We Stopped Trading Earnings After We Saw This New Research

Earnings season comes around four times a year for stocks, and, as traders, we’ve always loved the idea of trading these events for the crush in implied volatility and quick potential moves in option strategy positions. However, after analyzing 1,546 earnings events across 40 underlyings over 10 years, we decided to stop trading earnings events completely. In today’s podcast, I’m going to walk through the research on earnings moves and how different options strategies performed under various setups and conditions.

What Was Tested:

  • Selected 40 different ticker symbols across industries, which resulted in 1,546 different earnings events over 10 years.
  • Ran a series of specific option strategies — only selected neutral strategies and not directional strategies
  • Wanted to test both long and short option strategies.: long straddles, long strangles, short straddle, short strangles, short iron butterflies, and short iron condors
  • Within each of these different subcategories of strategies, we tested a lot of different parameters:
  • Different entry days from earnings: 30, 20, 10, 5, or 1 day from the earnings event.
  • Various different strike prices:

— For straddles, we tested the 50 delta and the 40 deltas.

— For strangles, we tested 30, 20, and 10 deltas.

— For short iron condors, we tested different short strikes at 30, 20, and 10 deltas with varying degrees of long strikes at 10 or 5 deltas.

— For iron butterflies, we tested 50 delta iron butterflies and 40 delta iron butterflies with varying degrees of long strikes, again, 20, 10, and 5 deltas out.

  • Tested the ability to exit the position right before the earnings event happened, or the day of the earnings event
  • Tested the days to expiration: front-most weekly contracts and contracts that are 20 to 30 days out from expiration.

Research Findings

1. Did stocks move more or less than their expected move, how often, and by how much?

  • On the day following the earnings event, the opening price of the underlying security fell within the expected move about 1,100 times, or 71%.
  • That proves the theory and hypothesis that we’ve had for quite some time that stocks move less than expected around earnings.
  • The closing price fell within the expected move about 64% of the time.
  • If the closing price or the opening price was greater than the expected move, then the out-performance was on average 34% to 38% greater than the expected move.

2. If the underlying security opens higher after earnings, did it tend to move higher, or did it tend to move lower into the close?

  • The underlying opened higher in 803 of the roughly 1,500 events; basically, it was opening higher 50% of the time.
  • Out of the 803 times the stock opened higher after earnings, the likelihood that it continued higher or closed higher was only 48% of the time.
  • So, not only is the opening price a 50/50 coin flip, but the likelihood that it will close higher if it opens higher is only a 50/50 shot, as well.

3. If the underlying security opens lower after earnings, did it tend to move lower?

  • The underlying opened lower about 47% of the time.
  • Of the 719 cases where the stock opened lower, it actually closed lower 47% of the time.
  • Just because the stock opens lower after earnings doesn’t necessarily mean that it’s destined to close lower.

4. Did implied volatility contract after earnings?

  • Implied volatility contracted 1,395 times out of the roughly 1,500 events.
  • This means that about 90% of the time we saw implied volatility go through a crush or contraction.
  • On average, implied volatility contracted 7.50 points or roughly 20%. That means that the implied volatility rank on average contracted 25 points or roughly 53%.

5. Was a stock more or less likely to move more than the expected when announcing earnings before the market or after the market close?

  • There were 666 instances where earnings were announced pre-market and 880 instances where earnings were announced after the market.
  • When earnings were announced pre-market, the opening price of the underlying security fell within the expected move about 81% of the time, and the closing price fell within the expected range about 73% of the time. 
  • When earnings were announced after the market closed, the opening price of the underlying security fell within the expected move about 64% of the time, and the closing price fell within the expected range about 59% of the time. 

6. Does one earnings season tend to out-perform the rest?

  • There was no quantifiable seasonality in earnings.

 

 

7. Does the stock tend to move higher or lower the day before earnings?

  • Of the 1,500 events tracked, the stock closed higher the day before earnings 45% of the time.
  • The stock closed lower the day before earnings 53% of the time, and 2% of the time remain unchanged.

8. Did the stock consistently out-perform the expected move? If the stock out-performed in one earnings season, did it continue to do so?

  • The stock out-performed the expected move twice in a row on 164 of the occurrences, or about 10.4% of the time
  • The stock out-performed the expected move three times in a row, 77 of the occurrences, or 4.9% of the time.

9. Was the performance of the stock and its expected earnings/IV rank/drop in implied volatility impacted by a sector or industry?

  • 40 stocks in data set: 7 technology, 3 energy, 7 financial, 11 consumer discretionary, 6 communications, 3 consumer staples, 1 healthcare, 1 industrial, 1 metal.
  • Tracked the average move, the average move in implied volatility, average move in implied volatility rank, and average move within the expected range.
  • There was no statistically meaningful difference between the different sectors and industries.

Trading Strategies

We analyzed 648,861 trades using 504 combinations of parameter inputs across 6 strategies through 1,546 earnings events across 40 underlyings over a period of 10 years. Here is what we found.

1. Is there any one particular trade entry time that was better than all of the others across all strategies?

  • When the number of days was considered for the trade, the overall profitability of the different data sets shows that there’s no meaningful difference to trading further out versus closer in.

2. Did option selling strategies outperform or under-perform option buying strategies?

  • In terms of gross profit, the top-performing strategy was actually the 50 delta long straddle entered at 20 days before earnings with 20 days to expiration and exited right after or right at the day of earnings.
  • This particular subset had total profits of $95,000 on all the different strategies and tickers that were tested.
  • The average win was $616, the average loss was $294 — 41% of the time it was a winner, 59% of the time it was a loser.
  • After digging deeper, we discovered 4 of the top 10 trades each generated in excess of $10,000. If the top 10 trades–out of 1,205 trades analyzed–were omitted, the strategy would no longer be profitable, and, therefore, no longer viable.

3. Did implied volatility rank have any real impact on performance?

  • When you look at the win rate of these different strategies when exiting before earnings or exiting the day of or after earnings, there’s really no meaningful difference.
  • The win percentage of each strategy by IVRank exiting the day before earnings:

 

  • The win percentage of each strategy by IVRank the day of/after earnings:

 

  • There was no visible correlation that we could find between implied volatility rank and win rate for any of these trades around earnings.
  • However, we can conclude from the study that there’s maybe a slight advantage to short strategies over long strategies.

4. How did risk defined versus undefined risk strategies perform?

  • The average P&L for defined risk buying strategies was actually profitable. However, the win rate was 32%.
  • Undefined risk trades and defined risk selling strategies both had negative average P&Ls, but had decent win rates; 57%.

  • This again shows that even though we might have won more often with earning trades, it was those large tail moves, whether defined risk or undefined risk, that ultimately caused the position and the strategy to fall apart.

5. Was the performance better, generally speaking, when closing before or after an earnings event?

  • Generally speaking, the option selling strategies lost less money heading into an earnings event where you closed before earnings and lost more money after earnings were released and then you closed the trade.
  • Strategy performance when closing trades the day before earnings:

  • Strategy performance when closing trades the day after earnings:

  • Long option buying strategies generally made more money after the earnings event, and they lost less money before the earnings event. However, they have really low win rates — 31% in some cases.

6. With the performance of options selling strategies, did we find that the performance was better when we were selling higher deltas, or when we were selling further out and lower deltas?

  • When it came to selling and trading high delta positions, we generally found that the P&Ls were better, but the win rates were worse.
  • When you were selling positions, you generally lost less money selling the higher or selling the further out options, but you had a higher win rate as well.
  • Performance when trading high delta positions by definition of risk:

  • Performance when trading low delta positions by definition of risk:

7. What do we learn about tail risk?

  • For this study, we considered the opening move of the stock the day after earnings.
  • If the opening price was greater than the expected move, it was greater by 34% on average.
  • This really shows us that the tail moves are not totally expected, but they do happen more than the models would suggest.

Conclusion

  • The numbers around earnings just don’t make it a strategy that we can really use moving forward.
  • In our opinion, it’s just not worth it to make earnings trades, because they don’t happen often enough to create enough consistency.

 

Option Trader Q&A w/ Steve

Trader Q&A is our favorite segment of the show because we get to hear from one of our community members and help answer their questions live on the air. Today’s question comes from Steve:

My question is about position size. You talk about not having more than 1% to 5% of your position size in anyone ticker. However, is there any way to change that a little bit in the sense that you might be able to spread out that risk among different strikes and different expiration dates and also by placing your trades on different days, so you’re following the market, which I believe you do support that type of strategy? If you place different vertical put spreads, bull put spreads or bear call spreads in different dates, on different strikes and placing them throughout the month, let’s say, for anywhere from one to two weeks, up to four or five weeks out. If you can explain that, I’d greatly appreciate that. Thank you so much.

Remember, if you’d like to get your question answered here on the podcast or LIVE on Facebook & Periscope, head over to OptionAlpha.com/ASK and click the big red record button in the middle of the screen and leave me a private voicemail. There’s no software to download or install and it’s incredibly easy.

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About The Author

Kirk Du Plessis

Kirk founded Option Alpha in early 2007 and currently serves as the Head Trader. In 2018, Option Alpha hit the Inc. 500 list at #215 as one of the fastest growing private companies in the US. Formerly an Investment Banker in the Mergers and Acquisitions Group for Deutsche Bank in New York and REIT Analyst for BB&T Capital Markets in Washington D.C., he's a Full-time Options Trader and Real Estate Investor. He's been interviewed on dozens of investing websites/podcasts and he's been seen in Barron’s Magazine, SmartMoney, and various other financial publications. Kirk currently lives in Pennsylvania (USA) with his beautiful wife and three children.