After one of its longest streakest ever above 15 (83 consecutive trading days), the VIX finally broke below that key level in the first week of February. And with market speed quieting down for at least a little while, traders now have the luxury of taking a step back and looking for ways to tweak their approach, tactics, and/or portfolio in the interim.
If you're looking to review some new data that may help you better position your portfolio the next time volatility pops, you should consider tuning into a new installment of Market Measures.
This particular episode takes a closer look at the correlations that exist between some of the best-known stock indices, and whether this data can help us regarding ongoing portfolio strategy.
As you probably already know, correlation measures the degree in which two securities move in relation to each other.
For example, when the prices of two financial assets are positively correlated, that means they move in the same direction (to varying degrees). When two securities are negatively correlated, that means they move in opposite directions (to varying degrees). If no correlation exists between two securities, than the relationship is described as "zero" correlation.
On the show, the hosts review how there's always been a strong historical correlation between SPY, IWM, QQQ, and DIA. The correlation between these four symbols would be characterized as “positive,” because the degree they move together is fairly close to 1 (if it was exactly 1 that would represent a perfect positive correlation).
While this information is certainly valuable, the Market Measures team decided to take this analysis to the next level, and actually backtest whether a similar trading strategy used in each of the four produced the same (or at least similar) results.
A study was therefore designed using the following parameters:
Utilized historical data in SPY, IWM, QQQ, DIA (2005-present)
Backtested short strangles deployed in each underlying
Compared the P/L from each underlying, and the correlation of P/L’s
Because the underlying symbols are so correlated, it probably won’t surprise you that the results of the above study also showed that the respective P/L’s from the same trading strategy were quite similar.
It is interesting to note that the correlations between the P/L’s was slightly lower than the correlations observed between the price movement of the four symbols.
This exercise has demonstrated that deploying the same trading strategy in highly correlated financial assets is akin to doubling down on a bet. This suggests that traders looking to diversify their portfolios, might consider deploying a different strategy when trading across correlated symbols. Additionally, traders could consider trading the same (or different) strategies when trading uncorrelated assets - especially if the goal is to diversify (i.e. reduce concentration) away from a similar bets on the same outcome.
If you want to review this topic in greater detail, we recommend reviewing the complete episode of Market Measures focusing on the correlations of stock indices when your schedule allows. For more information on diversification, we also recommend this past installment of Best Practices as well as this episode of Market Measures.
Should you have any outstanding questions on any of these topics, or want to share feedback from you own trading experience, don’t hesitate to leave a message in the space below, or contact us on Twitter (@tastytrade) or email (firstname.lastname@example.org).
Thanks for reading!
Sage Anderson has an extensive background trading equity derivatives and managing volatility-based portfolios. He has traded hundreds of thousands of contracts across the spectrum of industries in the single-stock universe.
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