Low-volatility investing is an investment style that buys stocks or securities with low volatility and avoids those with high volatility. This investment style exploits the low-volatility anomaly. According to financial theory risk and return should be positively related, however in practice this is not true. Low-volatility investors aim to achieve market-like returns, but with lower risk. This investment style is also referred to as minimum volatility, minimum variance, managed volatility, smart beta, defensive and conservative investing.
The low-volatility anomaly was already discovered in the early 1970s, yet it only became a popular investment style after the 2008 global financial crises. The first tests of the Capital Asset Pricing Model (CAPM) showed that the risk-return relation was too flat. [1] [2] Two decades later, in 1992 the seminal study by Fama and French clearly showed that market beta (risk) and return were not related when controlling for firm size. [3] Fisher Black argued that firms or investors could apply leverage by selling bonds and buying more low-beta equity to profit from the flat risk-return relation. [4] In the 2000s more studies followed, and investors started to take notice. [5] [6] [7] In the same period, asset managers such as Acadian, Robeco and Unigestion started offering this new investment style to investors. A few years later index providers such as MSCI and S&P started to create low-volatility indices.
Low-volatility investing is gradually gaining acceptance due to consistent real-life performance over more than 15 years, encompassing both bull and bear markets. While many academic studies and indices are based on simulations going back 20-30 years, some research spans over 90 years, showing low-volatility stocks outperform high-volatility stocks in the long run (see image). Since low-volatility securities tend to lag during bull markets and tend to reduce losses in bear markets, a full business cycle is needed to assess performance. Over shorter time periods, such as one year, Jensen's alpha is a useful performance metric, adjusting returns for market beta risk. For instance, a low-volatility strategy with a beta of 0.7 in a 10% rising market would be expected to return 7%. If the actual return is 10%, Jensen's alpha is 3%.
Any investment strategy can lose effectiveness over time if its popularity causes its advantage to be arbitraged away. This could apply to low-volatility investing, highlighted by the high valuations of low-volatility stocks in the late 2010s. [8] Still, David Blitz showed that hedge funds are at the other side of the low-volatility trade, despite their ability to use leverage. Others state that low-volatility is related to the well-known value investing style. For example, after the dotcom bubble, value stocks offered protection similar to low volatility stocks. Additionally, low-volatility stocks also tend to have more interest rate risk compared to other stocks. [9] 2020 was a challenging year for US low-volatility stocks as they significantly lagged behind the broader market by wide margins. [10] [11] Criticism and discussions are primarily found in various academic financial journals, but investors take notice and contribute to this debate. [12] [13]
A couple of books have been written about low-volatility investing:
In finance, the capital asset pricing model (CAPM) is a model used to determine a theoretically appropriate required rate of return of an asset, to make decisions about adding assets to a well-diversified portfolio.
Modern portfolio theory (MPT), or mean-variance analysis, is a mathematical framework for assembling a portfolio of assets such that the expected return is maximized for a given level of risk. It is a formalization and extension of diversification in investing, the idea that owning different kinds of financial assets is less risky than owning only one type. Its key insight is that an asset's risk and return should not be assessed by itself, but by how it contributes to a portfolio's overall risk and return. The variance of return is used as a measure of risk, because it is tractable when assets are combined into portfolios. Often, the historical variance and covariance of returns is used as a proxy for the forward-looking versions of these quantities, but other, more sophisticated methods are available.
In finance, the beta is a statistic that measures the expected increase or decrease of an individual stock price in proportion to movements of the stock market as a whole. Beta can be used to indicate the contribution of an individual asset to the market risk of a portfolio when it is added in small quantity. It refers to an asset's non-diversifiable risk, systematic risk, or market risk. Beta is not a measure of idiosyncratic risk.
In finance, the Sharpe ratio measures the performance of an investment such as a security or portfolio compared to a risk-free asset, after adjusting for its risk. It is defined as the difference between the returns of the investment and the risk-free return, divided by the standard deviation of the investment returns. It represents the additional amount of return that an investor receives per unit of increase in risk.
In finance, Jensen's alpha is used to determine the abnormal return of a security or portfolio of securities over the theoretical expected return. It is a version of the standard alpha based on a theoretical performance instead of a market index.
Market portfolio is an investment portfolio that theoretically consisting of a weighted sum of every asset in the market, with weights in the proportions that they exist in the market, with the necessary assumption that these assets are infinitely divisible.
Long/short equity is an investment strategy generally associated with hedge funds. It involves buying equities that are expected to increase in value and selling short equities that are expected to decrease in value. This is different from the risk reversal strategies where investors will simultaneously buy a call option and sell a put option to simulate being long in a stock.
Active management is an approach to investing. In an actively managed portfolio of investments, the investor selects the investments that make up the portfolio. Active management is often compared to passive management or index investing.
A market anomaly in a financial market is predictability that seems to be inconsistent with theories of asset prices. Standard theories include the capital asset pricing model and the Fama-French Three Factor Model, but a lack of agreement among academics about the proper theory leads many to refer to anomalies without a reference to a benchmark theory. Indeed, many academics simply refer to anomalies as "return predictors", avoiding the problem of defining a benchmark theory.
Momentum investing is a system of buying stocks or other securities that have had high returns over the past three to twelve months, and selling those that have had poor returns over the same period.
In asset pricing and portfolio management the Fama–French three-factor model is a statistical model designed in 1992 by Eugene Fama and Kenneth French to describe stock returns. Fama and French were colleagues at the University of Chicago Booth School of Business, where Fama still works. In 2013, Fama shared the Nobel Memorial Prize in Economic Sciences for his empirical analysis of asset prices. The three factors are (1) market excess return, (2) the outperformance of small versus big companies, and (3) the outperformance of high book/market versus low book/market companies. There is academic debate about the last two factors.
In finance, a stock index, or stock market index, is an index that measures the performance of a stock market, or of a subset of a stock market. It helps investors compare current stock price levels with past prices to calculate market performance.
Modigliani risk-adjusted performance (also known as M2, M2, Modigliani–Modigliani measure or RAP) is a measure of the risk-adjusted returns of some investment portfolio. It measures the returns of the portfolio, adjusted for the risk of the portfolio relative to that of some benchmark (e.g., the market). We can interpret the measure as the difference between the scaled excess return of our portfolio P and that of the market, where the scaled portfolio has the same volatility as the market. It is derived from the widely used Sharpe ratio, but it has the significant advantage of being in units of percent return (as opposed to the Sharpe ratio – an abstract, dimensionless ratio of limited utility to most investors), which makes it dramatically more intuitive to interpret.
In investing and finance, the low-volatility anomaly is the observation that low-volatility securities have higher returns than high-volatility securities in most markets studied. This is an example of a stock market anomaly since it contradicts the central prediction of many financial theories that higher returns can only be achieved by taking more risk.
In portfolio management, the Carhart four-factor model is an extra factor addition in the Fama–French three-factor model, proposed by Mark Carhart. The Fama-French model, developed in the 1990, argued most stock market returns are explained by three factors: risk, price and company size. Carhart added a momentum factor for asset pricing of stocks. The Four Factor Model is also known in the industry as the Monthly Momentum Factor (MOM). Momentum is the speed or velocity of price changes in a stock, security, or tradable instrument.
Factor investing is an investment approach that involves targeting quantifiable firm characteristics or “factors” that can explain differences in stock returns. Security characteristics that may be included in a factor-based approach include size, low-volatility, value, momentum, asset growth, profitability, leverage, term and carry.
Style drift occurs when a mutual fund's actual and declared investment style differs. A mutual fund’s declared investment style can be found in the fund prospectus which investors commonly rely upon to aid their investment decisions. For most investors, they assumed that mutual fund managers will invest according to the advertised guidelines, this is however, not the case for a fund with style drift. Style drift is commonplace in today’s mutual fund industry, making no distinction between developed and developing markets according to studies in the United States by Brown and Goetzmann (1997) and in China as reported in Sina Finance.
David C. Blitz is a Dutch econometrician and quantitative researcher on financial markets. He is a founding researcher of Robeco Quantitative Investments.
Conservative formula investing is an investment technique that uses the principles of low-volatility investing and is enhanced with momentum and net payout yield signals.
Pim van Vliet is a Dutch fund manager specializing in quantitative investment strategies, with a focus on low-volatility equities. As the head of conservative equities at Robeco Quantitative Investments, van Vliet has contributed to the field through both academic research and practical investment management.