Correlations

Correlations in finance measure the statistical relationship between the price movements of two different assets. Think of it as a financial dance partner scorecard. It tells you how likely one asset is to zig when the other zags. This relationship is measured by the correlation coefficient, a number that ranges from +1.0 (perfectly in sync) to -1.0 (perfectly opposite), with 0 meaning no relationship at all. For example, if two stocks have a high positive correlation, they tend to rise and fall together. If they have a negative correlation, one often rises when the other falls. Understanding these relationships is a cornerstone of portfolio construction and risk management. By combining assets with low or negative correlations, investors aim to smooth out the bumps in their investment journey, a strategy known as diversification. It’s about not putting all your eggs in baskets that are likely to be dropped at the same time.

Imagine you own two ice cream stands, one in Miami and one in Helsinki. When it's scorching hot in Miami and sales are booming, it's likely chilly in Helsinki and sales are slow. When a cold front hits Miami, a heatwave might be boosting your Helsinki business. By owning both, your total income is more stable than if you only operated in one city. This is the power of low or negative correlation in a nutshell. In investing, the goal is the same: to build a collection of assets that don't all suffer from the same “bad weather” at once. If your entire portfolio consists of tech stocks, a downturn in the tech sector could be devastating. However, if you also own assets that behave differently, like consumer staples companies or government bonds, a tech downturn might be cushioned by stability or even gains elsewhere in your portfolio. This reduces the overall volatility and helps you sleep better at night. Analyzing correlations is a key part of modern asset allocation.

Correlation comes in three main varieties, each telling a different story about how two investments interact.

This is the “birds of a feather flock together” scenario. When two assets are positively correlated, their prices tend to move in the same direction.

• Example: The stocks of two major, competing oil companies, like Shell and BP. When the global price of oil rises, both companies' profits and stock prices are likely to increase. When oil prices fall, both tend to suffer. Their fortunes are tied to the same underlying economic factor. A portfolio full of highly correlated assets is not well-diversified.

This is the “opposites attract” dynamic. When one asset's price goes up, the other's tends to go down.

• Example: Historically, stocks and long-term government bonds have often shown a negative correlation. During a stock market panic, investors often sell stocks (pushing prices down) and flee to the perceived safety of government bonds (pushing their prices up). This makes bonds a classic hedge against stock market turmoil.

This is the “ships passing in the night” relationship. The price movement of one asset has little to no predictable effect on the other.

• Example: The stock price of a pharmaceutical company and the market price of agricultural commodities like wheat. A breakthrough drug discovery will likely have zero impact on wheat prices, and a bad harvest will not affect the pharma company's stock. Combining uncorrelated assets is a powerful way to achieve true diversification.

While correlation is a central pillar of Modern Portfolio Theory, a strict value investor approaches it with a healthy dose of skepticism. For a value investor, the focus isn't just on statistical patterns but on the underlying business reality. A value investor achieves diversification not by running a correlation matrix, but by following a more fundamental approach:

• Focus on Intrinsic Value: The primary goal is to buy wonderful businesses at a price well below their intrinsic value.
• Business Diversification: Diversification is achieved by owning a collection of excellent businesses that operate in different industries, serve different customers, and have different economic drivers. A company that makes toothpaste, a railroad, and a software company are naturally diversified by their very nature.
• Margin of Safety: The ultimate protection against risk isn't a negative correlation coefficient, but a large margin of safety—the gap between the price you pay and the value you get.

Crucially, value investors know that correlations are not stable. In a true market panic (like the 2008 Financial Crisis), correlations often go to one. Seemingly unrelated assets all plunge together as fear takes over and investors sell everything they can. Relying solely on historical statistics can leave you dangerously exposed when “what usually happens” stops happening.

This is one of the most important lessons in statistics and investing. Just because two things move together does not mean one causes the other. A famous example is that ice cream sales are highly correlated with the number of shark attacks. Does eating ice cream make you more attractive to sharks? Of course not. A third factor—hot summer weather—causes people to both swim more (increasing the chance of a shark encounter) and eat more ice cream. In investing, you might find a strange correlation between the stock price of a Korean microchip maker and the price of Brazilian coffee. It might be a statistical fluke, or there could be a hidden economic reason (like the strength of the US dollar affecting both). Before you build a strategy around such a relationship, you must understand the why. Blindly following correlations without understanding the underlying business and economic drivers is a recipe for disaster.