A beta coefficient can measure the volatility of an individual stock compared to the systematic risk of the entire market, a market sector, or style. In statistical terms, beta represents the slope of the line through a regression of data points. In finance, each of these data points represents an individual stock’s returns against those of the market as a whole (or some aspect of the market such as sector, size, or interest rates).
A portfolio’s market beta is the dollar-weighted sum of individual security market betas.
Beta and exposure, though expressed differently, mean the same thing.
A market beta of 1.0 implies a 100% exposure to the market. A market beta of 2.0 implies a 200% exposure to the market.
While market beta is the most common, there are also sector betas, size betas, interest rate betas, and others.
For most, but not all, portfolios market beta is the most significant component of absolute systematic risk. When looking at risk relative to a benchmark (and it’s only relative risk that’s meaningful), market beta is often not the most significant component of risk. So for our purposes, it’s critical to model all betas.
If a fund with a benchmark with market beta of 1.0 has a consistent market beta of 0.8, the fund will underperform by 2.0% when the market is up 10% and outperform by 2.0% when the market is down 10%, absent any impact from security selection.
If a fund has a consistent tech sector beta of 1.5 when its benchmark’s tech beta is 1.0, that fund will outperform by 2.0% if the tech sector outperforms the market by 4.0%
Since market and sector betas other than 1.0 can be obtained passively, performance due to consistent beta differences from the benchmark is not part of active contribution.