Beta factor

Beta is a measure of the risk arising from exposure to general market movements as opposed to idiosyncratic factors. The market portfolio of all investable assets has a beta of exactly 1. A beta below 1 can indicate either an investment with lower volatility than the market or a volatile investment whose price movements are not highly correlated with the market. An example of the first is a treasury bill: the price does not go up or down a lot, so it has a low beta. An example of the second is gold. The price of gold does go up and down a lot, but not in the same direction or at the same time as the market Sharpe(1970).

According to the Efficient Market Hypothesis assets with a higher return will have higher associated risk. CAPM states that excess return is only attributable to the non-diversifiable ‘market risk’ and nothing else. Hence if an investor wants to achieve a given return, he or she needs to have a
proportionally large beta loading. This makes higher beta assets relatively more expensive. An investor could alternatively achieve the same level of return by leveraging and buying a greater quantity of the lower beta asset. However, a lot of investors are restricted or prescribed to hold no or low leverage. Also, not all investors have the same cost of borrowing, making such strategy worthwhile. This reasoning lets to a very popular strategy known as ‘Betting against beta factor’ or shortly

Brennan, Black, Jensen and Scholes provide early empirical studies (1973) on the evaluation of CAPM, stating that higher beta assets are more expensive compared to their equilibrium price. There are two common explanations of this anomaly. One approach postulates multifactor models, and the other is that investors bid up the price of high – beta stocks for their embedded leverage. Due to higher demand for assets on the upper part of the capital market line, investors are willing to pay more for higher-yielding assets compared to a lower-yielding asset even if their risk is relatively higher. The beta factor is a strategy where an investor creates a leveraged portfolio of low yielding low beta assets against high beta assets to take advantage of this market anomaly. BAB strategy has been shown to yield positive excess returns in academic studies and investment industry alike.

Key empirical documentation of this strategy is ‘Betting Against Beta’ by Frazzini and Pedersen (2014). Besides US equities, Frazzini and Pedersen (2014) show that BAB achieves abnormal returns in bonds, currencies and international equities (Beta factor in international equities). Asness et al. (2014b) and Baker et al. (2014) find similar results examining industry portfolios and macro-level country selection. Furthermore, in contrast to other anomalies in equities, the profits of exploiting the beta factor seem robust to transaction costs (Asness et al. (2014b)). Kapadia, Ostdiek, Weston and Zekhnini (2015) extend the literature by showing that stocks that are predicted to hedge market downturns out-of-sample significantly outperform those that do not.

Various explanations for the low-beta phenomenon have been put forward, including arbitrage constraints (Liu, Stambaugh, and Yuan 2018), lottery demand (Bali, Brown, Murray, and Tang 2017), regulatory constraints (Blitz, Falkenstein, and van Vliet 2014), leverage and short selling limitations (Asness et al. 2016; Frazzini and Pedersen 2014; Hong and Sraer 2016), or various behavioural biases (Baker, Bradley, and Wurgler 2011).

In conclusion, the ‘low-beta’ and related ‘low-volatility anomaly‘ are one of the most researched in the field of ‘alternative beta’. Despite strong published evidence going back to the 1970s that high beta/volatility stocks underperform relative to expectations generated by the CAPM, the anomaly still persists. However, some argue that BAB returns come just from a standard beta arbitrage. Explanations include investor’s bias, access to capital, misspecification of the CAPM due to option-like nonlinear nature of risk and return, return kurtosis and risk of funding.

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