Home Finance Hedge Fund The Best Way to Use Stock Market Correlations
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The Best Way to Use Stock Market Correlations

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When Alfred Winslow Jones pioneered the world’s first “hedged” fund (the “d” was dropped later) he blew other investors away by borrowing funds to short 20% of the stocks trading at the time. He believed that there was a connection between why some stocks go up while others go down.

Today this principle is commonplace amongst all traders, it’s called hedging. Hedging a portfolio protects investors from cyclical shifts in industry, sector disruption, and other market risks. Alfred was right, after all, fundamental sector relationships translate across asset pricing. These relationships are best exemplified in the close correlation of specific assets.

Gaining an understanding of the relationship between asset classes, and some specific securities can help an investor build a weatherproof portfolio that can withstand the tumultuous forces of the financial markets and hedge against a downside.

Reminder: a correlation of 1 denotes that asset prices are perfectly correlating, a measure of 0 is indicative of no correlation at all, and a negative correlation of -1 indicates that prices move in opposite directions.

Commodity Correlations

Commodity market correlations are driven by like-assets and complementary goods, but generally do not showcase high levels of price-action correlation. Commodities represent raw goods that may be used interchangeably across industries, which lends the asset class to little operational correlation. Unlike with company stock, commodities do not bear fundamental influence on each other.

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Figure 1: Correlation Matrix for Commodity Markets (one year)

The correlation that does exist is mainly tied to intrinsic similarity and shared utility. WTI Crude Oil correlates highly with Brent Oil, which serves as the main benchmark for oil prices because both commodities can be refined into gasoline. Supply shocks also cause similar reactions across both markets, even though WTI Crude is sourced in U.S. oil fields, while Brent is mostly sourced through offshore oil rigs.

Another pair of high volume commodities, Gold and Silver, showcase similar price action profiles for two main reasons. Gold and silver were both used commonly throughout history as a form of currency. Some societies standardized the value of gold and silver, others would peg their own currency to a fixed stock, and some even governed the mint ratio (the price of an ounce of gold divided by the price of an ounce of silver).

Industrial uses for both gold and silver remain abundant, and the two assets share many supply dynamics, which lends to the assets to a correlation.

Futures Correlations

Equity futures markets have several correlations from shared constituents (AAPL is a component of both Nasdaq 100 and S&P 500), and similar sector exposure. Additionally, institutional fund flow, as well as any high volume macro traders, affect multiple equity indices that are within the same market as redemption and inflow will warrant like changes in price action. A large pension fund, for instance, in anticipation of an economic downturn may redeem some of their U.S. equity market positions. This will be spread out across multiple funds covering the SP500, Nasdaq, and Russel 3000 constituents, and thus act as a correlating force in the market.

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Figure 2: Correlation Matrix for World Equity Index Futures (one year)

However, there are still equity markets that exhibit little correlation. It is expected that equity markets should all correlate to a certain extent, exhibiting slightly positive correlations. Investors view equity markets through comparable scopes, and financial market interdependence causes a spillover of systematic risk. For instance, FTSE 100 futures correlate highly with European STOXX 50 futures, which is to be expected since UK and EU businesses are subject to very similar economic conditions. Conversely, the S&P 500 and FTSE 1000 futures have almost no correlation.

Interestingly enough, indices provide investors with so much economic insight that many have started tracking the cross-correlation of multiple index-based securities, including futures and ETFs.

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Figure 3: S&P 500 Tracking Security Correlations

The theory is that a combination of analyzing futures, and index prices, can yield insight into market price-action. Both ETFs and Futures tend to deviate from the underlying S&P 500 – with the former only deviating by a matter of basis points.

Stock Market Correlations

As mentioned before with equity indices, certain large-cap stocks also lend themselves to correlation through fund flows. Additionally, for some stocks there are just fundamental similarities. For instance, companies operating within the same sector may correlate highly during sector-wide disturbances such as tax policy amendments, lobbyist interests, trade events affecting like supply chains, and macroeconomic changes. In the example matrix below, we can see that Microsoft (MSFT) and Apple (AAPL) have a stronger correlation than Advanced Micro Devices (AMD) and Pfizer (PFE), or Boeing (BA) and Alibaba (BABA).

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Figure 4: 30-Day Correlation of Selected US Stocks

Often enough competing companies will showcase a negative correlation around the time of an important announcement. For example, in the case of competing semi-conductor companies Nvidia (NVDA) and Advance Micro Devices (AMD), when one reports positive results the stock price of the other falls.

Foreign Exchange Correlations

The foreign exchange market is an excellent place to observe the effects of foreign policy and trade on global financial markets. Investors can actively trade world currencies in pairs of relative value, for example, EURUSD – the exchange rate of a Euro to the U.S. Dollar, where the base currency is the Euro, which is denominated in the quote currency, the U.S. Dollar. The value of the base currency is expressed in the quote currency, however, it can be difficult to determine the cause of price action of a single pair. For instance, if EURUSD has gone up, the price of the Euro has increased relative to the U.S. dollar. This can mean two things: something has occurred in the U.S. that has made the dollar weak, or something positive has occurred in Europe that has sparked optimism in the Euro. This is why it is important to examine currency value with cross-asset purchase power parity in mind.

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Figure 5: Foreign Exchange Markets Correlation Matrix

The chart above outlines the 30-day correlation between various currency pairs. One of the most noticeable properties of these assets is the inverse relationship of certain assets; EURUSD and USDJPY. Switching quote currencies will instantly yield a negative correlation, as the rate is expressed in reverse as a reciprocal currency rate. The reality is that the only way to asses the relative value and cross-asset correlation of a currency is to build a weighted index and then plot its correlation against another currency (a la U.S. Dollar Index).

Correlations Across Asset Classes

Trading across multiple asset classes allows investors to diversify their holdings and enter positions that can hedge certain financial outcomes. Hedging can be done based off fundamental driver of holding performance. If the portfolio is heavily weighted in energy stocks, holding energy commodities may be beneficial in the event of supply shocks that could underpin company performance, but send oil prices higher. Similarly, currency trading can be used in combination with equity index futures in order to gain holistic positioning in macro-driven strategies.

 

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Figure 6: 30-Day Price Action Correlation Across Asset Classes

The table above outlines the cross-correlation properties of all of the aforementioned securities, showing how prices across multiple asset classes are able to move synchronously.

“Gaining an understanding of how prices move together across global financial markets is imperative to managing a diverse portfolio of assets.”

Depending your goals as an investor you should also consider the data you use in calculating the correlation. If you’re a position trader and have a relatively short holding time, consider using a rolling correlation of 5 days. However, if your holding time usually spans several months consider upping it to 30 days, or even 90 days.

Correlations change fast depending on the rolling period that is employed. The chart below plots the correlation between two assets as the sample size increases.

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This is an example of two positively correlating assets that are both denominated in U.S. Dollars, correlation is endemic to this pair by design.

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Examining the SP500 and Brent Oil price correlation depth chart shows that with a larger observable period, the lower the correlation.

The first half of the chart caters to day traders and position traders, while the latter periods are more important to longer-term traders.

Understanding how prices move with respect to other assets is important for traders of all styles when managing a diverse portfolio.

Employing these methods as part of your portfolio management strategies could save you some downside.

1 COMMENT

  1. Thanks for this interesting article. Even though I am not a very experienced trader and I still have to read up on a lot of basics, I’d be very interested in learning how to actually practically use the given information in trading. Do you have any specific use cases for traders which explain in detail how to benefit from the information gained from such a correlation analysis. Or could you recommend any guide in this matter?

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