I just want to share with you folks a quick earnings analysis for Facebook based on option prices.

Implied move = 7.57% (up or down) or about 15.3 points at current prices.

Mean historical move after earnings = 5.48%

As you can see options are on the overpriced side when compared with the mean move, and doing a statistical analysis we can get the probability options dealers are correct:

Probability of being correct = 64.8%

Which is a bit higher than a coin toss, and provides a very small edge for those of you that want to bet on the same side that options dealers. In other words, playing this earnings cycle with a non-directional play have a positive small edge (betting on the move being contained within the 15.3 points range up or down).

Personally, the edge is too small for me. Remember that earnings plays are very speculative and it is better to take trades with bigger edges.

We know that options tend to be overpriced just before earnings, but how can we quantify the level of overpricing or underpricing? In fact, what is the best way to take advantage of this?

In this post, we are going to walk through a real earnings analysis for Amazon, which reports on July 25, 2019. For reference, I’m writing this on July 22 so I still don’t know what is going to happen a few days from now. The methodology that I follow involves a few steps that I’m going to be developing as you follow along.

The first thing we need to do to figure out if an earnings play is attractive is to compute what is the magnitude of the move that options prices are implying. I know that a lot of people out there uses the price of the at the money straddle of the nearest expiration to get an idea of it, but this is the wrong way of computing the implied move. The ATM straddle doesn’t contain information at all about how much dealers expect the stock to move. The reason is that options dealers price options in a risk-neutral distribution, and also, the price of the options assume continuous hedging until expiration. Using the ATM straddle as a reference for the move is wrong because it assumes that dealers won’t hedge at all until expiration and that assumption is false. However, that doesn’t stop most of the professional press corps out there using the straddle to measure move expectations. I have seen this done in very prestigious publications like the WSJ or Bloomberg.

The best way to obtain an idea of the real implied move is to use implied variance computed directly from options prices and that is how I do this myself.  I use the same methodology that is used by CBOE to compute the VIX index, and I apply it to all expirations dates. So if we do that with amazon we get this:

   Symbol Expiration   VIX
1    AMZN 2019-07-26 48.62
2    AMZN 2019-08-02 35.83
3    AMZN 2019-08-09 31.16
4    AMZN 2019-08-16 29.37
5    AMZN 2019-08-23 28.08
6    AMZN 2019-08-30 27.39
7    AMZN 2019-09-20 26.36
8    AMZN 2019-10-18 26.13
9    AMZN 2019-11-15 23.91
10   AMZN 2020-01-17 27.71
11   AMZN 2020-06-19 28.73
12   AMZN 2020-09-18 28.59
13   AMZN 2021-01-15 29.08
14   AMZN 2021-06-18 28.59

You can see that implied volatility is very elevated for the July 26 expiration which is the day after earnings have been reported and then it starts to decrease the longer we move away from earnings. With this information, we can compute the implied move by using the cumulative property of variance, or better yet we can use the Earnings Tool from the Gamma Central app to do this for us. Applying the methodology to AMZN we get:

Implied move: 4.4% or 87 points at current prices (up or down).

Remember that the implied move doesn’t tell us anything about direction, only that options are priced as if AMZN will move 87 points up or down the next day. This information is useful because we can now compare it with historical moves after earnings and see if options are overpriced or not with respect to previous cycles. We can get historical earnings information from public sources like the EDGAR database, from the SEC, or again, we can just use the Earnings Tool from the Gamma Central app. In this case, the information shows the following:

Mean move after earnings: 5.95%

Standard deviation: 4.22%

Right from the numbers, it looks like AMZN options are being underpriced with respect to the historical mean for some reason. Even more, if we include the standard deviation that shows that sometimes AMZN has moved quite a bit above the mean. This piece of information is also very interesting and it is pointing to some complacency on the part of options dealers, they seem to think that AMZN won’t move much after the report but that doesn’t align well with historical precedent and in fact, we can compute the following probability:

Prob move is within implied parameters = 35.9%

What the probability is telling us is that is very likely that AMZN will move more than 87 points after earnings and that looks like a tremendous edge for a nondirectional play. We just need to design a trade that profits nicely if the stock moves more than the 87 points implied. But before all of you go out and start looking at options, remember that there are still a couple of this before earnings and the situation can change a lot just before them.

This example was done just to illustrate a good earnings analysis before designing a trade. Remember that there are no magic recipes and we always have to assume risk in order to make money. But at least knowing where options dealers stand and the odds involved in the bet will provide us with some edge when designing the trade itself. And that is exactly what I’ll do in my next post. Stay tuned!

Is that time of the year again and a new earnings cycle starts. And again the questions about how to play earnings with options start to popup in the GammaOptimizer service and other spaces that I frequent. So the purpose of this article is to provide some guidance and to bust some myths associated with earnings and options.

Right out of the gate I’ll let you in a secret: There is no magical way to make money with options when playing earnings, period. If anyone is selling you a bulletproof “system” or a fantastic strategy that works all of the time run really fast and really far and don’t waste your hard-earned money with those charlatans. The cold hard truth is that at the end of the day options are just securities like other things out there (shares, futures) and the only way of making money with them is by taking risks and doing the good ole, buy low, sell high thing. Sorry to burst your bubble.

Of course, stock options are not “just securities”, they do offer incredible features that can be exploited in our favor and enhance the risk-reward of a trade but at the same time they can also imperil our trading and more so during special moments of extreme volatility like earnings cycles. So Caveat Emptor as they say.

I have a good section on Option Pricing theory and the importance of implied volatility in my Master Class online course. But for the sake of brevity, I’ll try to condense the relevant bits to earnings here. The important thing to consider here is that option prices are very sensitive to expectations of future volatility in the underlying stock. The main reason is that options dealers need to hedge their risk, and hedging costs increase with volatility, as well as the number of shares needed to hedge a particular option. Of course, dealers always want to be ahead of the curve and they tend to overprice options to take into account this. Most of the time retail traders don’t notice the overpricing that much, but during earnings, it is hard to miss. I bet that many of you have noticed that options get outrageously expensive just before the earnings announcement and there is a very good reason for that. The reason is that in reality is almost impossible for most option dealers to hedge their risk exposure during the event. You see, US companies have this interesting habit of reporting earnings when the market is closed. There might have been a good historical reason harkening to the days when quotes were broadcasted in ticker-tape machines, but in modern markets, I don’t really see any reason for that tradition to continue, but I digress! The net result of companies choosing to report material, market-moving news during periods of extreme low (or no) liquidity is that stock prices tend to move like crazy, I mean really crazy once some modicum of liquidity becomes available again. Perhaps if earnings were reported during market hours would change all of that, but I digress again!

So, the reality is that options dealers are mostly shout out of any sane hedging opportunities when the stock starts to move like crazy, so they have to use the nuclear option and price stock options like if the world would end that day. And that is why options are so expensive just before the earnings release. The worst feature of the earnings cycle is that once the stock reopens again the overpricing is gone and options drop significantly in price (what is known as the volatility crunch).

So what can we do about that? Well, I’ll post part 2 very soon on how to advantage of the overpricing and volatility crunch. But in the meantime here are a couple of recommendations:

– Don’t play earnings with outright options (single calls, or single puts). You are most likely than not to lose money on it due to the overpricing.

– If you must play a particular direction, try to use very tight vertical spreads to minimize overpricing and the effects of volatility crunch.

– Most of the time is better if we can see how overpriced options are and then try to exploit that to our advantage (wait for part 2) ideally with a direction neutral type of trade (my favorite construction).

Understanding the GT level
Or the not so invisible hand of the market.

You see me posting the GT level from time to time in the main room, and every day in the GammaOptimizer service, and it is also displayed real-time in the full Variance Center app. But what does it mean? And why is it important?

To better answer those questions I need to start by explaining the acronym. GT is an abbreviation for the Gamma Threshold level. And right there you know that it is related to options (as they are the only equity securities that exhibit Gamma, or Convexity properties). More exactly the Gamma Threshold is computed from options in the S&P 500, all of them, which as today they number more than 11,000 in total. But why do we care about SPX options at all? The answer will be surprising to many of you that are unfamiliar with market microstructure.

The invisible hand of Options Dealers.

Myths have a very interesting property, one way or another they are grounded in some amount of truth. Even though the evil Market Maker myth is false, it doesn’t mean that Options Market Makers don’t have an outsized influence in markets, the reality is that they do. And in modern markets (post-2009) market microstructure has changed dramatically in such a way that hedging activity by a certain type of options market participants has a tremendous effect on the market. The reality of the options market today is that microstructure is getting more complex day after day. In the past, we used to have speculators and MMs, but now Market Makers are dying and they are being replaced by High-Frequency Traders and joined by Volatility Traders (that can be HFT) which are risk-neutral in price but not in volatility (in other words they speculate with volatility). The current picture creates a new breed of participants that in the aggregate I’ll call Options Dealers or Dealers for short.

The common feature of Options Dealers is that for whatever reason, making markets or playing volatility, they are risk-neutral. And here is the key to the effect they have in other markets. You see, in other to be risk-neutral in the options world they need to trade the underlying stock (or basket of stocks) in such a way that they total net directional risk approaches 0.0, in other words, they need to constantly hedge their risk exposure, to make sure that their risk is very low. And it is this action of hedging that has an effect on the market. In its most basic form, hedging means buying or selling shares in the underlying in such a way that the total amount of delta/gamma risk for an Options Dealer remains very small over a window of price changes in the stock (or basket of stocks). Most dealers hedge at certain points during the day: At/near the open, at/near the close, and whenever their delta risk is starting to become too large during the day. Of course, you can imagine that hedging by a single option dealer has a very small effect on the price of a stock and you would be right most of the time. However what happens if the options market is so big that it starts to dwarf the market in the shares themselves? In that case, risk-neutral hedging by options dealers will start to have a noticeable effect on the underlying market.

Index Options Dealers

There is a special segment of options activity and that is the Index options space, in particular, SPX options (and also SPY options in a smaller degree). The Open Interest of the full SPX option chains surpasses 14,500,000 contracts and if you think that each contract commands a multiplier of 100, we are talking about a notional Open Interest of more than $4.4 Trillion dollars which is a staggering amount of money.  The size of the SPX options market is incredibly big and getting even bigger. And it is precisely in this space that hedging activity by options dealers has an outsized effect in the overall market. The reason is that the underlying for SPX options is the S&P 500 basket, so hedging activity in SPX options affects all of the 500 stocks that are part of the basket.

The popularity of SPX options and in particular of SPX weekly options (SPXW series) has been in an uptrend for the past several years and most of the new market participants are Volatility players and certain types of low volatility funds. The end result is that recent hedging activity is having an outsized effect in a stock market with dwindling trading volumes (which have been in a negative trend for several years now). In other words as fewer people trade shares, more and more players are trading SPX options, which leave Index Options Dealers as a big source of trading activity during certain times of the day.

Two kinds of Gamma Hedging

Not all hedging activity is the same and it all depends on the sign of the cumulative gamma of a portfolio. Imagine for a second that you are an Options Dealers with just one single short put in your book (you sold a put to a retail buyer). How do you hedge your delta/gamma risk? Because you are short a single put your hedge is also short the underlying (you sell shares of the underlying stock). Now let’s imagine that your book is instead a single long call option (you bought a call from a retailer that wanted to short it), how do you hedge the risk? Again, the hedge is selling shares to hedge the risk. In both cases, your book is long delta, in other words, you make money if the underlying goes up and that is why you go short in both cases for the initial risk-neutral hedge. However, both books are incredibly different from that moment on.

The moment the underlying starts to move hedging becomes very different for both cases. Let’s imagine that the stock is going up in price so we need to hedge our new delta/gamma risk after the move. For the lonely short put book, the amount of deltas to hedge has decreased so we need to reduce the total amount of short shares in the underlying, in other words, we become net buyers of shares when the stock rises (make a mental note of this important fact). Now, what happens if the stock moves down? The deltas to hedge increase and we need to increase our short as well, and therefore, in that case, we become net sellers of shares when price declines (Notice a pattern here?).

Repeating the exercise for the book with the lonely long call. If the stock goes up, the deltas of the Call increase and we need to increase our short hedge, in other words we become net sellers when the stock goes up (compare wit the previous case). Now, if the stock comes down in price, the deltas of the call decrease so we need to decrease our short hedge by covering, so in other words, we become net buyers of the stock when price declines (again, notice a pattern here?)

In the first case (short put) we say we our book is short gamma, and in the second case (long call) we say that our book is long gamma. And as you can see short gamma hedging is very different from long gamma hedging. If the amount of hedging is sizeable short gamma hedging tends to accelerate the moves because we need to buy when the stock goes up, and sell when it is going down. So hedging activity adds fuel and momentum to the prevailing direction. The opposite is true for long gamma hedging as we sell when the stock goes up, and buy when the stock goes down. So long gamma hedging provides a break to the market moves, it slows down momentum quite a bit if the hedging is sizeable.

Of course in real life the book of a given Options Dealers is very complex, as it might contain a mix of long/short calls and puts with many different sizes, but at the end the total gamma exposure and in particular the sign of the gamma exposure can be computed and we can know if he/she is long gamma or short gamma in the aggregate.

The GT level again

And that exactly is what the GT level does. It is a mathematical computation based on a set of assumptions, using publicly available information, to try to estimate the point where SPX options dealers are neutral (gamma exposure is 0). Once that point is computed it is very simple to compare the current value of the SPX index and see if dealers are net-long gamma or net-short gamma. For example, the GT level for yesterday was around 2927 (all in SPX points) and with the market trading above 3013 by the end of the session it means that SPX options dealers are net-long gamma (because we are above the GT level). And after this long post, you can see now why that insight is important. The reason is that hedging activity in SPX options will tend to slow down any moves in the market up or down (because dealers are hedging against the market), which in turn reduces volatility and has a secondary effect of producing residual upside drift (that I leave as homework).
There is also an additional insight to knowing that we are in a long gamma regime. For those of you that are expecting a downside leg in the market, and in particular a big downside leg, notice that a long gamma regime will work against that thesis because hedging activity will try to reverse any sudden big moves down (as we have seen for the past weeks). So it is important to check where the market is with respect to the GT level. Once you see SPX getting closer to it, then the potential to flip short gamma gets really big and consequently the door for bigger moves down also opens. In the meantime, we remain in a long gamma regime and my expectation is that it will last until the end of August at least, so be prepared for very little volatility and upside drift in SPX until then.

Anatomy of an Earnings Play

One of the most interesting and challenging trades with options is an earnings play. The main reason is the huge amount of uncertainty that surrounds the stock before an after the numbers are released. For that reason option dealers start to overprice massively the cost of options so they can offload a big chunk of risk into unsuspecting option buyers. This overpricing is such that even if the trader gets all the parameters of the thesis correct it is very likely that he/she will lose money on the trade because of the collapse in implied volatility that happens the next day.

An example with TSLA earnings for October 24/ 2018

Case in point is Tesla, which is a stock that is very volatile during normal times and can become right down crazy around earnings announcements. For the Oct 24 2018 earnings calls it was even crazier as the company decided to move forward the announced (it was scheduled for several weeks later) and there was massive speculation about the reasons why. Because of this option dealers were pricing the Oct 26 options as if TSLA will move at least 13.5% up or down after the releases (which suffice to say is a massive implied move).  In other words options were incredible expensive the afternoon of Oct 24. I decided to take advantage of this overpricing because in the past TSLA had moved about 6.5% after earnings releases and also because of the expected volatility collapse the next day was massive for Oct 26 options (about 90 vols of drop). Given my bullish stance and the expected volatility collapse the best trade was a binary risk reversal.

Binary Risk Reversal

The idea behind this kind of trade is to have a directional exposure to the stock and at the same time to take advantage of the volatility collapse the next day. The basic trade is this one:

• Sell downside binary TSLA Put for Oct 26.
• Buy upside binary TSLA Call for Oct 26.

Given that the market for single stock binary options is non existent in the US the trade was replicated as follows:

BUY 1 TSLA Oct26 270 PUT / SELL 1 TSLA Oct26 272.5 PUT / BUY 1 TSLA Oct26 322.5 CALL / SELL 1 TSLA Oct26 325 CALL

If you pay close attention to the trade you will notice that it consist of a short vertical put spread and a long call spread in a single trade.

The cost of the trade was actually a credit of $0.34 per contract (got paid to enter), but of course the trade requires a net collateral of $2.16 (which is the max risk). Here is a simulated profit and loss profit for the position:

As you can see the trade works in several regions, if TSLA ends below 270 we have a max loss of $2.16, between 272.5 and 322.5 we get to keep the credit received of $0.34 and if it moves above 325 then we get the max gain of $2.84. Not a bad trade at all.

As it happened at the close that day reported very good earnings, and it opened the next day around 319 (before starting to drop during the day). At the open I managed to close to the trade at 0.81 credit, so in essence I got paid to enter and got paid to exit for a net profit of $1.15 which is a return of 47% over max risk. Not a bad day at the office at all.

Source of the Edge for the Trade

The trade worked because the thesis was fulfilled. TSLA moved substantially high the next day and volatility collapsed really hard as well and that precisely was the main source of the edge. The short put spread in the position lost huge amounts of value (therefore providing a fat profit) due to vol collapse and the upside nove. While at the same time the upside call spread remained stable bringing a net profit on the whole trade. And that was the key to this particular position, the fact that option dealers overpriced options so much the day before allowed us to enter into this trade with a nice statistical edge.

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