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Choosing a Market Benchmark for Portfolio Beta

Article Quant Q&A · Author: rinspy

Summary

The document explains that a portfolio’s estimated beta depends on which market return series is used. Regressing the current portfolio holdings against the S&P 500’s realized historical returns measures their relationship to the index as it actually changed over the sample. Regressing against a backtest of today’s S&P 500 constituents instead asks how the current basket would have behaved historically, which may be more relevant to estimating its forward-looking exposure.

The choice depends on the purpose of the analysis. For risk management, a current-basket proxy or a volatility forecasting model such as GARCH may better target future beta. For ex-post performance analysis, realized index returns or historical constituent baskets may provide a more appropriate comparison. The discussion offers methodological guidance rather than empirical results, and it does not prescribe one universally correct regression: the estimate depends on the question being asked, and stress analysis may call for combining approaches.

Key ideas

  • Beta estimates depend on the benchmark return series used in the regression.
  • Realized index returns capture changes in index composition during the sample.
  • A backtest of today’s constituents may better represent the current portfolio for forward-looking risk estimates.
  • Ex-post analysis may call for realized index returns or historical market baskets.
  • The appropriate method depends on the analytical purpose, and volatility models can offer another forecasting approach.

Tags

Full text
# Calculating beta to market


# Calculating beta to market












Let's say we want to compute beta to S&P500 of a portfolio, using 3 years of weekly returns, as of today. We would take each stock in the portfolio and regress the weekly returns of that stock against the weekly returns of the S&P500 over the 3 years, right?

But let's say the current portfolio consists of exactly the same stocks and weights as the current holdings of S&P500. Beta should be exactly 1, right? Yet when we regress the returns of the current portfolio holdings against S&P500 historical returns, we might get a different value, because the composition of S&P500 changed over time.

So would it not be more correct to regress the returns of the current portfolio holdings against the historical returns of the current basket of S&P500, instead of regressing against the actual historical returns of S&P500?

## Answer by RobAbMo (score 5, accepted)

https://quant.stackexchange.com/a/40285

In a word, yes. That's a correct and valid view to take but, as you'll always find in finance, it really depends on context and the question that you're trying to answer. This is the case in markets but more broadly in business and something that academically minded scientists/engineers struggle often understand and appreciate fully. This boils down to the fact that the words we use in business (and generally outside of the scientific context) are often, if not the majority of the time, ambiguous.

Reading into the context from your question I might guess that you're coming from a portfolio/risk management perspective and what you're really interested in measuring is an estimate of your forward looking beta. Hence any methodological change that improves upon linear regression is welcome. Bear in mind that you can go further than simply updating your market (SPX) returns from realised index to current basket back-test. e.g. GARCH based models for forecasting the volatility (and hence beta) of your portfolio stocks.

On the other hand, the objective may be an ex-post analysis of a portfolio relative to the market. In that case you most likely want to look at realised index rather than the current basket, or perhaps back-test previous market baskets for each time point. Then there could be scenario analyses through stress periods when we might elect to use a combination the above mentioned methods.

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.