Measuring Correlations Across Global Markets
Jun 16, 2017
By: Sage Anderson
Market information from distant corners of the world is now available at the fingertips of traders and investors located thousands of miles away. Likewise, the interconnected nature of the global supply chain also means stock-related news often ripples across international borders.
For these reasons, it's worthwhile for traders to monitor correlations between international markets and maybe even consider trading these products should they match a trader's strategic approach and risk profile.
A recent episode of Options Jive on the tastytrade financial network takes a look at current correlations between some of the world's largest equity markets, and may be of interest to traders looking for new ideas or further diversification in their portfolios.
Positive correlation, in trading terms, tells us to the degree to which two underlying securities move up and down together. Negative correlation tells us the degree to which two underlying securities move in opposite directions. A high positive or negative correlation may indicate there's an opportunity for the deployment of risk.
Additionally, this episode of Options Jive presents the current correlations (using the past year of data) between SPY and some of the ETFs that represent the international categories discussed in the previous graphic. Not surprisingly, these correlations also are quite high, as shown below:
Average Correlation between SPY and EFA (Non-US Developed Markets ETF): +0.8
Average Correlation between SPY and EEM (Emerging Markets ETF): +0.7
Average Correlation between SPY and FEZ (Eurozone ETF): +0.7
Taking this examination a step further, tastytrade also investigated the correlation between SPY and some of the individual country ETFs. Interestingly, correlations between these products were relatively lower. Of the individual country ETFs, Germany (EWG), the United Kingdom (EWU), and China (FXI) showed the highest correlations of this group, measuring in at +0.7, +0.6, and +0.6, respectively.
In terms of trade idea generation, it’s important to keep in mind several factors. If you are already short premium in SPY, and you sell additional premium in a product highly correlated to SPY, you have effectively increased the exposure of your original position. This is a reason that one might look for offsetting risk in products that are highly correlated.
For example, if the SPY is highly correlated to a hypothetical index XYZ in Country A, and implied volatility in XYZ has an elevated Implied Volatility Rank (IVR), while SPY IVR is low - it may be possible to buy premium in SPY versus selling premium in XYZ - and let mean reversion go to work.
On the other hand, if low correlation exists between two products, there may be the opportunity to diversify your portfolio by deploying risk in both products - using the same structure.
For example, if SPY has a low correlation with hypothetical index ABC in Country Z, and implied volatility is high in both SPY and ABC, a trader may decide to sell volatility in both products. In this case, because the two products are not highly correlated (and therefore don’t necessarily move together) a trader has now diversified their exposure away from SPY, but with a similar high-probability of success profile.
As always, it’s advisable to monitor a product (and possibly even mock trade it) before deploying a live position. At the very least, by adding the country and regional ETFs to your watch list, you may be able to build out your understanding and familiarity of these products in the event you decide to trade them in the future.
We hope you’ll take the time to review the full episode of Options Jive when your schedule allows.
As always, don’t hesitate to reach out at firstname.lastname@example.org with any outstanding comments or questions.
Your feedback is much appreciated!
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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