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  • Leapday Quantitative Research Team

2023 mid-year update: REACTION performance through the AI boom


Summary


This report provides a 2023 mid-year update on the performance of the Leapday REACTION signals. In the first half of 2023, a portfolio that traded both the t0 open + 60 min and t0 close 3 REACTION signals with constant capital of $50M per entry point ($100M total) returned 2.2% with a Sharpe ratio of 0.89 and correlation to SPY of 0.07. In comparison, the same portfolio had an average return of 5.2% with a Sharpe of 1.60 in 2016-2022 H1 and an average return of 6.7% with a Sharpe of 2.21 in 2016-2022 H2. If the portfolio uses $10M per entry point ($20M total), the portfolio would have returned 10.4% with a Sharpe ratio of 2.10 in 2023 H1, as compared to an average return of 7.8% with a Sharpe of 1.55 in 2016-2022 H1 and an average return of 10.3% with a Sharpe of 2.39 in 2016-2022 H2. Additionally, when we apply the market direction filter (which was discovered in our previous research), the performance improves. These portfolio results are inclusive of conservative trading cost assumptions.



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Market Recap


The first half of 2023 saw stock markets soar with the S&P 500 rising 15.9% and NASDAQ up 31.7%, its best first half since 1983. The year began with markets rallying fueled by optimism that the Fed would pause rate hikes and perhaps cut rates by the end of year. However, markets faced turbulence with stubbornly high inflation numbers and a potential financial crisis sparked by the failures of Silicon Valley Bank and Signature Bank and the forced takeover of Credit Suisse. But by the second quarter, fears eased and equity markets rallied again, driven by the “AI boom” and investor optimism that AI will usher in an age of increased productivity and profitability. Despite a seemingly strong equity market, we head into the second half of 2023 with uncertainty. Inflation remains sticky, expectations are that the Fed will keep rates higher for longer, and the bulk of the stock market rally has come from a handful of the largest tech companies.



Performance Update


This report provides an update on portfolio performance through the first half of 2023. Like previous portfolio construction reports, we construct portfolios using the top one-third of REACTION signals. This report will provide an update on our t0 open + 60 min and t0 close signals. We present performance for portfolios that use constant capital of $50M per entry point ($100M total for the combined portfolio of both entry points) and constant capital of $10M per entry point ($20M total for the combined portfolio) to showcase performance for various end users with differing amount of capital to deploy. Additionally, we provide performance without and with the market direction filter that was discovered in previous research. The full list of assumptions including trading costs for constructing the portfolios is provided in the Appendix.


We begin with a chart that displays the portfolio performance of the combined portfolio that trades both the t0 open + 60 min and t0 close entry points with $50M of constant capital per entry point ($100M total) inclusive of costs. Additionally, we provide performance without and with the market direction filter.



We also show the same chart for a combined portfolio with $10M of constant capital per entry point ($20M total).



Below we provide the returns and Sharpe ratios for 2023 H1 and compare these metrics to historical H1 and H2 performance between 2016-2022. We provide these metrics for the entry points individually as well as the combined portfolio using both 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 2023 compared to each half historically from 2016 to 2022 without costs.



The results for 2023 H1 show that the $50M portfolios underperformed historical numbers for the same half in prior years being driven more so from the performance of the t0 close portfolio. However, both entry points were profitable. The $10M combo portfolio, in contrast, outperformed the same half in prior years with the t0 open + 60 min portfolio strongly outperforming. These results suggest that in 2023 H1, performance for large cap stocks that drive the performance of the $50M portfolio (due to liquidity constraints) underperformed. Next we look at the Sharpe ratios for the portfolio returns.



We see strong Sharpe ratios for combination portfolios across both $50M per entry point and $10M per entry point portfolios, with the $50M combo slightly underperforming the same half in prior years and the $10M combo outperforming. Sharpe ratios increase across the board when the market direction filter is applied. It is interesting to note that for the $50M portfolios, despite below average returns the Sharpe ratios remained strong due to the low volatility environment of the rallying stock market. Next we show portfolio metrics for the first half of 2023 compared to each half historically from 2016 to 2022 with costs.



Combined portfolio returns for 2023 H1 with costs show that the $50M combo underperformed historical metrics with that underperformance coming from the t0 close entry point. However, returns were positive for the half year. The $10M combo, in contrast, exceeded historical performance with strong returns. Additionally, results continued to show improvement when applying the market direction filter.


Finally, below we examine the correlation of each portfolio to SPY and to the other portfolios for 2023 H2. We focus on portfolios using $50M per entry point without the market direction filter.



In the first of half of 2023, portfolios built using REACTION signals continue to exhibit uncorrelated returns with equities.



Conclusion


In this report we provide a 2023 mid-year update on the performance of the Leapday REACTION signals. A portfolio that trades both the t0 open + 60 minutes and t0 close entry points with constant capital of $50M per entry point ($100M total) returned 2.2% with a Sharpe ratio of 0.89 and correlation to SPY of 0.07 in 2023 H1. In comparison, the same portfolio had an average return of 5.2% with a Sharpe of 1.60 in 2016-2022 H1 and an average return of 6.7% and Sharpe of 2.21 in 2016-2022 H2. If the portfolio uses $10M per entry point ($20M total), the portfolio would have returned 10.4% with a Sharpe ratio of 2.10 in 2023 H1, as compared to an average return of 7.8% with a Sharpe of 1.55 in 2016-2022 H1 and an average return of 10.3% with a Sharpe of 2.39 in 2016-2022 H2. These metrics are inclusive of conservative trading costs.


Additionally, when we apply the market direction filter discovered in our previous research, the performance of the portfolio trading both entry points with $50M each improves returning 4.0% with a Sharpe ratio of 2.00 in 2023 H1. When trading size is reduced to $10M per entry point and the market direction filter is applied, the portfolio would have returned 13.4% with a Sharpe ratio of 3.00 in 2023 H1.


A breakdown of performance by entry point indicates that the t0 open + 60 min signal outperformed historical averages in 2023 H1 while the t0 close underperformed. This is in contrast to 2022 when the t0 close signals outperformed while the t0 open + 60 min signals 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 entry point (t0 open + 60 min, t0 close) 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).

  • 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 ($10M) per entry point and $100M ($20M) for the combined portfolio, 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 1.5 percent for the t0 open + 60 min signal. Trade no more than 2 percent of a company’s historical average trade value per position for t0 close 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 below, 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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