Low-volatility anomaly: Explained
BY TIO Staff
|กรกฎาคม 30, 2567The low-volatility anomaly is a fascinating aspect of trading that has intrigued market participants for decades. It refers to the counterintuitive observation that low-volatility stocks tend to outperform high-volatility stocks, contrary to what traditional finance theories would suggest.
This phenomenon challenges the fundamental principle of risk and reward, which posits that higher risk should yield higher returns. However, the low-volatility anomaly suggests that this is not always the case in the stock market. In this comprehensive glossary entry, we will delve into the intricacies of the low-volatility anomaly, its implications for traders, and the theories that attempt to explain this perplexing phenomenon.
Understanding Volatility
Before we delve into the low-volatility anomaly, it's crucial to understand what volatility is. In the context of trading, volatility refers to the degree of variation in a financial instrument's trading price over a certain period. It is a key indicator of the risk associated with the instrument.
High volatility implies that the price of the instrument can change dramatically over a short time period in either direction, indicating higher risk. Conversely, low volatility suggests that the price changes are minimal, indicating lower risk. Volatility is typically measured using statistical metrics such as standard deviation or variance.
Types of Volatility
There are two main types of volatility that traders should be aware of: historical volatility and implied volatility. Historical volatility, as the name suggests, is calculated based on the historical price data of the instrument. It provides a measure of the instrument's past price fluctuations.
On the other hand, implied volatility is derived from an instrument's current price and is a measure of the market's future expectations. It is often used in the pricing of options. Both types of volatility play a crucial role in trading and risk management.
The Low-Volatility Anomaly
Now that we have a solid understanding of volatility, let's delve into the low-volatility anomaly. This anomaly refers to the empirical observation that low-volatility stocks tend to generate higher returns than high-volatility stocks, despite their lower risk.
This observation contradicts the Capital Asset Pricing Model (CAPM), a cornerstone of modern financial theory, which posits that expected returns are directly proportional to risk. The low-volatility anomaly suggests that this may not always hold true in the stock market.
Historical Evidence
There is a wealth of empirical evidence supporting the low-volatility anomaly. Numerous studies have found that low-volatility stocks have outperformed their high-volatility counterparts across various time periods and markets.
For instance, a study by Baker and Haugen (2012) found that the 1000 least volatile US stocks outperformed the 1000 most volatile stocks by a significant margin over the period from 1968 to 2012. Similar findings have been reported in other markets around the world.
Theories Explaining the Low-Volatility Anomaly
Several theories have been proposed to explain the low-volatility anomaly. These theories attempt to reconcile this anomaly with traditional finance theories and provide insights into the underlying mechanisms.
Some of these theories suggest that the anomaly is due to market inefficiencies or behavioral biases, while others argue that it is a result of constraints on leverage or the limitations of the CAPM. Let's delve into some of these theories in more detail.
Behavioral Finance Theory
One of the most popular theories explaining the low-volatility anomaly is rooted in behavioral finance. This theory suggests that the anomaly is due to investors' irrational behavior and cognitive biases.
According to this theory, investors tend to overestimate the future returns of high-volatility stocks due to their preference for lottery-like payoffs. This leads to the overpricing of high-volatility stocks and the underpricing of low-volatility stocks, resulting in the low-volatility anomaly.
Constraints on Leverage
Another theory suggests that the low-volatility anomaly is due to constraints on leverage. According to this theory, investors who are unable to use leverage to amplify their returns are forced to invest in high-volatility stocks to achieve their desired level of risk.
This increased demand for high-volatility stocks drives up their prices and reduces their future returns, leading to the low-volatility anomaly. This theory is supported by empirical evidence showing that the anomaly is stronger in markets with greater constraints on leverage.
Implications for Traders
The low-volatility anomaly has significant implications for traders. It suggests that by investing in low-volatility stocks, traders can achieve higher returns with lower risk, defying the traditional risk-reward tradeoff.
However, it's important to note that the low-volatility anomaly does not guarantee that low-volatility stocks will always outperform. Market conditions, economic factors, and individual stock characteristics can all influence the performance of low-volatility stocks.
Portfolio Construction
The low-volatility anomaly can be leveraged in portfolio construction. By including a higher proportion of low-volatility stocks in their portfolios, traders can potentially enhance their risk-adjusted returns.
Several low-volatility indices and exchange-traded funds (ETFs) have been created to provide investors with easy access to low-volatility stocks. These products use various strategies to select and weight stocks based on their volatility.
Risk Management
The low-volatility anomaly can also be used in risk management. By understanding this anomaly, traders can better assess the risk-return tradeoff of their investments and make more informed decisions.
For instance, traders who are risk-averse may prefer to invest in low-volatility stocks to reduce their portfolio risk. On the other hand, traders who are risk-tolerant may choose to invest in high-volatility stocks for their potential for higher returns, despite the low-volatility anomaly.
Conclusion
The low-volatility anomaly is a fascinating aspect of trading that challenges traditional finance theories. Despite its counterintuitive nature, it has been supported by a wealth of empirical evidence and has significant implications for traders.
By understanding this anomaly, traders can enhance their portfolio construction and risk management strategies, potentially achieving higher returns with lower risk. However, it's important to remember that the low-volatility anomaly does not guarantee that low-volatility stocks will always outperform, and traders should always consider other factors when making their investment decisions.
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