Correlation and Stock Beta Explained
Correlation measures how two return series move together over a chosen sample. Beta measures a series’ sensitivity to a specified benchmark through covariance divided by the benchmark’s variance.
How it works
Correlation is bounded between −1 and +1; beta is not. Beta=Cov(asset,benchmark)/Var(benchmark), assuming nonzero variance. Use aligned total returns, currencies, frequency and dates. Historical estimates vary with the window and can change during stress.
Worked example
If benchmark variance is 0.0004 and covariance with a stock is 0.0006, estimated beta is 1.5. In a simple fitted relationship this suggests a 1% benchmark move corresponds to about 1.5% stock movement around the model, not a daily guarantee. A high-volatility stock can have moderate correlation yet high beta.
Amounts, prices and scenarios are fictional teaching examples. They exclude any effects not explicitly stated and are not trade recommendations.
Limits and common mistakes
Beta omits some issuer-specific and nonlinear risks. Correlations can rise in crises, and short samples are noisy. Negative historical correlation does not guarantee a hedge during the exact event an investor wants protection from.
Knowledge check
Does beta 1.5 guarantee a 15% gain if the market gains 10%?
Read the explanation
No. It is an estimated sensitivity, not a deterministic return rule. Residual movement, model uncertainty and changing exposure remain.
References and further reading
- SEC Investor.gov: stocks, ownership and risks
- SEC: company filings and financial reports
- SEC: beginners’ guide to financial statements
These sources explain the underlying concepts and specifications. They do not endorse QBMFX Academy. Check the relevant market, protocol version and reporting rules before applying an example.