calculate how much the options market forecasts the underlying stock price to move as a response to ER.
Binary Catalyst Events and Price Decoherence
Remember what I said about price formation being a gradual, continuous process? In the face of special circumstances, in particularly binary catalyst events - events where the outcome is one of two choices, good (1) or bad (0) - the gradual part gets thrown out the window. Earnings in particular is a common and notable case of a binary event, because the price will go down (assuming the company did not meet the market's expectations) or up (assuming the company exceeded the market's expectations) (it will rarely stay flat, so I'm not going to address that case).
Earnings especially is interesting, because unlike other catalytic events, they're pre-scheduled (so the whole market expects them at a certain date/time) and usually have publicly released pre-estimations (guidance, analyst predictions). This separates them from other binary catalysts (e.g. FSLY dipping 30% on guidance update) because the market has ample time to anticipate the event, and participants therefore have time to speculate and hedge on the event.
In most binary catalyst events, we see rapid fluctuations in price, usually called a gap up or gap down, which is caused by participants rapidly intaking new information and changing their FEPF accordingly. This is for the most part an anticipated adjustment to the FEPF based on the expectation that earnings is a Very Big Deal (TM), and is the reason why volatility and therefore option premiums increase so dramatically before earnings.
What makes earnings so interesting in particular is the dramatic effect it can have on all market participants FEPF, as opposed to let's say a Trump tweet, or more people dying of coronavirus. In lots of cases, especially the FEPF of the short term (3-6 months) rapidly changes in response to updated guidance about a company, causing large portions of the future possibility spectrum to rapidly and spectacularly go to zero. In an instant, your Tesla 10/30 800Cs go from "some value" to "not worth the electrons they're printed on".
[Lily's Speculation] This phenomena, I like to call price decoherence, mostly as an analogy to quantum mechanical processes which produce similar results (the collapse of a wavefunction on observation). Price decoherence occurs at a widespread but minor scale continuously, which we normally call price formation (and explains portions of the random walk derivation explained above), but hits a special limit in the face of binary catalyst events, as in an instant rapid portions of the future expected payoff function are extinguished, versus a more gradual process which occurs over time (as an option nears expiration).
Price decoherence, mathematically, ends up being a more generalizable case of the phenomenon we all love to hate - IV crush. Price decoherence during earnings collapses the future expected payoff function of a ticker, leading large portions of the option chain to be effectively worthless (IV crush). It has interesting implications, especially in the case of hedged option sellers, our dear Market Makers. This is because given the expectation that they maintain delta-gamma neutral, and now many of the options they have written are now worthless and have 0 delta, what do they now have to do?
They have to unwind.
[/Lily's Speculation]
- Lily
submitted by the_lilypad to thecorporation [link] [comments]

The classic WSB story - lost it all.

Going to keep this simple. EDIT: this isn’t simple and I should write a short story on this.
I am generally risk averse. I hate losing $100 at the casino, I hate paying extra for guac at chipotles, I will return something or price match an item for a few dollars of savings. I am generally frugal.
But, I somehow had no issues losing 10k in options...
How I started
I remember my first trades like they were yesterday. I was trading the first hydrogen run-up in 2014 (FCEL, BLDP, PLUG) and made a few hundred dollars over a couple weeks.
I quickly progressed to penny stocks / biotech binary events and general stock market gambling mid-2014. I was making a few % here and there but the trend was down in total account value. I was the king of buying the peak in run-ups. I managed to make it out of 2014 close to break-even to slightly down.
WSB Era
March 2015 was my first option trade. It was an AXP - American Express - monthly option trade. I saw one of the regular option traders/services post a block of 10,000 calls that had been bought for 1.3 and I followed the trade with 10 call options for a total of $1300.
I woke up the next day to an analyst upgrade on AXP and was up 50% on my position. I was addicted! I day-dreamed for days about my AXP over night success. I think around that time there was some sort of Buffet buyout of Heinz and an option trade that was up a ridiculous amount of %%%. I wanted to hit it BIG.
I came up with the idea that all I needed to reach my goal was a few 100% over night gains/ 1k>2k>4k>8k> etc. I convinced myself that I would have no problems being patient for the exact criteria that I had set and worked on some other trades.
Remember, the first win is always free.
I was trading options pretty regularly from March 2015 until August 2016. During my best week I was up 20k and could feel the milli within reach. I can remember the exact option trade (HTZ) and I was trading weeklies on it.
For those who have been in the market long enough, you will remember the huge drawdown of August 2015.
I lost half my account value on QCOM calls (100 of them) that I followed at the beginning of July and never materialized. I watched them eventually go to 0. It was another 10,000 block that was probably a hedge or sold.
In August 2015 there were some issues with China and all of us woke up to stocks gapping down huge. Unfortunately my idea of buying far dated calls during the following days/weeks after the crash went sideways. I quickly learned that an increase in volatility causes a rise in option prices and I was paying a premium for calls that were going to lose value very quickly (the infamous IV crush).
I kept trading options into the end of 2015 and managed to maintain my account value positive but the trading fees for the year amounted to $30,000+. My broker was loving it.
I tried all the services, all the strategies. I created rules for my option plays: 1. No earnings 2. Only follow the big buys at a discount (10,000 blocks or more). 3. No weekly options 4. Take profit right away 5. Take losses quickly 6. etc.
I had a whole note book of option plays that I was writing down and following. I was paying for option services that all of you know about - remember, they make money on the services and not trading.
I even figured out a loop-hole with my broker: if I didn’t have enough money in my account, I could change my ask price to .01 and then change it to market buy and I would only need to accept a warning ⚠️ for the order to go through. I was able to day trade the option and make money, who cares if I didnt have enough? After a few months of this, I got a call from my broker that told me to stop and that I would be suspended if I continued with this.
By the way, I was always able to satisfy the debit on the account - so it wasn’t an issue of lack of funds.
Lost it all. Started taking money from lines of credits, every penny that I earned and losing it quicker and quicker.
I was a full on gambler but I was convinced that 8 trades would offset all the losses. I kept getting drawn in to the idea that I could hit a homerun and make it out a hero.
I eventually hit rock bottom on some weekly expiring FSLR options that I bought hours before expiration and said to myself - what the f are you doing? I resolved to invest for the long term and stop throwing tendies away.
The feeling was reinforced during the birth of my first born and I thought - what a loser this kid will think of me if he knew how much I was gambling and wasting my life. It was a really powerful moment looking at my kid and reflecting on this idea.
I decided at that point I was going to save every penny I had and invest it on new issues with potential.
Fall 2016
TTD, COUP and NTNX IPO ‘ed I decided I was going to throw every dollar at these and did so for the next few months. I eventually started using margin (up to 215%) and buying these for the next 6 months. They paid out and managed to make it over 100k within the year.
The first 100k was hard but once I crossed it, I never fell below this magic number.
2017 - I did some day trading but it was mostly obsessing over the above issues. I did gamble on a few options here and there but never more than 1k.
2018 - SFIX was my big winner, I bought a gap up in June 2018 and my combined account value had crossed 400k by August 2018. I was really struggling at crossing the 500k account value and experienced 3 x 30-40% drawdowns over the next 2 years before I finally crossed the 500k barrier and have never looked back.
I still made some mistakes over the next few months - AKAO & GSUM come to mind. Both of these resulted in 20k+ losses. Fortunately my winners were much bigger than my losers.
I thought about giving up and moving to index funds - but i was doing well - just experiencing large drawdowns because of leverage.
2019 big winners were CRON SWAV STNE.
2017 / 2018 / 2019 all had six digit capital gains on my tax returns.
At the beginning of 2020 I was still day trading on margin (180-220%) and got a call from my broker that they were tightening up my margin as my account was analyzed by the risk department and deemed too risky. Believe it or not this was right before the covid crash. I brought my margin down to 100-110% of account value and even though the drawdown from covid hit hard, I wasn’t wiped out.
I stayed the course and bought FSLY / RH during the big march drawdown and this resulted in some nice gains over the next few months.
I am constantly changing and testing my investment strategy but let me tell you that obsessing over 1 or 2 ideas and throwing every penny at it and holding for a few years is the best strategy. It may not work at some point but right now it does.
I still day trade but I trade with 10k or less on each individual position. It allows me minimize my losses and my winners are 1-7%. I am able to consistently make between 3-700$/ a day on day trades using the above strategy. I still take losses and still dream about hitting it big with an option trade but dont feel the need to put it all on the line every month / week.
I finally crossed into the two , club. I know people are going to ask for proof or ban but I am not earning anything for posting and the details about some of the trades should be proof enough that I kept a detailed journal of it all. I have way more to write but these are the highlights.
Eventually I will share how I build a position in a story I love. I still sell buy and sell to early but I am working on improving.
TL:DR - I gambled, lost it all and gambled some more lost more. I made it out alive. I have only sold calls/puts lately.
The one common denominator in all successful people is how much they obsess over 1 or 2 ideas. Do the same. All the winners on this sub have gone all in on one idea (FSLY / TSLA ). Stick with new stories or ones that are changing and go all in...wait a second, I didnt learn anything.
submitted by jojo2021 to wallstreetbets [link] [comments]

Everything You Always Wanted To Know About Swaps* (*But Were Afraid To Ask)

Hello, dummies
It's your old pal, Fuzzy.
As I'm sure you've all noticed, a lot of the stuff that gets posted here is - to put it delicately - fucking ridiculous. More backwards-ass shit gets posted to wallstreetbets than you'd see on a Westboro Baptist community message board. I mean, I had a look at the daily thread yesterday and..... yeesh. I know, I know. We all make like the divine Laura Dern circa 1992 on the daily and stick our hands deep into this steaming heap of shit to find the nuggets of valuable and/or hilarious information within (thanks for reading, BTW). I agree. I love it just the way it is too. That's what makes WSB great.
What I'm getting at is that a lot of the stuff that gets posted here - notwithstanding it being funny or interesting - is just... wrong. Like, fucking your cousin wrong. And to be clear, I mean the fucking your *first* cousin kinda wrong, before my Southerners in the back get all het up (simmer down, Billy Ray - I know Mabel's twice removed on your grand-sister's side). Truly, I try to let it slide. I do my bit to try and put you on the right path. Most of the time, I sleep easy no matter how badly I've seen someone explain what a bank liquidity crisis is. But out of all of those tens of thousands of misguided, autistic attempts at understanding the world of high finance, one thing gets so consistently - so *emphatically* - fucked up and misunderstood by you retards that last night I felt obligated at the end of a long work day to pull together this edition of Finance with Fuzzy just for you. It's so serious I'm not even going to make a u/pokimane gag. Have you guessed what it is yet? Here's a clue. It's in the title of the post.
That's right, friends. Today in the neighborhood we're going to talk all about hedging in financial markets - spots, swaps, collars, forwards, CDS, synthetic CDOs, all that fun shit. Don't worry; I'm going to explain what all the scary words mean and how they impact your OTM RH positions along the way.
We're going to break it down like this. (1) "What's a hedge, Fuzzy?" (2) Common Hedging Strategies and (3) All About ISDAs and Credit Default Swaps.
Before we begin. For the nerds and JV traders in the back (and anyone else who needs to hear this up front) - I am simplifying these descriptions for the purposes of this post. I am also obviously not going to try and cover every exotic form of hedge under the sun or give a detailed summation of what caused the financial crisis. If you are interested in something specific ask a question, but don't try and impress me with your Investopedia skills or technical points I didn't cover; I will just be forced to flex my years of IRL experience on you in the comments and you'll look like a big dummy.
TL;DR? Fuck you. There is no TL;DR. You've come this far already. What's a few more paragraphs? Put down the Cheetos and try to concentrate for the next 5-7 minutes. You'll learn something, and I promise I'll be gentle.
Ready? Let's get started.
1. The Tao of Risk: Hedging as a Way of Life
The simplest way to characterize what a hedge 'is' is to imagine every action having a binary outcome. One is bad, one is good. Red lines, green lines; uppie, downie. With me so far? Good. A 'hedge' is simply the employment of a strategy to mitigate the effect of your action having the wrong binary outcome. You wanted X, but you got Z! Frowny face. A hedge strategy introduces a third outcome. If you hedged against the possibility of Z happening, then you can wind up with Y instead. Not as good as X, but not as bad as Z. The technical definition I like to give my idiot juniors is as follows:
Utilization of a defensive strategy to mitigate risk, at a fraction of the cost to capital of the risk itself.
Congratulations. You just finished Hedging 101. "But Fuzzy, that's easy! I just sold a naked call against my 95% OTM put! I'm adequately hedged!". Spoiler alert: you're not (although good work on executing a collar, which I describe below). What I'm talking about here is what would be referred to as a 'perfect hedge'; a binary outcome where downside is totally mitigated by a risk management strategy. That's not how it works IRL. Pay attention; this is the tricky part.
You can't take a single position and conclude that you're adequately hedged because risks are fluid, not static. So you need to constantly adjust your position in order to maximize the value of the hedge and insure your position. You also need to consider exposure to more than one category of risk. There are micro (specific exposure) risks, and macro (trend exposure) risks, and both need to factor into the hedge calculus.
That's why, in the real world, the value of hedging depends entirely on the design of the hedging strategy itself. Here, when we say "value" of the hedge, we're not talking about cash money - we're talking about the intrinsic value of the hedge relative to the the risk profile of your underlying exposure. To achieve this, people hedge dynamically. In wallstreetbets terms, this means that as the value of your position changes, you need to change your hedges too. The idea is to efficiently and continuously distribute and rebalance risk across different states and periods, taking value from states in which the marginal cost of the hedge is low and putting it back into states where marginal cost of the hedge is high, until the shadow value of your underlying exposure is equalized across your positions. The punchline, I guess, is that one static position is a hedge in the same way that the finger paintings you make for your wife's boyfriend are art - it's technically correct, but you're only playing yourself by believing it.
Anyway. Obviously doing this as a small potatoes trader is hard but it's worth taking into account. Enough basic shit. So how does this work in markets?
2. A Hedging Taxonomy
The best place to start here is a practical question. What does a business need to hedge against? Think about the specific risk that an individual business faces. These are legion, so I'm just going to list a few of the key ones that apply to most corporates. (1) You have commodity risk for the shit you buy or the shit you use. (2) You have currency risk for the money you borrow. (3) You have rate risk on the debt you carry. (4) You have offtake risk for the shit you sell. Complicated, right? To help address the many and varied ways that shit can go wrong in a sophisticated market, smart operators like yours truly have devised a whole bundle of different instruments which can help you manage the risk. I might write about some of the more complicated ones in a later post if people are interested (CDO/CLOs, strip/stack hedges and bond swaps with option toggles come to mind) but let's stick to the basics for now.
(i) Swaps
A swap is one of the most common forms of hedge instrument, and they're used by pretty much everyone that can afford them. The language is complicated but the concept isn't, so pay attention and you'll be fine. This is the most important part of this section so it'll be the longest one.
Swaps are derivative contracts with two counterparties (before you ask, you can't trade 'em on an exchange - they're OTC instruments only). They're used to exchange one cash flow for another cash flow of equal expected value; doing this allows you to take speculative positions on certain financial prices or to alter the cash flows of existing assets or liabilities within a business. "Wait, Fuzz; slow down! What do you mean sets of cash flows?". Fear not, little autist. Ol' Fuzz has you covered.
The cash flows I'm talking about are referred to in swap-land as 'legs'. One leg is fixed - a set payment that's the same every time it gets paid - and the other is variable - it fluctuates (typically indexed off the price of the underlying risk that you are speculating on / protecting against). You set it up at the start so that they're notionally equal and the two legs net off; so at open, the swap is a zero NPV instrument. Here's where the fun starts. If the price that you based the variable leg of the swap on changes, the value of the swap will shift; the party on the wrong side of the move ponies up via the variable payment. It's a zero sum game.
I'll give you an example using the most vanilla swap around; an interest rate trade. Here's how it works. You borrow money from a bank, and they charge you a rate of interest. You lock the rate up front, because you're smart like that. But then - quelle surprise! - the rate gets better after you borrow. Now you're bagholding to the tune of, I don't know, 5 bps. Doesn't sound like much but on a billion dollar loan that's a lot of money (a classic example of the kind of 'small, deep hole' that's terrible for profits). Now, if you had a swap contract on the rate before you entered the trade, you're set; if the rate goes down, you get a payment under the swap. If it goes up, whatever payment you're making to the bank is netted off by the fact that you're borrowing at a sub-market rate. Win-win! Or, at least, Lose Less / Lose Less. That's the name of the game in hedging.
There are many different kinds of swaps, some of which are pretty exotic; but they're all different variations on the same theme. If your business has exposure to something which fluctuates in price, you trade swaps to hedge against the fluctuation. The valuation of swaps is also super interesting but I guarantee you that 99% of you won't understand it so I'm not going to try and explain it here although I encourage you to google it if you're interested.
Because they're OTC, none of them are filed publicly. Someeeeeetimes you see an ISDA (dsicussed below) but the confirms themselves (the individual swaps) are not filed. You can usually read about the hedging strategy in a 10-K, though. For what it's worth, most modern credit agreements ban speculative hedging. Top tip: This is occasionally something worth checking in credit agreements when you invest in businesses that are debt issuers - being able to do this increases the risk profile significantly and is particularly important in times of economic volatility (ctrl+f "non-speculative" in the credit agreement to be sure).
(ii) Forwards
A forward is a contract made today for the future delivery of an asset at a pre-agreed price. That's it. "But Fuzzy! That sounds just like a futures contract!". I know. Confusing, right? Just like a futures trade, forwards are generally used in commodity or forex land to protect against price fluctuations. The differences between forwards and futures are small but significant. I'm not going to go into super boring detail because I don't think many of you are commodities traders but it is still an important thing to understand even if you're just an RH jockey, so stick with me.
Just like swaps, forwards are OTC contracts - they're not publicly traded. This is distinct from futures, which are traded on exchanges (see The Ballad Of Big Dick Vick for some more color on this). In a forward, no money changes hands until the maturity date of the contract when delivery and receipt are carried out; price and quantity are locked in from day 1. As you now know having read about BDV, futures are marked to market daily, and normally people close them out with synthetic settlement using an inverse position. They're also liquid, and that makes them easier to unwind or close out in case shit goes sideways.
People use forwards when they absolutely have to get rid of the thing they made (or take delivery of the thing they need). If you're a miner, or a farmer, you use this shit to make sure that at the end of the production cycle, you can get rid of the shit you made (and you won't get fucked by someone taking cash settlement over delivery). If you're a buyer, you use them to guarantee that you'll get whatever the shit is that you'll need at a price agreed in advance. Because they're OTC, you can also exactly tailor them to the requirements of your particular circumstances.
These contracts are incredibly byzantine (and there are even crazier synthetic forwards you can see in money markets for the true degenerate fund managers). In my experience, only Texan oilfield magnates, commodities traders, and the weirdo forex crowd fuck with them. I (i) do not own a 10 gallon hat or a novelty size belt buckle (ii) do not wake up in the middle of the night freaking out about the price of pork fat and (iii) love greenbacks too much to care about other countries' monopoly money, so I don't fuck with them.
(iii) Collars
No, not the kind your wife is encouraging you to wear try out to 'spice things up' in the bedroom during quarantine. Collars are actually the hedging strategy most applicable to WSB. Collars deal with options! Hooray!
To execute a basic collar (also called a wrapper by tea-drinking Brits and people from the Antipodes), you buy an out of the money put while simultaneously writing a covered call on the same equity. The put protects your position against price drops and writing the call produces income that offsets the put premium. Doing this limits your tendies (you can only profit up to the strike price of the call) but also writes down your risk. If you screen large volume trades with a VOL/OI of more than 3 or 4x (and they're not bullshit biotech stocks), you can sometimes see these being constructed in real time as hedge funds protect themselves on their shorts.
(3) All About ISDAs, CDS and Synthetic CDOs
You may have heard about the mythical ISDA. Much like an indenture (discussed in my post on $F), it's a magic legal machine that lets you build swaps via trade confirms with a willing counterparty. They are very complicated legal documents and you need to be a true expert to fuck with them. Fortunately, I am, so I do. They're made of two parts; a Master (which is a form agreement that's always the same) and a Schedule (which amends the Master to include your specific terms). They are also the engine behind just about every major credit crunch of the last 10+ years.
First - a brief explainer. An ISDA is a not in and of itself a hedge - it's an umbrella contract that governs the terms of your swaps, which you use to construct your hedge position. You can trade commodities, forex, rates, whatever, all under the same ISDA.
Let me explain. Remember when we talked about swaps? Right. So. You can trade swaps on just about anything. In the late 90s and early 2000s, people had the smart idea of using other people's debt and or credit ratings as the variable leg of swap documentation. These are called credit default swaps. I was actually starting out at a bank during this time and, I gotta tell you, the only thing I can compare people's enthusiasm for this shit to was that moment in your early teens when you discover jerking off. Except, unlike your bathroom bound shame sessions to Mom's Sears catalogue, every single person you know felt that way too; and they're all doing it at once. It was a fiscal circlejerk of epic proportions, and the financial crisis was the inevitable bukkake finish. WSB autism is absolutely no comparison for the enthusiasm people had during this time for lighting each other's money on fire.
Here's how it works. You pick a company. Any company. Maybe even your own! And then you write a swap. In the swap, you define "Credit Event" with respect to that company's debt as the variable leg . And you write in... whatever you want. A ratings downgrade, default under the docs, failure to meet a leverage ratio or FCCR for a certain testing period... whatever. Now, this started out as a hedge position, just like we discussed above. The purest of intentions, of course. But then people realized - if bad shit happens, you make money. And banks... don't like calling in loans or forcing bankruptcies. Can you smell what the moral hazard is cooking?
Enter synthetic CDOs. CDOs are basically pools of asset backed securities that invest in debt (loans or bonds). They've been around for a minute but they got famous in the 2000s because a shitload of them containing subprime mortgage debt went belly up in 2008. This got a lot of publicity because a lot of sad looking rednecks got foreclosed on and were interviewed on CNBC. "OH!", the people cried. "Look at those big bad bankers buying up subprime loans! They caused this!". Wrong answer, America. The debt wasn't the problem. What a lot of people don't realize is that the real meat of the problem was not in regular way CDOs investing in bundles of shit mortgage debts in synthetic CDOs investing in CDS predicated on that debt. They're synthetic because they don't have a stake in the actual underlying debt; just the instruments riding on the coattails. The reason these are so popular (and remain so) is that smart structured attorneys and bankers like your faithful correspondent realized that an even more profitable and efficient way of building high yield products with limited downside was investing in instruments that profit from failure of debt and in instruments that rely on that debt and then hedging that exposure with other CDS instruments in paired trades, and on and on up the chain. The problem with doing this was that everyone wound up exposed to everybody else's books as a result, and when one went tits up, everybody did. Hence, recession, Basel III, etc. Thanks, Obama.
Heavy investment in CDS can also have a warping effect on the price of debt (something else that happened during the pre-financial crisis years and is starting to happen again now). This happens in three different ways. (1) Investors who previously were long on the debt hedge their position by selling CDS protection on the underlying, putting downward pressure on the debt price. (2) Investors who previously shorted the debt switch to buying CDS protection because the relatively illiquid debt (partic. when its a bond) trades at a discount below par compared to the CDS. The resulting reduction in short selling puts upward pressure on the bond price. (3) The delta in price and actual value of the debt tempts some investors to become NBTs (neg basis traders) who long the debt and purchase CDS protection. If traders can't take leverage, nothing happens to the price of the debt. If basis traders can take leverage (which is nearly always the case because they're holding a hedged position), they can push up or depress the debt price, goosing swap premiums etc. Anyway. Enough technical details.
I could keep going. This is a fascinating topic that is very poorly understood and explained, mainly because the people that caused it all still work on the street and use the same tactics today (it's also terribly taught at business schools because none of the teachers were actually around to see how this played out live). But it relates to the topic of today's lesson, so I thought I'd include it here.
Work depending, I'll be back next week with a covenant breakdown. Most upvoted ticker gets the post.
*EDIT 1\* In a total blowout, $PLAY won. So it's D&B time next week. Post will drop Monday at market open.
submitted by fuzzyblankeet to wallstreetbets [link] [comments]

2 months back at trading (update) and some new questions

Hi all, I posted a thread back a few months ago when I started getting seriously back into trading after 20 years away. I thought I'd post an update with some notes on how I'm progressing. I like to type, so settle in. Maybe it'll help new traders who are exactly where I was 2 months ago, I dunno. Or maybe you'll wonder why you spent 3 minutes reading this. Risk/reward, yo.
I'm trading 5k on TastyWorks. I'm a newcomer to theta positive strategies and have done about two thirds of my overall trades in this style. However, most of my experience in trading in the past has been intraday timeframe oriented chart reading and momentum stuff. I learned almost everything "new" that I'm doing from TastyTrade, /options, /thetagang, and Option Alpha. I've enjoyed the material coming from esinvests YouTube channel quite a bit as well. The theta gang type strategies I've done have been almost entirely around binary event IV contraction (mostly earnings, but not always) and in most cases, capped to about $250 in risk per position.
The raw numbers:
Net PnL : +247
Commissions paid: -155
Fees: -42
Right away what jumps out is something that was indicated by realdeal43 and PapaCharlie9 in my previous thread. This is a tough, grindy way to trade a small account. It reminds me a little bit of when I was rising through the stakes in online poker, playing $2/4 limit holdem. Even if you're a profitable player in that game, beating the rake over the long term is very, very hard. Here, over 3 months of trading a conservative style with mostly defined risk strategies, my commissions are roughly equal to my net PnL. That is just insane, and I don't even think I've been overtrading.
55 trades total, win rate of 60%
22 neutral / other trades
Biggest wins:
Biggest losses:
This is pretty much where I expected to be while learning a bunch of new trading techniques. And no, this is not a large sample size so I have no idea whether or not I can be profitable trading this way (yet). I am heartened by the fact that I seem to be hitting my earnings trades and selling quick spikes in IV (like weed cures Corona day). I'm disheartened that I've went against my principles several times, holding trades for longer than I originally intended, or letting losses mount, believing that I could roll or manage my way out of trouble.
I still feel like I am going against my nature to some degree. My trading in years past was scalping oriented and simple. I was taught that a good trade was right almost immediately. If it went against me, I'd cut it immediately and look for a better entry. This is absolutely nothing like that. A good trade may take weeks to develop. It's been really hard for me to sit through the troughs and it's been even harder to watch an okay profit get taken out by a big swing in delta. Part of me wonders if I am cut out for this style at all and if I shouldn't just take my 5k and start trading micro futures. But that's a different post...
I'll share a couple of my meager learnings:


My new questions :

That's enough of this wall of text for now. If you made it this far, I salute you, because this shit was even longer than my last post.
submitted by bogglor to options [link] [comments]

Says flair added no button still

So excited Can't sleep Options plus leverage Love when autistic leverage an absolutely null awareness of risk reward the righteous. Join me in Sueing @RobinHoodClassAction in your spare time. They are dirty they do shady unethical things like counter party risk against the other platform they also own. While not allowing. You to enter it exit a position Ah or PM but I.digress. make a separate piece for that later. Heheem Step 1. Use abuse worthless broker the aforementioned. With as much leverage as will not set off there risk assessment team. For example voldemortTicker U an then E plus C . We are not allowed to say . Makes mods bum bums sore. They reject your script off rip. Once theta decayed on calls an price fell below 93 cents. You could purchase an even better write options for 1 dollar an 10 cents, expiring in as little as one week for 1 dollar. That's right trade 100 shares for 1 dollar. So naturally I grabbed 250 for the 20th of this month. An then more for the next 2 consecutive months out. I had to pay 10 dollars per contract bc, I have no patients but not relevant. Step 2. Make sure there is an event of non tech analysis origins that will move price one way or the other. *note this doesn't even necessarily have to be in your favor direction. You don't have to be insane or extra and look for a binary outcome like myself. Honestly I was aggrevated an looking for a way to be pretty after multiple PDT suspension the 3rd wasn't even my fault. Anyways you sell for as little as one dollar more than you payed then you double down. Till you get. Txt saying we are closing your position or deposit funds. Example of event . Us in 2019 decided to limit the supply of yellow cakes from foreign power. Global demand is constant or increasing. Step 3. I like the added insurance of volatility of using a Mico cap. 300m or less. Fellow NPC an employees at the scam or company will decide my fate. Not some nasty market maker killing momentum to collect HTB an weekend. Margin. Nor hedge funds that positions by the Quarter. Who buy or sell side institutions catching a hair across the ass. My outcome is bc you worthless NPC panic sold or brave heart avingers assemble hold the linens held the Line!!!!!!! In Unison- So yes why you Wana rinse an repeat. They have all these bogus Greek letters that destroy your position based on price time an baloney. It's better to take a little piece an start mixing a bigger pie An you can do long short . Straddle or strangle her while you hit her from the back. Rule of thumb price of contract falls more than 20% in one day and your not the one purchasing get rid of it. Give that opportunity to the next man live to fight another day. I totally forgot what I was saying maybe some one in the comments will sumorize for me. Last point about scaling. It helps you find instead of picking a top or a bottom. Just increasing the time you have until you push the buy buttons does miracles. Already holding a few is like getting your mourning fix no fomo sickness no chasing. Yolo with finesse ya savages an buy my #stonk cheaper than. I did your welcome NPC
submitted by Mr_Frost360 to smallstreetbets [link] [comments]

New to deep learning, trying to understand how to approach a network I have in mind

Hey all! I've been fascinated with machine/deep learning for years now, and am finally taking my first steps into this world. I want to take a stab at creating a stock trading AI, and came across this fantastic article that outlines one approach. The goal of the network described in the article is to predict the price on a day-to-day basis, which seems like an obvious starting point. It uses a LSTM network as the generator in a GAN. The first image in the article outlines how the approach is structured.
The thing is, I'm not very interested in predicting the stock price. My ideal system would instead output a "conviction" value for a variety of financial instruments. These would include holding cash, stocks, and options (both calls and puts, likely with a variety of strike prices and time horizons). A higher value would represent a stronger conviction that holding that financial instrument would be more profitable than not. The network would not be optimizing for raw numerical accuracy, but profitability. There would be non-machine learning based logic that translates the conviction values into actions (buy/sell/hold), with the outcome of those actions determining profitability.
An example of the conviction values it might return for a given day are as follows:
If I look at this, it tells me that the network thinks the stock is more likely to go up than not (stock and calls having higher percentages than cash and puts), but that it thinks there's enough of a chance it'll go down that buying some puts to hedge is worth their loss in value if it goes up instead. What to do with this information will depend on each person individually, but let's assume the action logic is pretty basic and allocates the funds proportionally based on the percentages. One note: the percentages don't have to add up to 100%. If it is 100% convinced the stock will go up, the conviction for both stock and calls would be 100%, while cash and puts would be 0%. In that case, with this super naive logic, it would split funds 50/50 between stocks and calls.
That leads me to my question: what would you use as the baseline-truth that the LSTM generator output gets compared to in the discriminator? With stock price it's obviously just the real stock price, but when we're talking about profitability across several financial instruments it's less so. My first thought is to use a 0/1 value based on whether or not holding that instrument through the next day was actually profitable, but it's important to me that the conviction value isn't just a binary YES/NO. I'm not familiar enough with GANs to know if it's possible to have it optimize towards an answer that doesn't necessarily match the baseline-truth it's being discriminated against. My gut reaction based on the little I know tells me it wouldn't be possible. I'm also not familiar enough with deep learning generally to know if another training methodology would be more appropriate in my situation.
How would you approach this?
EDIT: Been mulling this over a bit more and realized that I need to nail down what my ideal end result would be. I said I'd want it to optimize for profit, which means that I would need to calculate the maximum potential profit for each day and use that value as the baseline-truth that the results from the LSTM generator gets compared to. So, we can imagine a day where the stock went up 2%. If going all in on calls would result in $1 more in profit compared to going all in on stock, the maximum potential profit value for that day would be based on going 100% in on calls and 0% in on stocks. As a result, the perfectly optimal conviction values from the LSTM generator would be:
Now, the chance of making a model that predicts/matches this perfectly in a situation where you'd make $1 more going all in on calls is essentially 0. The next best case scenario is the generator acknowledging the fact that it can't predict it perfectly by giving calls a much lower weight and shares a higher weight (the reason being, calls generally lose value every single day you hold them if all else is equal and the price doesn't change). During training, it will run into situations like I described above where there's almost equal profit potential from holding stocks and calls. When it makes the wrong judgement call and says that going all in on calls is the way to go when stocks were actually better, the discrepancy in profit will be higher since the calls actually lost value. Over the training period, it should learn that it needs to be more conservative and allocate more funds to stocks in those situations. In other situations when it's REALLY sure the stock will go up, it will learn that it's safemore profitable to prioritize calls over stock.
Actually, instead of calculating an actual dollar value and using that as the base-line truth, it should be enough to instead choose one financial instrument to have a conviction value of 1 for that day (representing that it's the most profitable instrument), while all the others get a value of 0. This is different to what I said in my original post, which was that I would set the conviction value for each instrument that would produce some profit to 1. In that situation the sum of the convictions could very well be over 100%; whereas, if only one instrument is given a value of 1 in the baseline-truth data, the sum of the conviction values should be close to 100%.
Now that I've written that out, I feel like I have a clearer path forward. If anything I said sounds wrong, please let me know. It's based off of assumptions I'm making about how GANs work, without having any real experience with them.
submitted by EdvardDashD to MLQuestions [link] [comments]

New to deep learning, trying to understand how to approach a network I have in mind

Hey all! I've been fascinated with machine/deep learning for years now, and am finally taking my first steps into this world. I want to take a stab at creating a stock trading AI, and came across this fantastic article that outlines one approach. The goal of the network described in the article is to predict the price on a day-to-day basis, which seems like an obvious starting point. It uses a LSTM network as the generator in a GAN. The first image in the article outlines how the approach is structured.
The thing is, I'm not very interested in predicting the stock price. My ideal system would instead output a "conviction" value for a variety of financial instruments. These would include holding cash, stocks, and options (both calls and puts, likely with a variety of strike prices and time horizons). A higher value would represent a stronger conviction that holding that financial instrument would be more profitable than not. The network would not be optimizing for raw numerical accuracy, but profitability. There would be non-machine learning based logic that translates the conviction values into actions (buy/sell/hold), with the outcome of those actions determining profitability.
An example of the conviction values it might return for a given day are as follows:
If I look at this, it tells me that the network thinks the stock is more likely to go up than not (stock and calls having higher percentages than cash and puts), but that it thinks there's enough of a chance it'll go down that buying some puts to hedge is worth their loss in value if it goes up instead. What to do with this information will depend on each person individually, but let's assume the action logic is pretty basic and allocates the funds proportionally based on the percentages. One note: the percentages don't have to add up to 100%. If it is 100% convinced the stock will go up, the conviction for both stock and calls would be 100%, while cash and puts would be 0%. In that case, with this super naive logic, it would split funds 50/50 between stocks and calls.
That leads me to my question: what would you use as the baseline-truth that the LSTM generator output gets compared to in the discriminator? With stock price it's obviously just the real stock price, but when we're talking about profitability across several financial instruments it's less so. My first thought is to use a 0/1 value based on whether or not holding that instrument through the next day was actually profitable, but it's important to me that the conviction value isn't just a binary YES/NO. I'm not familiar enough with GANs to know if it's possible to have it optimize towards an answer that doesn't necessarily match the baseline-truth it's being discriminated against. My gut reaction based on the little I know tells me it wouldn't be possible. I'm also not familiar enough with deep learning generally to know if another training methodology would be more appropriate in my situation.
How would you approach this?
EDIT: Been mulling this over a bit more and realized that I need to nail down what my ideal end result would be. I said I'd want it to optimize for profit, which means that I would need to calculate the maximum potential profit for each day and use that value as the baseline-truth that the results from the LSTM generator gets compared to. So, we can imagine a day where the stock went up 2%. If going all in on calls would result in $1 more in profit compared to going all in on stock, the maximum potential profit value for that day would be based on going 100% in on calls and 0% in on stocks. As a result, the perfectly optimal conviction values from the LSTM generator would be:
Now, the chance of making a model that predicts/matches this perfectly in a situation where you'd make $1 more going all in on calls is essentially 0. The next best case scenario is the generator acknowledging the fact that it can't predict it perfectly by giving calls a much lower weight and shares a higher weight (the reason being, calls generally lose value every single day you hold them if all else is equal and the price doesn't change). During training, it will run into situations like I described above where there's almost equal profit potential from holding stocks and calls. When it makes the wrong judgement call and says that going all in on calls is the way to go when stocks were actually better, the discrepancy in profit will be higher since the calls actually lost value. Over the training period, it should learn that it needs to be more conservative and allocate more funds to stocks in those situations. In other situations when it's REALLY sure the stock will go up, it will learn that it's safemore profitable to prioritize calls over stock.
Actually, instead of calculating an actual dollar value and using that as the base-line truth, it should be enough to instead choose one financial instrument to have a conviction value of 1 for that day (representing that it's the most profitable instrument), while all the others get a value of 0. This is different to what I said in my original post, which was that I would set the conviction value for each instrument that would produce some profit to 1. In that situation the sum of the convictions could very well be over 100%; whereas, if only one instrument is given a value of 1 in the baseline-truth data, the sum of the conviction values should be close to 100%.
Now that I've written that out, I feel like I have a clearer path forward. If anything I said sounds wrong, please let me know. It's based off of assumptions I'm making about how GANs work, without having any real experience with them.
submitted by EdvardDashD to learnmachinelearning [link] [comments]

New to deep learning, trying to understand how to approach a network I have in mind

Hey all! I've been fascinated with machine/deep learning for years now, and am finally taking my first steps into this world. I want to take a stab at creating a stock trading AI, and came across this fantastic article that outlines one approach. The goal of the network described in the article is to predict the price on a day-to-day basis, which seems like an obvious starting point. It uses a LSTM network as the generator in a GAN. The first image in the article outlines how the approach is structured.
The thing is, I'm not very interested in predicting the stock price. My ideal system would instead output a "conviction" value for a variety of financial instruments. These would include holding cash, stocks, and options (both calls and puts, likely with a variety of strike prices and time horizons). A higher value would represent a stronger conviction that holding that financial instrument would be more profitable than not. The network would not be optimizing for raw numerical accuracy, but profitability. There would be non-machine learning based logic that translates the conviction values into actions (buy/sell/hold), with the outcome of those actions determining profitability.
An example of the conviction values it might return for a given day are as follows:
If I look at this, it tells me that the network thinks the stock is more likely to go up than not (stock and calls having higher percentages than cash and puts), but that it thinks there's enough of a chance it'll go down that buying some puts to hedge is worth their loss in value if it goes up instead. What to do with this information will depend on each person individually, but let's assume the action logic is pretty basic and allocates the funds proportionally based on the percentages. One note: the percentages don't have to add up to 100%. If it is 100% convinced the stock will go up, the conviction for both stock and calls would be 100%, while cash and puts would be 0%. In that case, with this super naive logic, it would split funds 50/50 between stocks and calls.
That leads me to my question: what would you use as the baseline-truth that the LSTM generator output gets compared to in the discriminator? With stock price it's obviously just the real stock price, but when we're talking about profitability across several financial instruments it's less so. My first thought is to use a 0/1 value based on whether or not holding that instrument through the next day was actually profitable, but it's important to me that the conviction value isn't just a binary YES/NO. I'm not familiar enough with GANs to know if it's possible to have it optimize towards an answer that doesn't necessarily match the baseline-truth it's being discriminated against. My gut reaction based on the little I know tells me it wouldn't be possible. I'm also not familiar enough with deep learning generally to know if another training methodology would be more appropriate in my situation.
How would you approach this?
EDIT: Been mulling this over a bit more and realized that I need to nail down what my ideal end result would be. I said I'd want it to optimize for profit, which means that I would need to calculate the maximum potential profit for each day and use that value as the baseline-truth that the results from the LSTM generator gets compared to. So, we can imagine a day where the stock went up 2%. If going all in on calls would result in $1 more in profit compared to going all in on stock, the maximum potential profit value for that day would be based on going 100% in on calls and 0% in on stocks. As a result, the perfectly optimal conviction values from the LSTM generator would be:
Now, the chance of making a model that predicts/matches this perfectly in a situation where you'd make $1 more going all in on calls is essentially 0. The next best case scenario is the generator acknowledging the fact that it can't predict it perfectly by giving calls a much lower weight and shares a higher weight (the reason being, calls generally lose value every single day you hold them if all else is equal and the price doesn't change). During training, it will run into situations like I described above where there's almost equal profit potential from holding stocks and calls. When it makes the wrong judgement call and says that going all in on calls is the way to go when stocks were actually better, the discrepancy in profit will be higher since the calls actually lost value. Over the training period, it should learn that it needs to be more conservative and allocate more funds to stocks in those situations. In other situations when it's REALLY sure the stock will go up, it will learn that it's safemore profitable to prioritize calls over stock.
Actually, instead of calculating an actual dollar value and using that as the base-line truth, it should be enough to instead choose one financial instrument to have a conviction value of 1 for that day (representing that it's the most profitable instrument), while all the others get a value of 0. This is different to what I said in my original post, which was that I would set the conviction value for each instrument that would produce some profit to 1. In that situation the sum of the convictions could very well be over 100%; whereas, if only one instrument is given a value of 1 in the baseline-truth data, the sum of the conviction values should be close to 100%.
Now that I've written that out, I feel like I have a clearer path forward. If anything I said sounds wrong, please let me know. It's based off of assumptions I'm making about how GANs work, without having any real experience with them.
submitted by EdvardDashD to deeplearning [link] [comments]

Wall Street Week Ahead for the trading week beginning March 9th, 2020

Good Saturday morning to all of you here on wallstreetbets. I hope everyone on this sub made out pretty nicely in the market this past week, and is ready for the new trading week and month ahead.
Here is everything you need to know to get you ready for the trading week beginning March 9th, 2020.

Wall Street braces for more market volatility as wild swings become the ‘new normal’ amid coronavirus - (Source)

The S&P 500 has never behaved like this, but Wall Street strategists say get used to it.
Investors just witnessed the equity benchmark swinging up or down 2% for four days straight in the face of the coronavirus panic.
In the index’s history dating back to 1927, this is the first time the S&P 500 had a week of alternating gains and losses of more than 2% from Monday through Thursday, according to Bespoke Investment Group. Daily swings like this over a two-week period were only seen at the peak of the financial crisis and in 2011 when U.S. sovereign debt got its first-ever downgrade, the firm said.
“The message to all investors is that they should expect this volatility to continue. This should be considered the new normal going forward,” said Mike Loewengart, managing director of investment strategy at E-Trade.
The Dow Jones Industrial Average jumped north of 1,000 points twice in the past week, only to erase the quadruple-digit gains in the subsequent sessions. The coronavirus outbreak kept investors on edge as global cases of the infections surpassed 100,000. It’s also spreading rapidly in the U.S. California has declared a state of emergency, while the number of cases in New York reached 33.
“Uncertainty breeds greater market volatility,” Keith Lerner, SunTrust’s chief market strategist, said in a note. “Much is still unknown about how severe and widespread the coronavirus will become. From a market perspective, what we are seeing is uncomfortable but somewhat typical after shock periods.”

More stimulus?

So far, the actions from global central banks and governments in response to the outbreak haven’t triggered a sustainable rebound.
The Federal Reserve’s first emergency rate cut since the financial crisis did little to calm investor anxiety. President Donald Trump on Friday signed a sweeping spending bill with an$8.3 billion packageto aid prevention efforts to produce a vaccine for the deadly disease, but stocks extended their heavy rout that day.
“The market is recognizing the global authorities are responding to this,” said Tom Essaye, founder of the Sevens Report. “If the market begins to worry they are not doing that sufficiently, then I think we are going to go down ugly. It is helping stocks hold up.”
Essaye said any further stimulus from China and a decent-sized fiscal package from Germany would be positive to the market, but he doesn’t expect the moves to create a huge rebound.
The fed funds future market is now pricing in the possibility of the U.S. central bank cutting by 75 basis points at its March 17-18 meeting.

Where is the bottom?

Many on Wall Street expect the market to fall further before recovering as the health crisis unfolds.
Binky Chadha, Deutsche Bank’s chief equity strategist, sees a bottom for the S&P 500 in the second quarter after stocks falling as much as 20% from their recent peak.
“The magnitude of the selloff in the S&P 500 so far has further to go; and in terms of duration, just two weeks in, it is much too early to declare this episode as being done,” Chadha said in a note. “We do view the impacts on macro and earnings growth as being relatively short-lived and the market eventually looking through them.”
Deutsche Bank maintained its year-end target of 3,250 for the S&P 500, which would represent a 10% gain from here and a flat return for 2020.
Strategists are also urging patience during this heightened volatility, cautioning against panic selling.
“It is during times like these that investors need to maintain a longer-term perspective and stick to their investment process rather than making knee-jerk, binary decisions,” Brian Belski, chief investment strategist at BMO Capital Markets, said in a note.

This past week saw the following moves in the S&P:

(CLICK HERE FOR THE FULL S&P TREE MAP FOR THE PAST WEEK!)

Major Indices for this past week:

(CLICK HERE FOR THE MAJOR INDICES FOR THE PAST WEEK!)

Major Futures Markets as of Friday's close:

(CLICK HERE FOR THE MAJOR FUTURES INDICES AS OF FRIDAY!)

Economic Calendar for the Week Ahead:

(CLICK HERE FOR THE FULL ECONOMIC CALENDAR FOR THE WEEK AHEAD!)

Sector Performance WTD, MTD, YTD:

(CLICK HERE FOR FRIDAY'S PERFORMANCE!)
(CLICK HERE FOR THE WEEK-TO-DATE PERFORMANCE!)
(CLICK HERE FOR THE MONTH-TO-DATE PERFORMANCE!)
(CLICK HERE FOR THE 3-MONTH PERFORMANCE!)
(CLICK HERE FOR THE YEAR-TO-DATE PERFORMANCE!)
(CLICK HERE FOR THE 52-WEEK PERFORMANCE!)

Percentage Changes for the Major Indices, WTD, MTD, QTD, YTD as of Friday's close:

(CLICK HERE FOR THE CHART!)

S&P Sectors for the Past Week:

(CLICK HERE FOR THE CHART!)

Major Indices Pullback/Correction Levels as of Friday's close:

(CLICK HERE FOR THE CHART!

Major Indices Rally Levels as of Friday's close:

(CLICK HERE FOR THE CHART!)

Most Anticipated Earnings Releases for this week:

(CLICK HERE FOR THE CHART!)

Here are the upcoming IPO's for this week:

(CLICK HERE FOR THE CHART!)

Friday's Stock Analyst Upgrades & Downgrades:

(CLICK HERE FOR THE CHART LINK #1!)
(CLICK HERE FOR THE CHART LINK #2!)
(CLICK HERE FOR THE CHART LINK #3!)

A "Run of the Mill" Drawdown

If you're like us, you've heard a lot of people reference the recent equity declines as a sign that the market is pricing in some sort of Armageddon in the US economy. While comments like that make for great soundbites, a little perspective is in order. Since the S&P 500's high on February 19th, the S&P 500 is down 12.8%. In the chart below, we show the S&P 500's annual maximum drawdown by year going back to 1928. In the entire history of the index, the median maximum drawdown from a YTD high is 13.05%. In other words, this year's decline is actually less than normal. Perhaps due to the fact that we have only seen one larger-than-average drawdown in the last eight years is why this one feels so bad.
The fact that the current decline has only been inline with the historical norm raises a number of questions. For example, if the market has already priced in the worst-case scenario, going out and adding some equity exposure would be a no brainer. However, if we're only in the midst of a 'normal' drawdown in the equity market as the coronavirus outbreak threatens to put the economy into a recession, one could argue that things for the stock market could get worse before they get better, especially when we know that the market can be prone to over-reaction in both directions. The fact is that nobody knows right now how this entire outbreak will play out. If it really is a black swan, the market definitely has further to fall and now would present a great opportunity to sell more equities. However, if it proves to be temporary and after a quarter or two resolves itself and the economy gets back on the path it was on at the start of the year, then the magnitude of the current decline is probably appropriate. As they say, that's what makes a market!
(CLICK HERE FOR THE CHART!)

Long-Term Treasuries Go Haywire

Take a good luck at today's moves in long-term US Treasury yields, because chances are you won't see moves of this magnitude again soon. Let's start with the yield on the 30-year US Treasury. Today's decline of 29 basis points in the yield will go down as the largest one-day decline in the yield on the 30-year since 2009. For some perspective, there have only been 25 other days since 1977 where the yield saw a larger one day decline.
(CLICK HERE FOR THE CHART!)
That doesn't even tell the whole story, though. As shown in the chart below, every other time the yield saw a sharper one-day decline, the actual yield of the 30-year was much higher, and in most other cases it was much, much higher.
(CLICK HERE FOR THE CHART!)
To show this another way, the percentage change in the yield on the 30-year has never been seen before, and it's not even close. Now, before the chart crime police come calling, we realize showing a percentage change of a percentage is not the most accurate representation, but we wanted to show this for illustrative purposes only.
(CLICK HERE FOR THE CHART!)
Finally, with long-term interest rates plummetting we wanted to provide an update on the performance of the Austrian 100-year bond. That's now back at record highs, begging the question, why is the US not flooding the market with long-term debt?
(CLICK HERE FOR THE CHART!)

It Doesn't Get Much Worse Than This For Crude Oil

Crude oil prices are down close to 10% today in what is shaping up to be the worst day for crude oil since late 2014. That's more than five years.
(CLICK HERE FOR THE CHART!)
Today's decline is pretty much a continuation of what has been a one-way trade for the commodity ever since the US drone strike on Iranian general Soleimani. The last time prices were this low was around Christmas 2018.
(CLICK HERE FOR THE CHART!)
With today's decline, crude oil is now off to its worst start to a year in a generation falling 32%. Since 1984, the only other year that was worse was 1986 when the year started out with a decline of 50% through March 6th. If you're looking for a bright spot, in 1986, prices rose 36% over the remainder of the year. The only other year where crude oil kicked off the year with a 30% decline was in 1991 after the first Iraq war. Over the remainder of that year, prices rose a more modest 5%.
(CLICK HERE FOR THE CHART!)

10-Year Treasury Yield Breaks Below 1%

Despite strong market gains on Wednesday, March 4, 2020, the on-the-run 10-year Treasury yield ended the day below 1% for the first time ever and has posted additional declines in real time, sitting at 0.92% intraday as this blog is being written. “The decline in yields has been remarkable,” said LPL Research Senior Market Strategist Ryan Detrick. “The 10-year Treasury yield has dipped below 1%, and today’s declines are likely to make the recent run lower the largest decline of the cycle.”
As shown in LPL Research’s chart of the day, the current decline in the 10-year Treasury yield without a meaningful reversal (defined as at least 0.75%) is approaching the decline seen in 2011 and 2012 and would need about another two months to be the longest decline in length of time. At the same time, no prior decline has lasted forever and a pattern of declines and increases has been normal.
(CLICK HERE FOR THE CHART!)
What are some things that can push the 10-year Treasury yield lower?
  • A shrinking but still sizable yield advantage over other developed market sovereign debt
  • Added stock volatility if downside risks to economic growth from the coronavirus increase
  • A larger potential premium over shorter-term yields if the Federal Reserve aggressively cuts interest rates
What are some things that can push the 10-year Treasury yield higher?
  • A second half economic rebound acting a catalyst for a Treasury sell-off
  • As yields move lower, investors may increasingly seek more attractive sources of income
  • Any dollar weakness could lead to some selling by international investors
  • Longer maturity Treasuries are looking like an increasingly crowded trade, potentially adding energy to any sell-off
On balance, our view remains that the prospect of an economic rebound over the second half points to the potential for interest rates moving higher. At the same time, we still see some advantage in the potential diversification benefits of intermediate maturity high-quality bonds, especially during periods of market stress. We continue to recommend that suitable investors consider keeping a bond portfolio’s sensitivity to changes in interest rates below that of the benchmark Bloomberg Barclays U.S. Aggregate Bond Index by emphasizing short to intermediate maturity bonds, but do not believe it’s time to pile into very short maturities despite the 10-year Treasury yield sitting at historically low levels.

U.S. Jobs Growth Marches On

While stock markets continue to be extremely volatile as they come to terms with how the coronavirus may affect global growth, the U.S. job market has remained remarkably robust. Continued U.S. jobs data resilience in the face of headwinds from the coronavirus outbreak may be a key factor in prolonging the expansion, given how important the strength of the U.S. consumer has been late into this expansion.
The U.S. Department of Labor today reported that U.S. nonfarm payroll data had a strong showing of 273,000 jobs added in February, topping the expectation of every Bloomberg-surveyed economist, with an additional upward revision of 85,000 additional jobs for December 2019 and January 2020. This has brought the current unemployment rate back to its 50-year low of 3.5%. So far, it appears it’s too soon for any effects of the coronavirus to have been felt in the jobs numbers. (Note: The survey takes place in the middle of each month.)
On Wednesday, ADP released its private payroll data (excluding government jobs), which increased by 183,000 in February, also handily beating market expectations. Most of these jobs were added in the service sector, with 44,000 added in the leisure and hospitality sector, and another 31,000 in trade/transportation/utilities. Both of these areas could be at risk of potential cutbacks if consumers start to avoid eating out or other leisure pursuits due to coronavirus fears.
As shown in the LPL Chart of the Day, payrolls remain strong, and any effects of the virus outbreaks most likely would be felt in coming months.
(CLICK HERE FOR THE CHART!)
“February’s jobs report shows the 113th straight month that the U.S. jobs market has grown,” said LPL Financial Senior Market Strategist Ryan Detrick. “That’s an incredible run and highlights how the U.S. consumer has become key to extending the expansion, especially given setbacks to global growth from the coronavirus outbreak.”
While there is bound to be some drag on future jobs data from the coronavirus-related slowdown, we would anticipate that the effects of this may be transitory. We believe economic fundamentals continue to suggest the possibility of a second-half-of-the–year economic rebound.

Down January & Down February: S&P 500 Posts Full-Year Gain Just 43.75% of Time

The combination of a down January and a down February has come about 17 times, including this year, going back to 1950. Rest of the year and full-year performance has taken a rather sizable hit following the previous 16 occurrences. March through December S&P 500 average performance drops to 2.32% compared to 7.69% in all years. Full-year performance is even worse with S&P 500 average turning to a loss of 4.91% compared to an average gain of 9.14% in all years. All hope for 2020 is not lost as seven of the 16 past down January and down February years did go on to log gains over the last 10 months and full year while six enjoyed double-digit gains from March to December.
(CLICK HERE FOR THE CHART!)

Take Caution After Emergency Rate Cut

Today’s big rally was an encouraging sign that the markets are becoming more comfortable with the public health, monetary and political handling of the situation. But the history of these “emergency” or “surprise” rate cuts by the Fed between meetings suggest some caution remains in order.
The table here shows that these surprise cuts between meetings have really only “worked” once in the past 20+ years. In 1998 when the Fed and the plunge protection team acted swiftly and in a coordinated manner to stave off the fallout from the financial crisis caused by the collapse of the Russian ruble and the highly leveraged Long Term Capital Management hedge fund markets responded well. This was not the case during the extended bear markets of 2001-2002 and 2007-2009.
Bottom line: if this is a short-term impact like the 1998 financial crisis the market should recover sooner rather than later. But if the economic impact of coronavirus virus is prolonged, the market is more likely to languish.
(CLICK HERE FOR THE CHART!)
Here are the most notable companies (tickers) reporting earnings in this upcoming trading week ahead-
  • $ADBE
  • $DKS
  • $AVGO
  • $THO
  • $ULTA
  • $WORK
  • $DG
  • $SFIX
  • $SOGO
  • $DOCU
  • $INO
  • $CLDR
  • $INSG
  • $SOHU
  • $BTAI
  • $ORCL
  • $HEAR
  • $NVAX
  • $ADDYY
  • $GPS
  • $AKBA
  • $PDD
  • $CYOU
  • $FNV
  • $MTNB
  • $NERV
  • $MTN
  • $BEST
  • $PRTY
  • $NINE
  • $AZUL
  • $UNFI
  • $PRPL
  • $VSLR
  • $KLZE
  • $ZUO
  • $DVAX
  • $EXPR
  • $VRA
  • $AXSM
  • $CDMO
  • $CASY
(CLICK HERE FOR NEXT WEEK'S MOST NOTABLE EARNINGS RELEASES!)
(CLICK HERE FOR NEXT WEEK'S HIGHEST VOLATILITY EARNINGS RELEASES!)
Below are some of the notable companies coming out with earnings releases this upcoming trading week ahead which includes the date/time of release & consensus estimates courtesy of Earnings Whispers:

Monday 3.9.20 Before Market Open:

(CLICK HERE FOR MONDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES!)

Monday 3.9.20 After Market Close:

(CLICK HERE FOR MONDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES!)

Tuesday 3.10.20 Before Market Open:

(CLICK HERE FOR TUESDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES!)

Tuesday 3.10.20 After Market Close:

(CLICK HERE FOR TUESDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES!)

Wednesday 3.11.20 Before Market Open:

(CLICK HERE FOR WEDNESDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES!)

Wednesday 3.11.20 After Market Close:

(CLICK HERE FOR WEDNESDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES!)

Thursday 3.12.20 Before Market Open:

(CLICK HERE FOR THURSDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES!)

Thursday 3.12.20 After Market Close:

(CLICK HERE FOR THURSDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES!)

Friday 3.13.20 Before Market Open:

(CLICK HERE FOR FRIDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES!)

Friday 3.13.20 After Market Close:

([CLICK HERE FOR FRIDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES!]())
NONE.

Adobe Inc. $336.77

Adobe Inc. (ADBE) is confirmed to report earnings at approximately 4:05 PM ET on Thursday, March 12, 2020. The consensus earnings estimate is $2.23 per share on revenue of $3.04 billion and the Earnings Whisper ® number is $2.29 per share. Investor sentiment going into the company's earnings release has 81% expecting an earnings beat The company's guidance was for earnings of approximately $2.23 per share. Consensus estimates are for year-over-year earnings growth of 29.65% with revenue increasing by 16.88%. Short interest has decreased by 38.4% since the company's last earnings release while the stock has drifted higher by 7.2% from its open following the earnings release to be 10.9% above its 200 day moving average of $303.70. Overall earnings estimates have been revised higher since the company's last earnings release. On Monday, February 24, 2020 there was some notable buying of 1,109 contracts of the $400.00 call expiring on Friday, March 20, 2020. Option traders are pricing in a 9.3% move on earnings and the stock has averaged a 4.1% move in recent quarters.

(CLICK HERE FOR THE CHART!)

DICK'S Sporting Goods, Inc. $34.98

DICK'S Sporting Goods, Inc. (DKS) is confirmed to report earnings at approximately 7:30 AM ET on Tuesday, March 10, 2020. The consensus earnings estimate is $1.23 per share on revenue of $2.56 billion and the Earnings Whisper ® number is $1.28 per share. Investor sentiment going into the company's earnings release has 57% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 14.95% with revenue increasing by 2.73%. Short interest has decreased by 29.1% since the company's last earnings release while the stock has drifted lower by 20.3% from its open following the earnings release to be 12.0% below its 200 day moving average of $39.75. Overall earnings estimates have been revised higher since the company's last earnings release. On Wednesday, February 26, 2020 there was some notable buying of 848 contracts of the $39.00 put expiring on Friday, March 20, 2020. Option traders are pricing in a 14.4% move on earnings and the stock has averaged a 7.3% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Broadcom Limited $269.45

Broadcom Limited (AVGO) is confirmed to report earnings at approximately 4:15 PM ET on Thursday, March 12, 2020. The consensus earnings estimate is $5.34 per share on revenue of $5.93 billion and the Earnings Whisper ® number is $5.45 per share. Investor sentiment going into the company's earnings release has 83% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 5.65% with revenue increasing by 2.44%. Short interest has decreased by 15.6% since the company's last earnings release while the stock has drifted lower by 15.3% from its open following the earnings release to be 7.7% below its 200 day moving average of $291.95. Overall earnings estimates have been revised lower since the company's last earnings release. On Tuesday, February 25, 2020 there was some notable buying of 1,197 contracts of the $260.00 put expiring on Friday, April 17, 2020. Option traders are pricing in a 11.1% move on earnings and the stock has averaged a 4.9% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Thor Industries, Inc. $70.04

Thor Industries, Inc. (THO) is confirmed to report earnings at approximately 6:45 AM ET on Monday, March 9, 2020. The consensus earnings estimate is $0.76 per share on revenue of $1.79 billion and the Earnings Whisper ® number is $0.84 per share. Investor sentiment going into the company's earnings release has 62% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 16.92% with revenue increasing by 38.70%. Short interest has decreased by 12.9% since the company's last earnings release while the stock has drifted higher by 5.4% from its open following the earnings release to be 12.0% above its 200 day moving average of $62.53. Overall earnings estimates have been revised lower since the company's last earnings release. Option traders are pricing in a 6.3% move on earnings and the stock has averaged a 8.1% move in recent quarters.

(CLICK HERE FOR THE CHART!)

ULTA Beauty $256.58

ULTA Beauty (ULTA) is confirmed to report earnings at approximately 4:00 PM ET on Thursday, March 12, 2020. The consensus earnings estimate is $3.71 per share on revenue of $2.29 billion and the Earnings Whisper ® number is $3.75 per share. Investor sentiment going into the company's earnings release has 73% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 2.77% with revenue increasing by 7.78%. Short interest has increased by 8.7% since the company's last earnings release while the stock has drifted lower by 0.1% from its open following the earnings release to be 9.5% below its 200 day moving average of $283.43. Overall earnings estimates have been revised lower since the company's last earnings release. Option traders are pricing in a 15.3% move on earnings and the stock has averaged a 11.7% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Slack Technologies, Inc. $26.42

Slack Technologies, Inc. (WORK) is confirmed to report earnings at approximately 4:15 PM ET on Thursday, March 12, 2020. The consensus estimate is for a loss of $0.06 per share on revenue of $173.06 million and the Earnings Whisper ® number is ($0.04) per share. Investor sentiment going into the company's earnings release has 67% expecting an earnings beat The company's guidance was for a loss of $0.07 to $0.06 per share on revenue of $172.00 million to $174.00 million. Short interest has increased by 1.2% since the company's last earnings release while the stock has drifted higher by 19.0% from its open following the earnings release. Overall earnings estimates have been revised higher since the company's last earnings release. The stock has averaged a 4.3% move on earnings in recent quarters.

(CLICK HERE FOR THE CHART!)

Dollar General Corporation $158.38

Dollar General Corporation (DG) is confirmed to report earnings at approximately 6:55 AM ET on Thursday, March 12, 2020. The consensus earnings estimate is $2.02 per share on revenue of $7.15 billion and the Earnings Whisper ® number is $2.05 per share. Investor sentiment going into the company's earnings release has 76% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 9.78% with revenue increasing by 7.52%. Short interest has increased by 16.2% since the company's last earnings release while the stock has drifted higher by 1.8% from its open following the earnings release to be 5.7% above its 200 day moving average of $149.88. Overall earnings estimates have been revised higher since the company's last earnings release. On Friday, February 28, 2020 there was some notable buying of 1,013 contracts of the $182.50 call expiring on Friday, March 20, 2020. Option traders are pricing in a 9.2% move on earnings and the stock has averaged a 5.7% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Stitch Fix, Inc. $22.78

Stitch Fix, Inc. (SFIX) is confirmed to report earnings at approximately 4:05 PM ET on Monday, March 9, 2020. The consensus earnings estimate is $0.06 per share on revenue of $452.96 million and the Earnings Whisper ® number is $0.09 per share. Investor sentiment going into the company's earnings release has 83% expecting an earnings beat The company's guidance was for revenue of $447.00 million to $455.00 million. Consensus estimates are for earnings to decline year-over-year by 50.00% with revenue increasing by 22.33%. Short interest has decreased by 4.6% since the company's last earnings release while the stock has drifted lower by 16.1% from its open following the earnings release to be 5.1% below its 200 day moving average of $24.01. Overall earnings estimates have been revised higher since the company's last earnings release. On Wednesday, February 19, 2020 there was some notable buying of 4,026 contracts of the $35.00 call expiring on Friday, June 19, 2020. Option traders are pricing in a 28.0% move on earnings and the stock has averaged a 15.2% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Sogou Inc. $3.85

Sogou Inc. (SOGO) is confirmed to report earnings at approximately 4:00 AM ET on Monday, March 9, 2020. The consensus earnings estimate is $0.09 per share on revenue of $303.08 million and the Earnings Whisper ® number is $0.10 per share. Investor sentiment going into the company's earnings release has 58% expecting an earnings beat The company's guidance was for revenue of $290.00 million to $310.00 million. Consensus estimates are for year-over-year earnings growth of 28.57% with revenue increasing by 1.78%. Short interest has increased by 6.6% since the company's last earnings release while the stock has drifted lower by 27.8% from its open following the earnings release to be 15.7% below its 200 day moving average of $4.57. Overall earnings estimates have been revised lower since the company's last earnings release. The stock has averaged a 3.8% move on earnings in recent quarters.

(CLICK HERE FOR THE CHART!)

DocuSign $84.02

DocuSign (DOCU) is confirmed to report earnings at approximately 4:05 PM ET on Thursday, March 12, 2020. The consensus earnings estimate is $0.05 per share on revenue of $267.44 million and the Earnings Whisper ® number is $0.08 per share. Investor sentiment going into the company's earnings release has 81% expecting an earnings beat The company's guidance was for revenue of $263.00 million to $267.00 million. Consensus estimates are for year-over-year earnings growth of 600.00% with revenue increasing by 33.90%. Short interest has decreased by 37.7% since the company's last earnings release while the stock has drifted higher by 12.1% from its open following the earnings release to be 31.9% above its 200 day moving average of $63.71. Overall earnings estimates have been revised higher since the company's last earnings release. On Wednesday, March 4, 2020 there was some notable buying of 1,698 contracts of the $87.50 call expiring on Friday, March 20, 2020. Option traders are pricing in a 8.5% move on earnings and the stock has averaged a 10.0% move in recent quarters.

(CLICK HERE FOR THE CHART!)

DISCUSS!

What are you all watching for in this upcoming trading week?
I hope you all have a wonderful weekend and a great trading week ahead wallstreetbets.
submitted by bigbear0083 to wallstreetbets [link] [comments]

Any Tips for Binary trading?

any suggestion of training and seminar for binary trading? Thank you
submitted by SirMj450 to options [link] [comments]

TokenClub Bi-Weekly Report — Issue 114(5.4–5.17)

TokenClub Bi-Weekly Report — Issue 114(5.4–5.17)

https://preview.redd.it/kkhj7agzz5251.png?width=875&format=png&auto=webp&s=f47007e7923d8f40d98e3ba7d08a31c3729a0bd3
Hello everyone, thank you for your continued interest and support. In the past two weeks, various tasks of TokenClub have been progressing steadily. The product development and community operation progress this week are as follows:
1. TokenClub Events
1)TokenClub & 499Block reached strategic cooperation in live broadcasting
On May 28th, TokenClub and 499Block reached a strategic cooperation to jointly build a live broadcast ecosystem in the vertical field of blockchain.
2)520e events
When 520 comes, TokenClub launches live interactive interaction. During the event, participate in interactive questions in the live broadcast room or forward the live poster to Twitter and the telegram group, and upload a screenshot to have the opportunity to extract 520, 1314 red envelope rewards

https://preview.redd.it/apyee28406251.png?width=1080&format=png&auto=webp&s=9c9798db931ad6611d6c258907120610ae11ff11

3)Text version of live content is abailable on Medium
In order to better understand the live broadcast of TokenClub by overseas communities, we translated the live broadcast content into English and uploaded it to TokenClub’s Medium official account, so that the community’s small partners can view it.


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4)Preview: TokenClub’s self-media grandma is invited to participate in the golden financial theme live event
From May 29th to June 4th, Golden Finance will hold a five-day live broadcast of the theme of “Finding Double Coins”. Grandpa Coin will express his views on June 3, welcome to pay attention.

2.TokenClub Live
1) Summary
Recently, Binance Co-founder He Yi, TRON founder Sun Yuchen, Hobbit HBTC founder Ju Jianhua, OSL chairman Dave, BlockVC founding partner Xu Yingkai, Outlier Ventures founder amie Burke, Bitribe founder SKY, CryptoBriefing CEO Han Kao , Huarai Group / Vice President, Global Market and Business Leader Ciara, Guosheng Securities Blockchain Research Institute Sun Shuang, Tongtongtong Research Institute CEO Song Shuangjie, Jin Tiancheng Law Firm Senior Partner Yu Bingguang, Binance China Jiang Jinze, principal researcher of Blockchain Research Institute, Meng Yan, vice president of Digital Asset Research Institute, co-founder of Primitive Ventures & director of Coindesk advisory board-Dovey Wan, founding partner of Genesis Capital & co-founder of Kushen Wallet Ocean Liao Yangyang, Binance C2C-Kathy, Binance OTC-Coco, Binance Contract & Options-Justin, Binance VIP-Jennifer, Binance Broker-Jess, Binance Mining Pool-Denny, Harbin Institute of Technology Blockchain Research Executive Deputy Director Xu Zhifeng, dForce founder Yang Mindao, Mars Finance co-founder Shang Silin, Cobo & Yuchi co-founder Shenyu, well-known investor Xu Zhe, CasperLabs CEO Mrinal Manohar, CasperLabs co-founder Scott Walker, Chairman of Rock Tree Omer Ozden, Nova Club incubation team leader & Waterdrop Capital partner Zheng Yushan, Rolling Stone miner founder Alex Lam, BitUniverse coin founder Chen Yong, Odaily Planet Daily founder and CEO Mandy Wang Mengdie, Binance stablecoin BUSD project responsible Helen Tu and senior expert of TokenClub blockchain and cryptocurrency investment strategy-Zao Shen talks with you about blockchain things ~
On May 18, Block 101 Binance Key Account Manager Luna talked to Primitive Ventures co-founder, non-profit bitcoin development fund Hardcore Fund executive director, and Coindesk advisory board director-Dovey Wan, to understand “C and C How is the Goddess of Crypto Assets made? “Dovey Wan shared with us on asset allocation, investment judgment, entrepreneurship, DCEP, etc.


https://preview.redd.it/0dsry36906251.png?width=1080&format=png&auto=webp&s=a7f6f4b852547d2e43114f81a981f7aa6ea10f61
On May 19, Block 101 Yingge talked with Sun Zeyu, the founding partner of Genesis Capital and co-founder of Kushen Wallet, to share the theme of “Blockchain Investment Experience”. This investor, who is rated as “reliable” by insiders, recommends that novices try not to touch contracts, do not stay overnight even when making contracts, be alert to risks, refuse gambling, and rationally analyze investments.

On May 20th, 499Block ’s two-year birthday carnival “Global Hot Chain, Keeping Together for Every Year” celebration was held in the TokenClub Live Room. The cross-border AMA Solitaire + popular day group anchor live video sharing, including Binance Co-founder He Yi, TRON founder Sun Yuchen, Hobbit HBTC founder Ju Jianhua, OSL chairman Dave, BlockVC founding partner Xu Yingkai, Outlier Ventures founder amie Burke, Bitribe founder SKY, CryptoBriefing CEO Han Kao, Huobi Group / Vice President Global Markets and Dozens of blockchain leaders from home and abroad, such as Ciara, the business leader, all appeared on the scene, and 499Block became a popular beauty angel group to help the interactive host.


https://preview.redd.it/ga6ey51b06251.png?width=1280&format=png&auto=webp&s=d94cc1a03640538ec1e99443c8cbb7a5e77596de
On May 20, Sun Shuang, senior researcher of Guosheng Securities Blockchain Research Institute, Song Shuangjie, Jin Tong, CEO of Tongzhengtong Research Institute were jointly invited by Lingang Xinyefang, Lingang Innovation Management School, and Binance China Blockchain Research Institute. Tian Bingguang Senior Partner Yu Bingguang, Binance China Blockchain Research Institute Chief Researcher Jiang Jinze, Vice President of Digital Assets Research Institute Meng Yan, and many experts talked about the “Critical Digital RMB DCEP” in the live broadcast, one A feast of intertwined thoughts is worth watching again!

On May 21st, Ocean Liao Yangyang, the founder of Block 101 Seven Seven Dialogue Force Field, focused on the “big enlightenment era of digital assets”, Ocean shared with us his entrepreneurial experience, the first pot of gold, public chain, currency circle and Analysis of the current market. Regarding the future of Bitcoin, Ocean feels that he can work hard towards the direction of digital gold and become a substitute or supplement for gold. He is determined to see more, because the ceiling of the entire industry is very high, and he still cannot see its end point. The index level is rising, far from being over.

On May 22, “In the name of the Pizza Festival, we came to a different live broadcast” Bringing Goods “”, which was organized by the girls in the 101-day group of the block: June 6, July 7, Sisi, Yingge, Qianjiangyue , Dialogue: Binance First Sister, Binance C2C-Kathy, Binance OTC-Coco, Binance Contract & Options-Justin, Binance VIP-Jennifer, Binance Broker-Jess, Binance Mining Pool-Denny. We have explained to us one by one about C2C, OTC, contract options, etc. If you are interested, please move to the live room.


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On May 22, Block 101 Sisi Dialogue Xu Zhifeng, executive deputy director of the Blockchain Research Center of Harbin Institute of Technology, shared the theme: “Strategy of Great Powers: Seizing New Highlands of Blockchain Technology”. He expressed his views on his own currency circle experience, entrepreneurship, blockchain technology, DECP, etc. Xu Zhifeng is very optimistic about the future development of blockchain. He said: “Ten years later, blockchain will become a very common industry. We are the Internet industry and have never changed.”

On May 23, the old Chinese doctor Zao Shen from the coin circle went online ~ The theme of this issue: If you want to be short, you must be able to sing first, and if you want to be long, you must be patient. If the meal is not fragrant, the game is not good, and the happiness of the past has drifted into the distance, just because the daily reading is still a loss, and the head is hurt. Don’t panic, the old Chinese doctor Zao Shen of the currency circle will adopt the Trinity Interventional Therapy and precise care to regenerate life. Don’t move quickly to the live room to see what “therapy” is.

On May 25, Block 101, July 7th conversation with dForce founder Yang Mindao, talked about “DeFi opportunities and challenges.” Yang Mindao believes that the four biggest benefits of DeFi are: programmability; non-custodial nature; non-licensing; composability. He believes that the current public chain market is seriously homogenized, and the most promising public chain is Ethereum. Ethereum is the best and largest in terms of developer group, ecology, and technological evolution, and can absorb the advantages of each public chain. At the same time, he is also extremely optimistic about DeFi, “DeFi application value is gradually verified, and the value of this type of token will gradually become more prominent.”

On May 26th, Mars Finance co-founder Shang Silin Hardcore Dialogue Cobo & Yuchi co-founder Shenyu and well-known investor Xu Zhe. The trend of “financialization” in the digital asset industry is becoming more and more obvious, and the friends of miners need to master more and more skills. Unveiling the mystery of hedging for everyone.

On May 26th, Nova Superstar Dialogue Phase 13 focused on the Silicon Valley star project CasperLabs, specially invited CasperLabs CEO Mrinal Manohar, CasperLabs co-founder Scott Walker, Rock Tree chairman Omer Ozden, and Nova Club incubation team leader Water Capital Partners Zheng Yushan, discuss CasperLbs together.
On May 26, Block 101 Sisi talked with the founder of the Rolling Stone Miner, Alex Lam, and took us into the “post-worker life” of a PhD in finance. Alex shared the reasons for entering the coin circle, the first pot of gold, mining, pitted pits, investment experience and opportunities in the digital currency industry. Alex said: Bitcoin exceeds US $ 100,000, and it will be in the second half of next year or the year after.
On May 27th, Block 101 Yingge talked with BitUniverse founder Chen Yong and shared the theme: “Who” needs grid trading. Chen Yong mainly introduced the currency trading tool of Bitcoin. In his view, grid trading has changed an investor’s concept-from stud into a batch of positions and positions. Regarding the price of Bitcoin, Chen Yong believes that the price of Bitcoin may reach one hundred thousand dollars around 2030.

On May 28, Block 101 Binance Mining Pool Wu Di talked to Mandai Wang Mengdie, founder of Planet Daily Odaily, to learn more about the process of “media entrepreneurs marching into the blockchain from venture capital circles”. Mandy believes that the core competence in the media industry is high-quality original content, which is the most basic but difficult to stick to. The initial focus of entering the mixed media industry of the dragon and dragon is to focus and amplify value.

On May 29th, Block 101 Qianjiangyue Dialogue Hellen Tu, the project leader of Binance Stablecoin BUSD project, talked with everyone about the stablecoin “Life and Death”, Hellen shared the stablecoin in detail, and published his own the opinion of. For details, please move to the live room.

On May 30th, Zaoshen came to share the theme: Dongfeng blowing, bullets flying, unlimited chase? In this issue, Zao Shen shared with you the recent international financial situation and various major events in the United States in the past week, which extended to the impact on the currency circle and answered various questions about investment strategies. Friends who want to know more details can move to the live room of Zao Shen.
3.TokenClub operation data
-Live data: 13 live broadcasts in the past two weeks, with over 800,000 views. TokenClub hosted a total of 870 live broadcasts with a total of 45.06 million views.
-Binary trade data: In the past two weeks, guess the rise and fall to participate in a total of 1268 times, the amount of participation exceeded 2 million TCT. At present, it is guessed that the rise and fall function has participated in a total of 1.11 million times, with a cumulative participation amount of 498 million TCT.
-Chat data: In the past two weeks, a total of 19271 messages have been generated. A total of 4.85 milliom messages have been launched since the function was launched.
-Mini-game data: The mini-game has participated in a total of 4212 times in the past two weeks. A total of 1,66 million self-functions have been online.
-Cut leeks game data together: Since the game was launched, the total number of user participation in the game was 962612 TCT total consumption was 6,27 million gift certificate total consumption was 15,95million and TCT mining output was 161496.
-TokenClub KOL data: Over the past two weeks, the total reading volume of the BTCGrandpa article has been viewed by more than 300,000 people.
-Social media data: At present, the number of Weibo official accounts is 18033 and the number of Twitter followers is 1332 and we have opened the official Medium account this week, welcome to follow.
-Telegram official group data: In the past 2 weeks, there were 238 chats in the group, and the total number of Telegram official groups is currently 2906.
-Medium data: Medium official account u/TokenClub has published 5 excellent articles, official announcements and updates are published in English, welcome to follow.
4.Communities
1)Overseas Community
TokenClub held an event for forwarding Twitter and telegram group chats for overseas users. Bitcoin halved in less than two weeks, overseas users are more active in the telegram group, and some friends are more concerned about Binance Block 101 live broadcast, aggregation exchange, TCT usage and other issues, the administrator responded in time.On May 12th, when Bitcoin was halved, TokenClub organized a forwarding Twitter, telegram group chat prize event and participating in a live question asking interactive prize event for overseas users. There are many live broadcast events in the near future. The live broadcast poster information will be released to overseas users as soon as possible. The follow-up TokenClub will translate and broadcast high-quality live broadcast content to Twitter and Medium. Bitcoin halved, overseas users are more active in the telegram group, and some partners are more concerned about block 101 live broadcast, bitcoin future price trend, TCT usage and other issues, the administrator responded in time in the group.


https://preview.redd.it/2nrknnyo06251.png?width=1080&format=png&auto=webp&s=fb98b385c0caf7e65c7b3b2bb1edd782ec126905
2)Domestic community
Sweet Orange Club Weekly News
Last Friday, a holiday, the community opened the red envelope rain event, and brought a sincere gift to everyone while relaxing in the holiday. At the same time, it also sent the most sincere blessings to all mothers in the community on Mother’s Day. Thank you for your long-term support and help to the Orange Club community.

Hundred-day scheduled investment event (Phase II)
The fourth week of the second 100-day fixed investment plan held this week has been awarded, and everyone is still very active in this event. This week, the Bitcoin halving market was also opened in advance. The small partners participating in the fixed investment should now have a certain floating win, so we adopt the correct cycle investment strategy to believe that it can bring unexpected benefits to everyone.
Sign in the lottery.
On the evening of May 3rd and May 10th, TCT Fortune Free Academy carried out the 51st and 52nd week sign-in sweepstakes, and rewarded the small TCT partners who had always insisted on signing in. In these two sign-in sweepstakes, the lucky friends received 20–180TCT as a reward. In addition, during the lucky draw, the college friends also actively expressed their opinions on the topic of this year’s bull market.

The Leek Paradise Community Conference will continue as usual every Sunday at 20:00. During the conference, members will discuss recent hot topics, including gifts and blessings for Mother ’s Day, and the halving of Bitcoin everyone is paying attention to. At the end, the friends in the group also showed a rare enthusiasm at the first sight. It seems that the market still affects the mood. The members routinely started a red envelope rain to cheer for the participating partners and encourage everyone to maintain patience and confidence. Of course, at the same time, we are encouraging ourselves to see the community meeting next week. Come on!

TokenClub volunteer community, sign in red envelopes every day, as long as you sign in every day, you can get good benefits, friends join us quickly! In the past two weeks, the community has conducted active partners.
Volunteer community: Change to the currency circle consultation and pass the analysis of Grandma Coin and Panda analysts, support TokenClub in action, and continue to vote for TCT. In the last month, we have worked hard to learn the rain god’s strategy. We have doubled the coins in our hands. The community WeChat group has recently injected fresh students. We look forward to more people joining! Volunteer community, will continue to work hard for TokenClub
TCT has been listed on Binance、Okex、Gate.io、ZB-M、MXC、Biki、Coinex、BigOne、Coinbene、Cybex、SWFT、Loopring、Rootrex etc.
TokenClub website: www.tokenclub.com
Telegram:https://t.me/token\_club
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Hedging Trades Using Binary Options - YouTube Binäre Optionen Handeln - YouTube Learn Hedging Strategies for Binary Options Trading ... HEDGING HIGH LOW BINARY BOT BINARY OPTION HEDGING! Secret strategy to earn money. Binary Options Strategy That Works - 2019 Hedging ... Binäre Optionen / So einfach Funktioniert der OTC Handel / 1 of 2

Binäre Option statt enges Stop-Loss? Bei einem Hedgeschäft wird eine abzusichernde Position durch die Eröffnung einer gegenläufigen Position gegen Verluste geschützt. Eine Longposition im EUR/USD kann etwa durch eine binäre Put-Option abgesichert werden. Fällt der EUR/USD wird der Verlust in FX-Konto durch den Gewinn in der Option ausgeglichen, sofern die beiden Positionsgrößen ... A very popular hedging method in binary options trading is “the straddle”. This strategy is not easy because it’s difficult to find the righ setups. It’s a strategy about two contracts with different strike price to the same asset. Let’s see a screen shot. This binary option chart is from GBPUSD currency pair. The general idea of this ... Hedging gibt es in verschiedenen Varianten, sodass zum Beispiel auch im Zuge der binären Optionen unter anderem zwischen einer konservativen und einer aggressiven Absicherungsstrategie unterschieden wird. Beim konservativen Hedging werden fast immer die einfachen binären Optionen genutzt, also die Call- oder Put-Optionen. Dem Spekulanten geht ... Die Option würde abhängig vom gewählten Broker bei Fälligkeit Ende des Monats etwa zwischen 70 und 85 Prozent Rendite bringen, falls der DAX dann immer noch über 7.800 Punkten notiert. Man hat also derzeit einen netten Buchgewinn erzielt. Falls die binäre Option am Monatsende jedoch aus dem Geld verfällt (wenn der DAX dann unter 7.800 Punkten notiert), hat man aber nicht nur seinen ... What exactly is the Binary Options Hedging Strategy? Before putting it in a binary options-context, we must first look into the meaning of the hedging itself. In simple words, hedging means mitigating, controlling or limiting risks. A real-life hedging is, for instance, buying insurance for your house that will act as a hedge against weather ... Trader können mit Hilfe von binären Optionen nicht nur beide Marktrichtungen flexibel und mit kalkulierbarem Risiko handeln, sondern das Finanzinstrument der Option auch zur Absicherung von bestehenden Positionen, etwa im Forex-Markt, einsetzen.Die Absicherung einer längerfristigen Trading-Position gegen negative Kursentwicklungen wird als „Hedging“ bezeichnet. Je weiter der per One-Touch-Option prognostizierte Zielkurs vom aktuellen Kurs entfernt ist, desto höher ist die potentielle Rendite. Bei eher unwahrscheinlichen Kurszielen kann Sie bis zu 500 Prozent pro One-Touch-Option liegen, für ein erfolgreiches aggressives Hedging reichen allerdings Renditen im Bereich von 200 Prozent vollkommen aus. Aus einem bereits spekulativen Geschäft wird so ...

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Hedging Trades Using Binary Options - YouTube

Binary Options Strategy That Works. Check this amazing opportunity - http://copypasteacademy.com/opportunity Binary Options Strategy - "Binary options hedgin... binary option hedging strategy binary option how to win binary option hourly strategy binary option how it works binary option iq binary option indicators cryptocurrency trade initial coin ... Binäre Optionen / So einfach Funktioniert der OTC Handel / 2 of 2 - Duration: 12:22. ... Hedging - Funktioniert es wirklich? - Duration: 18:25. Optionsstrategien 8,317 views. 18:25 . CRV 1:10 im ... http://option.go2jump.org/SHu84H - Der Handel mit binären Optionen ist für viele interessierte Trader noch Neuland. Deshalb bieten wir eine übersichtliche Bi... BO209 - A video to help traders reduce losses and have stronger money management skills. This video demonstrates how to hedge ranging markets and the benefit... Make sure you have watched the video "BINARY OPTION HEDGING" to the very end cause we tried so hard Leave you comments below this media, we appreciate any of your opinion about binary options ... Get Your Free Candlestick Guide: http://bit.ly/candlestickguide In this video, Gail shows you how to hedge a position using binary options when trading forex...

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