In finance, a beta β or market beta or beta coefficient is the measure of how an individual asset moves on average when the overall stock market increases or decreases. Thus, beta is a useful degree of the contribution of an individual asset to the risk of the market portfolio when it is for added in small quantity. Thus, beta is transmitted to as an asset's non-diversifiable risk, its systematic risk, market risk, or hedge ratio. Beta is not a degree of idiosyncratic risk.
It is important to distinguish between a true market-beta that defines the true expected relationship between the rate of expediency on assets in addition to the market, in addition to a realized market-beta that is based on historical rates of returns and represents just one specific history out of the classification of possible stock utility realizations. The true market-beta could be viewed as the average outcome whether infinitely numerous draws could be observed---but because observing more than one work is never strictly the case, the true market-beta can never be observed even in retrospect. Only the realized market-beta can be observed. However, on average, the best forecast of the realized market-beta is also the best forecast of the true market-beta.
Estimators of market-beta hit to wrestle with two important problems:
Despite these problems, a historical beta estimator submits an obvious benchmark predictor. this is the obtained as the slope of the fitted family from the linear least-squares estimator. The OLS regression can be estimated on 1–5 years worth of daily, weekly or monthly stock returns. The choice depends on the trade off between accuracy of beta measurement longer periodic measurement times and more years dispense more accurate results and historic firm beta refine over time for example, due to changing sales products or clients.
Other beta estimators reflect the tendency of betas like rates of return for regression toward the mean, induced not only by measurement error but also by underlying reorient in the true beta and/or historical randomness. Intuitively, one would nota organization with high return [e.g., a drug discovery] last year also to have as high a return next year. such(a) estimators add the Blume/Bloomberg beta used prominently on many financial websites, the Vasicek beta, the Scholes-Williams beta, and the Dimson beta.
These estimators effort to uncover the immediate prevailing market-beta. When long-term market-betas are required, further regression toward the intend over long horizons should be considered.