Correlation

Correlation is a statistical measure of the degree to which two assets (or variables) move in relation to one another, expressed as a correlation coefficient ranging from -1 to +1. A coefficient of +1 indicates a perfect positive linear relationship (the assets move in lockstep in the same direction), -1 indicates a perfect negative (inverse) linear relationship, and 0 indicates no linear relationship. In trading and portfolio risk management, correlation is used to assess how positions interact: strongly positively correlated holdings concentrate risk because they tend to gain or lose together, whereas low or negatively correlated holdings can reduce the variability of a combined portfolio. Correlation describes the degree of linear co-movement only and does not imply causation, nor is it a constant — coefficients are calculated over a chosen historical window and can shift materially as market conditions change.

In plain English — Correlation answers a simple question: when one thing moves, what does the other one usually do? In trading, it describes how the prices of two assets tend to move relative to each other over a given period. The relationship is summarised by a number called the correlation coefficient, which always sits between -1 and +1 and measures the strength of a linear (straight-line) relationship: - A value near +1 means the two assets tend to move in the same direction at the same time (when one rises, the other usually rises too). This is called positive correlation. - A value near -1 means they tend to move in opposite directions (when one rises, the other usually falls). This is negative or inverse correlation. - A value near 0 means there is no reliable linear relationship — knowing what one does tells you little about the other in a straight-line sense (though a more complex, non-linear relationship could still exist). As a rough guide, many traders treat readings above roughly +0.7 or below roughly -0.7 as a "strong" relationship, and anything between about -0.3 and +0.3 as "weak." These are conventions, not hard rules. The big idea for risk management is this: if you hold several positions that are all strongly positively correlated, you may feel diversified because you own different tickers, but in reality you are taking on heavily overlapping exposure. If those assets fall together, your losses can stack up at the same time. Holding things that are uncorrelated or negatively correlated is one way people try to spread risk. Two critical cautions: First, correlation is not causation — two assets can move together by coincidence or because they both respond to a third factor, without one driving the other. Second, correlation is not fixed. It drifts over time and can change sharply, especially during market stress.

Suppose a trader holds three positions and assumes they are diversified: shares of two large technology companies and a position in a tech-sector ETF. Looking at past data, the trader measures the correlation between the two tech stocks and finds a coefficient of about +0.85, and each stock shows roughly +0.80 correlation with the ETF. All three values are well above the +0.7 "strong positive" convention. What this reveals: although the account holds three different instruments, they have historically behaved almost like a single, larger position. On a day the technology sector sells off, all three would likely fall together rather than offsetting one another. The apparent diversification is largely an illusion. For contrast, imagine the trader instead measured the correlation between a stock index position and a position in a defensive asset and found a coefficient of -0.4 over the same window. A negative reading like this means the two have historically tended to move in opposite directions, so a loss in one was often partly cushioned by the other — though, as always, past co-movement is not a promise about the future. These figures are hypothetical illustrations, not a description of any specific real-world relationship.