The IPO train keeps on moving, with GoodRx debuting this week up 53% in its first day of trading and Palantir and Asana set to hit the public scene next week. We continue our spotlight on IPOs by discussing how to de-risk IPO trades and boost your potential alpha in the name.

Hedging as a Tool to “De-Risk” Your Ideas

In the past, we’ve stressed the importance of hedging to remove market and factor risk that may cloud the alpha in investment ideas. Hedging can be done in a number of ways and the most common way to hedge is using broad market or sector ETFs. For example, if a portfolio is net long, a short SPY hedge can be used to hedge out market risk. These types of hedges can certainly be effective, but can also introduce undesired factor risks into the portfolio.

In order to combat this, we’ve seen a trend towards building customized “smart” hedges. Custom hedges leapfrog the one-size-fits-all approach that limits ETFs and instead allow you to create a more efficient hedge to target factor risk, resulting in a more desirable risk profile that magnifies specific risk.

Omega Point recently released Smart Trades, a new tool that allow our customers to build single stock factor hedges on the fly. For more information on Smart Trades as well as examples of how it can be used, we encourage you to take a look at our recent post highlighting the construction of a sample hedge to reduce the riskiness of a trade on Kodak. We’ll be leveraging this tool to build smarter hedges for the IPOs that we profiled last week.

Smart Trading IPO Bets

When trading a security, we are faced with a few choices of how the to take on the risk of the asset. For simplicity, we’ll assume that specific risk, which generally translates to alpha, is “good” risk, and factor risk, which can translate to unintended bets, is “bad” risk.

1. Invest in the stock → assume all of the risk, both good and bad risk.
2. Invest in the stock; hedge with a broad market or sector ETF → assume less risk, mostly good but still some bad.
3. Invest in the stock; hedge with a factor hedge → assume the good risk with very little of the bad.

To illustrate the various options, we built examples of each type of hedge for Facebook (FB), Uber (UBER), HCA Health Care (HCA), and Snap (SNAP) immediately following their respective IPOs.

Starting off with FB, we constructed a $50M hedge based on the objective of minimizing factor risk for the combined FB-hedge trade on the IPO date. Using the Smart Trade tool, we were able to create a combined trade that resulted in 71% specific risk. FB’s specific risk alone is only 6.5% so including the factor hedge massively increased the alpha of this idea.

We rebalanced the factor hedge every 4 weeks for 1 year and compared the risk profile over time to that of a hedge using a broad US market ETF, the iShares Russell 3000 ETF (IWV), and a hedge using a relevant SPDR S&P sector ETF. We then repeated this process for UBER, HCA, and SNAP.

The above table shows the total risk and factor vs specific risk breakdown for the securities and their hedged trades on the IPO date and 2 weeks, 1 month, 3 months, 6 months, and 12 months after the IPO date.

We see that the Smart Trade consistently yields significantly higher specific risk than the trades using the IWV or sector ETF hedges. This is highlighted in blue in the tables above. In 18 out of 24 scenarios, specific risk was over 90% for the factor hedge. Even though the specific risk in the security alone increased naturally over time as we moved further away from the IPO, the Smart Trade hedge was significantly superior in boosting alpha potential.

Not only is the specific risk superior in all of the hedges using the Smart Trades, but the total risk is lower in the majority of cases. The total risk of the factor-hedged trade was 2-5x lower than the total risk of the individual IPO security alone! This reinforces the idea that factor aware hedging reduces risk while amplifying alpha potential.

Building Superior Hedges

These simple examples show that factor aware hedge construction can significantly de-risk your bets, especially for securities such as recent IPOs that bear a high degree of uncertainty. While there is no tool that removes all uncertainty behind these investments, we can at least engage in the next best thing by using factor hedges to remove unwanted risk and allow our alpha ideas to be the star of the show.

This week’s analysis is just the tip of the proverbial iceberg in terms of what factor-aware hedging can do to help portfolio managers. We plan on holding a series of webinars in the coming weeks to explore hedging best practices in more detail, please stay tuned to learn more.

US Market: 9/21/20 - 9/25/20

• Market results were mixed, as we ended lower for the fourth straight week but saw a slight lift on Friday. Investors continue to grapple with concerns around the next COVID relief package, weak job numbers, and uncertainty around vaccine availability and the upcoming election.
• Thursday saw a Labor Department release of uninspiring jobless claims data, with initial claims for state unemployment benefits up 4,000 to a seasonally adjusted 870,000 for the week ending 9/19 (Consensus estimates were at 840,000). A total of 26 million Americans were on unemployment benefits in early September.
• U.S equity mutual funds and ETFs saw their biggest weekly outflows since December 2018 ($26.87B). This was a whipsaw relative to the prior week, when they were up $22.67B.
• On Wednesday, Goldman Sachs cut its 4Q GDP growth estimate by half, from 6% to 3%, citing “lack of further fiscal support.”

Normalized Factor Returns: Axioma US Equity Risk Model (AXUS4-MH)

Methodology for normalized factor returns

• Growth was the week’s biggest winner, reversing its course from a nadir of -1.92 SD below the mean on 9/18 and moving back towards the mean with a +0.34 SD move.
• Earnings Yield saw continued strength, as it earned an Overbought label at +1.21 SD above the mean.
• Size ended the week completely flat at +0.75 SD above the mean.
• Profitability saw another downward move, and is now on the cusp of Oversold space at -1 SD below the mean.
• US Total Risk (using the Russell 3000 as proxy) declined by 24bps.

Normalized Factor Returns: Axioma Worldwide Equity Risk Model (AXWW4-MH)

Methodology for normalized factor returns

• Growth enjoyed a sizable rally worldwide, up +0.5 SD and looking poised to exit Oversold territory in short order.
• Meanwhile, Value moved away from its recent bottom of -1.12 SD below the mean on 9/16 and exited Oversold space.
• Momentum saw some relief after recent weakness, ticking up from a trough of -1.37 SD below the mean on 9/21.
• After experiencing some positive movement last week, Volatility touched a peak of —0.5 SD below the mean on 9/21 and then reversed course, now sitting at -0.61 SD below the mean.
• Market Sensitivity crossed back into negative territory after finishing last week on a slight upwards note.
• Profitability continued its decline, down -0.3 SD this week and crossing into negative space.
• Unlike the US, Global Risk (using the ACWI as proxy) declined by 18bps.

Please don’t hesitate to reach out if you’d like to see how Smart Trades can help you hedge risk from IPOs or any other equity positions, or discuss the factor trends that may be impacting your portfolio.

Regards,
Alyx