What Timeframes to Use to Calculate Betas

The beta of a stock is a measure of the stock’s volatility in relation to the market. In other words, it is a measure of how much a stock price fluctuates with the overall market. A higher beta means more volatile and a lower beta means less volatile. A stock with a beta of one is said to be as volatile as the market itself. A stock with a beta of two is twice as volatile as the market. And so on. A stock’s beta can be affected by a number of factors, such as the company’s size, earnings, and industry.

Beta is an important metric for investors to consider because it can help them understand the risk involved with investing in a particular stock. It is important to remember that beta is a historical measure. Just because a stock had a certain beta in the past does not mean it will have the same beta in the future.

Beta is usually calculated over a period of 5 years using monthly data. But is it an appropriate timeframe for calculating betas?

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Reference [1] studied various timeframes for calculating beta. It pointed out,

The traditional CAPM beta is almost exclusively calculated over a return period that spans a window length of 60-months, at one-month return frequencies. It is one of the most utilized models in the asset management industry to assess systematic risk. Yet there is limited evidence to suggest that these estimation parameters are optimal. Utilizing data between January 2000 and December 2021 for the Russell 1000 index, we test daily, weekly, and monthly beta estimations to calculate tracking errors (TE) for the use of these betas in predicting subsequent performance over daily, weekly, and monthly timeframes. We identify that daily CAPM betas are best for predicting subsequent period daily returns and that weekly CAPM betas are strongly correlated with forward weekly and monthly period returns. Leveraging the significant advances in computing resources and the increasing utilization of high frequency trading strategies, we argue that additional window length and return interval-based CAPM betas should be calculated for estimating the systematic risk embedded in diversified portfolios.

In short, daily and weekly betas are more accurate.

This article brings up an interesting idea that we should perform similar studies regarding realized volatilities.

Let us know what you think in the comments below or in the discussion forum.

References

[1] Pankaj Agrrawal, Faye W. Gilbert and Jason Harkins, Time Dependence of CAPM Betas on the Choice of Interval Frequency and Return Timeframes: Is There an Optimum? Journal of Risk and Financial Management 15(11):520, 2022