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Factor investing is an investment strategy that selects securities based on specific attributes that are associated with higher returns.
Factor investing is an investment strategy that selects securities based on specific attributes that are associated with higher returns. There are two main types of factors that drive returns on stocks, bonds and other assets: macroeconomic factors and style factors. The former captures a broad range of risks across asset classes, while the latter aims to explain returns and risks within the same asset class.
Some common macroeconomic factors include: inflation rate, GDP growth rate and unemployment rate. Microeconomic factors include: the company's credit status, stock liquidity and stock price volatility. Style factors involve growth stocks and value stocks, market capitalization and industry sectors.
From a theoretical level, factor investing aims to enhance portfolio diversification, generate market-beating returns, and manage risk. Portfolio diversification has long been popular, but the benefits of diversification can be offset if the selected securities move in tandem with the overall market. For example, when certain market conditions occur, an investor's possible portfolio of stocks and bonds may decline in value. Thankfully, factor investing can offset potential risks by targeting broad, durable, and long-term recognized drivers of returns.
Considering that traditional portfolio allocations, such as 60% stocks and 40% bonds, are relatively easy to implement, factor investing is complicated by the wide variety of factors to choose from. For beginners in factor investing, one can focus on simpler elements such as style (growth vs. value), size (large-cap vs. small-cap), and risk (beta) rather than complex attributes. These attributes are readily available for most securities and are listed in detail on popular equity research websites.
The value factor is designed to capture the excess returns of stocks that are priced low relative to their fundamental value. Typically tracked by metrics such as price-to-book ratio, price-to-earnings ratio, dividends, and free cash flow. [1]
Historically, small-cap portfolios typically have higher returns than portfolios containing only large-cap stocks. Investors can capture this scale effect by looking at a stock's market capitalization. [2]
Stocks that have performed well in the past tend to show strong returns in the future. Momentum strategies are based on relative returns over three-month to one-year time horizons. [3]
Quality factors are primarily defined by low debt, stable earnings, and consistent asset growth. Investors can identify quality stocks using common financial metrics such as return on equity, debt-to-equity ratio, and earnings volatility. [4]
Empirical research shows that low-volatility stocks generally have better risk-adjusted returns than high-volatility assets. [5] The standard deviation measure from one to three years is a common way to capture beta.
A widely used multi-factor model is Fama and French's three-factor model, which is based on the capital asset pricing model (CAPM). The model, developed by economists Eugene Fama and Kenneth French, uses three factors: the company's size, book-to-market ratio and the market's excess returns. In the terminology of the model, the three factors are SMB (small market capitalization minus large market capitalization), HML (high book market capitalization minus low book market capitalization), and portfolio return minus risk-free rate of return. SMB considers small-cap public companies, which generate higher returns, while HML focuses on high book-to-market value stocks, which typically generate higher returns compared to the market. [6]
[1] MSCI. "Factor Focus: Value." Page 2.
[2] MSCI. "Factor Focus: Size." Page 2.
[3] MSCI. "Factor Focus: Momentum." Page 2.
[4] MSCI. "Factor Focus: Quality." Page 2.
[5] S&P Dow Jones Indices. "Low Volatility: A Practitioner’s Guide." Pages 1-2.
[6] Fama, Eugene F. and French, Kenneth R. "Multifactor Explanations of Asset Pricing Anomalies." The Journal of Finance, vol. 51, no. 1, March 1996, pp. 55-84.
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