Being a core part of modern portfolio theory,
Alpha quantifies the above-market return which an investment delivers, while beta measures how volatile, or risky, an investment is relative to the market. As such, alpha strategies (some believe smart beta funds fall under this category)
Meanwhile, beta is a volatility measure and is synonymous with risk. A beta value of more than 1 implies that a fund is more volatile than the market and so investors stand to either gain more when markets rise or lose more when markets fall. Conversely, a beta of less than 1 shows that a stock or fund is less volatile than the market.
But some investors and market commentators believe the link between volatility and risk is nonsensical.
Long-term investor Warren Buffett has famously denounced the relationship between risk and volatility on more than one occasion, and has spoken against the relevance of modern portfolio theory.
Modern portfolio theory suggests that market returns are difficult to beat, and doing so requires skill and or taking on additional risk.
But a lot of modern portfolio theory is premised on the assumption of efficient financial markets, where information is readily available and markets price securities efficiently. Moreover, returns and performance are adjusted for risk (volatility).
Many investors question why this should be the case. For example, consider separate investments in two funds, A and B. If over a 10 year period the returns from fund A were double those of fund B, then most investors would naturally have preferred a holding in company A – even if its price fluctuated more than B’s did. However, depending on the magnitude of price fluctuations, or volatility, modern portfolio theory might portray the returns of funds A and B as the same
on a risk-adjusted(or
Buffett believes risk should rather be thought of as the possibility of loss, while dismissing volatility as a risk proxy. He focuses rather on the long-term fundamentals of a company and its prospects, with far less quantitative analysis than modern portfolio theory promotes. To an ultra long-term investor, short-term volatility (or ‘noise’) can be irrelevant to overall performance.
Long-term investors often buy stocks when volatility spikes and prices fall – for example, when other short-term investors sell in a panic amid severe financial market events. While greater volatility represents greater risk, or higher beta values, investors like Buffett see little change in long-term risk if a company’s prospects remain intact.
On that argument, volatility may act as a proxy for risk to the short-term investor though the link is less clear to long-horizon investors. In other words, risk means different things to different investors.
The implications for risk-return measures alpha and beta
For fund managers and alternative index providers seeking alpha returns, the delinking of volatility and risk makes the capital asset pricing model (CAPM) largely irrelevant, since this model uses a stock’s beta measure (or volatility risk) to calculate expected returns.
But alpha and beta have a number of other uses in the CAPM model and beyond. For one, they allow investors to analyse the performance of fund managers and gauge whether a fund’s returns are the result of superior fund allocation or simply the result of market movements.
Even many critics of modern portfolio theory believe that the theory, and its alpha and beta risk-return measures, still has a role to play in making efficient investment decisions. And as markets develop and information becomes more rapidly available – edging modern portfolio theory’s assumption of efficient markets closer to realisation – the theory may become more watertight.
Some studies have shown that factor investing strategies, which target underlying risk factors based on quantitative analyses, can generate market-beating returns over long time horizons. Many risk factors themselves are proof of inefficient market pricing. For example, value stocks are undervalued by the market (often because investors are irrational) and offer an opportunity for long term growth.
Smart beta investing, for example, can provide exposure to these factors through alternative index construction.
By taking advantage of underlying stock attributes – sometimes market abnormalities which result from inefficient markets – smart beta funds can target alpha returns or control risk. Investment performance is measured against market benchmarks.
By targeting various factors, smart beta, risk premia and other factor strategies can replicate hedge fund returns.
In an attempt to smooth returns and sometimes to beat the market, some factor investing strategies target low volatility, or low beta, funds.