Be sceptical the next time someone insists that you buy a high risk stock in order to generate higher returns.
For the longest time, we have known and believed that in order to generate higher returns we must assume higher risk. Thereby, using volatility as a measure of risk, the standard thought process tells us that stocks with higher volatility have the potential to generate higher returns relative to stocks with lower volatility. But, what if this is not always true?
Investment, especially equity market, conversations are often peppered with the word “volatility”. The term is frequently used to validate arbitrary stock price movements and determine potential returns. Consequently, it invokes fear in many but also holds a promise of opportunity. Volatility is simply the range of price changes a stock experiences over a given period of time. If the price movement is relatively stable, then the stock is considered to have low volatility. Conversely, if the stock price movement is erratic and experiences rapid & frequent peaks and troughs, then it is considered to be volatile.
If they are saying it, then it must be true!
Various studies of the US, as well as, global markets have demonstrated a long-term connection between future stock returns and various measures of prior stock price variability, including total return volatility, idiosyncratic volatility and beta. These studies have clearly showed that future returns of previously low-return-variability portfolios significantly outperform those of previously high-return-variability portfolios. These empirical findings have indeed surprised investment professionals as traditional economic theory postulates that higher expected risk is compensated with higher expected return.
One of the bedrocks of finance, the capital asset pricing model (CAPM), endeavoured to derive a relationship between risk and returns. CAPM theorised that the expected return of a stock is a linear function of risk, meaning that higher the risk, the higher should be the expected return. Subsequent studies have however, disputed this assumption and proved that portfolios comprising low volatility stocks have consistently outperformed portfolios comprising high volatility stocks, giving rise to the “Low Volatility Anomaly”.
The low-volatility anomaly is considered one of the greatest anomalies of the CAPM, which is part of the foundation of modern portfolio theory. It is basically an observation that demonstrates that stocks with low volatility consistently outperform high volatility stocks, on a risk-adjusted basis.
There are two primary sources of this anomaly:
· Behavioural Biases – Investors are often ruled by their emotions and can be irrational while making investment decisions. Such investors may eschew low-risk stocks in favour of riskier stocks that are the current flavour of the markets, in the hope for higher returns. Due to the paucity of demand, low risk stocks may be under-priced, thereby increasing their potential for future returns.
· Structural Impediments - Some low-risk investments may be off-limits to certain class or type of investors, making their prices attractive for others.
When making investment decisions, we must recognise that there are various factors that can influence the price of an asset. Volatility is one such factor where risk and return are considered to be inversely related, such that low volatile stocks tend to generate higher returns and vice versa. This is also known as the low-volatility anomaly, the volatility effect or the low-risk anomaly. Therefore, be sceptical the next time someone insists that you buy a high risk stock in order to generate higher returns.