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  • Leapday Quantitative Research Team

2022 mid-year update: REACTION signals remain strong


Summary


This report provides a 2022 mid-year update on the performance of the Leapday REACTION signals. In the first half of 2022 amidst a massive global stock market sell off which saw the SPY fall 20%, a portfolio that traded all 3 REACTION entry points (t0 open + 60 min, t0 close, and t1 open) with constant capital of $50M per entry point ($150M total) returned 7.8% with a Sharpe ratio of 1.66 and correlation to SPY of -0.06. In comparison, the same portfolio had an average return of 4.8% with a Sharpe of 1.68 in 2016-2021 H1 and an average return of 6.3% with a Sharpe of 2.32 in 2016-2021 H2. If trading is restricted to only the 500 most liquid stocks, the portfolio would have returned 8.0% with a Sharpe ratio of 2.16 in 2022 H1, as compared to an average return of 2.4% with a Sharpe of 1.03 in 2016-2021 H1 and an average return of 4.9% with a Sharpe of 2.15 in 2016-2021 H2. Additionally, when we apply the market direction filter (which was discovered in our 2021 research), the performance improves and outperforms historical averages. These portfolio results are inclusive of conservative trading cost assumptions.



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Market Recap


The first half of 2022 was the stock market’s worst first half performance in over 50 years with the S&P dropping 20% and NASDAQ dropping nearly 30%. Rising inflation was a big headline with the annual inflation rate as measured by CPI rising 9.1% in June of 2022, the highest since November of 1981. The preceding record-setting stock market run fueled by quantitative easing and cheap money has ended and been replaced by rising interest rates and a Fed that is playing catch up after underestimating inflation. Numerous geopolitical risks hover including the continuation of COVID-19 and lockdowns in China, a global supply chain that remains clogged, and Russia’s ongoing invasion of Ukraine. Amidst this volatile and uncertain environment, Leapday’s REACTION signals continued to do well with strong 2022 H1 performance that we present below.



Performance Update


Our previous portfolio construction reports presented performance for portfolios constructed using the top one-third of REACTION signals for each of the entry points (t0 open + 60min, t0 close, t1 open) and for a combined portfolio that trades all 3 entry points. These portfolios use constant capital of $50M per entry point ($150M total for the combined portfolio) and include conservative trading cost assumptions. The full list of assumptions for constructing the portfolios is provided in the Appendix.


This report provides an update on portfolio performance through the first half of 2022. We begin with a chart that displays the portfolio performance of the combined portfolio that trades all 3 entry points with $50M of constant capital per entry point inclusive of costs. We show performance for a portfolio that trades all stocks as well as a portfolio that restricts trading to only the most liquid 500 stocks. Additionally, we provide performance without and with the market direction filter that was discovered in our research last year.



Below we provide the returns and Sharpe ratios for 2022 H1 and compare these metrics to historical H1 and H2 performance between 2016-2021. We provide these metrics for each of the 3 entry points as well as the combined portfolio using all 3 entry points. These breakdowns include results without and with the market direction filter as well as without and with trading costs.


First we show portfolio metrics for the first half of 2022 compared to each half historically from 2016 to 2021 without costs.



The results for 20221 H1 are generally strong compared to the same half in prior years. The result that stands out the most is the performance of the liquid 500. In particular when using all 3 entries the liquid 500 stocks returned 9.0% compared to the historical average of 3.2%. Next we look at the Sharpe ratios for the portfolio returns.



Aside from the t0 open + 60m entry we see strong Sharpe ratios across entry points and whether or not the market direction filter is applied. Next we show portfolio metrics for the first half of 2022 compared to each half historically from 2016 to 2021 with costs.



Combined portfolio returns for 2022 H1 with costs also exceeded historical performance with strong returns. Sharpe ratios in 2022 H1 were slightly below average likely due to the increased volatility in the market relative to the historical period but remained strong overall. The t0 close and t1 open entry points had very strong H1 performance while the t0 open + 60m underperformed. As mentioned above, the liquid 500 stocks also had a very strong H1 with returns that outpaced their historical average. Additionally, results continued to show improvement when applying the market direction filter while also outperforming historical results with the filter applied.


Finally, below we examine the correlation of each portfolio to SPY and to the other portfolios for 2021 H2. We focus on the portfolios that trade all stocks and without the market direction filter.



In the first of half of 2022, portfolios built using REACTION signals continue to exhibit uncorrelated returns with equities. In addition, there continues to be added value from using all 3 entry points of signals.



Conclusion


In this report we provide a 2022 mid-year update on the performance of the Leapday REACTION signals. A portfolio that trades all 3 entry points (t0 open + 60 minutes, t0 close, t1 open) with constant capital of $50M per entry point ($150M total) returned 7.8% with a Sharpe ratio of 1.66 and correlation to SPY of -0.06 in 2022 H1. In comparison, the same portfolio had an average return of 4.8% with a Sharpe of 1.68 in 2016-2021 H1 and an average return of 6.3% and Sharpe of 2.32 in 2016-2021 H2. If trading is restricted to only the 500 most liquid stocks, the portfolio would have returned 8.0% with a Sharpe ratio of 2.16 in 2022 H1, as compared to an average return of 2.4% with a Sharpe of 1.03 in 2016-2021 H1 and an average return of 4.9% with a Sharpe of 2.15 in 2016-2021 H2. These metrics are inclusive of conservative trading cost assumptions.


Additionally, when we apply the market direction filter discovered in our 2021 research, the performance of the portfolio trading all 3 entry points improves returning 9.9% with a Sharpe ratio of 2.26 in 2022 H1. When trading is restricted to only the 500 most liquid stocks and the market direction filter is applied, the portfolio would have returned 7.6% with a Sharpe ratio of 2.67 in 2022 H1.


A breakdown of performance by entry point indicates that the t0 close and t1 open signals outperformed historical averages in 2022 H1 while the t0 open + 60 min signals underperformed. This is in contrast to 2021 when the t0 open + 60 min signals outperformed but the other entry points underperformed and once again highlights the value of using multiple entry points to trade earnings reactions.



 


Appendix - Assumptions Used In Portfolio Construction


We use the strongest one-third of the 3d REACTION signals for each of the three entry points (t0 open + 60 min, t0 close, t1 open) to build a simulated portfolio. Below we present all the assumptions used in the portfolio construction.


  • Enter and exit trades as follows:

    • t0 open + 60min signal: Enter a trade 60 minutes after the open on the first day the market is open subsequent to a company’s earnings announcement (t0 open + 60 minutes) and exit the trade on the close 3 days later (t2 close).

    • t0 close signal: Enter a trade at the market close on the first day the market is open subsequent to a company’s earnings announcement (t0 close) and exit the trade on the close 3 days later (t3 close).

    • t1 open signal: Enter a trade at the open on the second day the market is open subsequent to a company’s earnings announcement (t1 open) and exit the trade on the close 3 days later (t3 close).

  • Create a market-neutral portfolio by hedging trades using an opposite side trade in SPY with a beta-adjusted notional value that offsets the beta risk of the event trade.

  • Starting capital of $50M per entry point ($150M for the combined portfolio of all entry points), assuming constant capital throughout the portfolio (i.e. - we do not reinvest profits).

  • Portfolio leverage used during periods of high activity.

  • Trade no more than 6 percent of the starting capital per position.

  • Trade no more than 2 percent of a company’s historical average trade value per position for t0 close and t1 open signals. Trade no more than 1.5 percent for the t0 open + 60 min signal. (The historical average trade value is calculated using the trailing 20 day average traded value.)

  • Beyond the two constraints on trade size stated above, trade equal weight.

  • Round-trip trading costs are based on breakpoints for liquidity group as follows:

    • Low (<$3M historical average trade value): 20 bps (40 bps for t0 open + 60 min signals)

    • Mid ($3M-$25M historical average trade value): 10 bps (20 bps for t0 open + 60 min signals)

    • High (>$25M historical average trade value): 5 bps (10 bps for t0 open + 60 min signals)

    • Costs are allocated half on entry and half on exit

    • In the metrics presented above, we assume $0 in hedge costs (for the SPY hedge) and the hedge does not use any equity or margin



 


Disclaimer


This material is solely for informational purposes and is not an offer or solicitation for the purchase or sale of any security, nor is it to be construed as legal or tax advice. References to securities and strategies are for illustrative purposes only and do not constitute buy or sell recommendations. The information in this report should not be used as the basis for any investment decisions. We make no representation or warranty as to the accuracy or completeness of the information contained in this report, including third-party data sources. The views expressed are as of the publication date and subject to change at any time. Hypothetical performance has many significant limitations and no representation is being made that such performance is achievable in the future. Past performance is no guarantee of future performance.


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