FACTOR INVESTING for EQUITIES

Factor-Based Investing (also known as “Smart Beta”) utilizes specific factors to choose which stocks have an elevated probability of higher-than-average future returns.  A factor is a specific characteristic of a stock, such as its earnings yield.  Factor investing relies on decades of research on which characteristics of a stock tend to be rewarded by future performance.  Factor-Based Investing has a consistent, systematic architecture in order to improve returns.

Traditional equity indexes are weighted by the market capitalization of each stock. Larger index weights are given to companies with greater market caps, regardless of company fundamentals or other factors that affect stock performance. Factor-Based portfolios, instead, have a proclivity toward one or more of a handful of factors that have been demonstrated to outperform traditional cap-weighted indexes over long periods of time.

Factor-Based Investing combines facets of both passive and active investing. As with an index, factor-based portfolios have a consistent, rules-based approach. At the same time, these portfolios offer exposure to factors employed by many active managers to generate alpha.

Individual factors can have periods of underperformance versus a cap-weighted approach even though, over the long term, the identified factors have historically outperformed. Atlas Capital Advisors’ portfolios address this issue by diversifying amongst factors. The factors supported by extensive academic research and used by Atlas Capital Advisors are:

Value
Size

ABOUT THE INTERACTIVE CHARTS

Each of the factor descriptions below are followed by three charts, which allow you to test different implementations of the factor.  The Ken French dataset provides monthly returns for stock portfolios which are sorted into deciles based upon a factor.  For instance, for Earnings to Price, the dataset has monthly returns for the 10% of stocks with the lowest E/P (decile 1), the next 10% in rank (decile 2) and each decile up to the 10% of stocks with the highest E/P (decile 10).  Stocks are ranked and sorted into deciles each month. The decile sliders at the top of the first chart are interactive – you may select which deciles to be long or short, and the charts will update automatically with the results of the strategy you chose.  For instance, a potential investment strategy would be to own decile 10 while being short decile 1.  Alternatively, one could own deciles 9 and 10 (the best 20% of stocks) while being short deciles 1 and 2 (the worst 20% of stocks).  Or, you could own decile 10 and be short deciles 1 through 9 – this would show how much better decile 10 performs vs. the average stock which is not in Decile 10. 

You may also choose the beginning and end dates for the charts.  For instance, if you are mainly interested in the past ten years you could select 2014 to 2023 rather than 1968 to 2023.

The top chart in each section shows the annual investment return of the long/short strategy you chose. The second chart shows the cumulative return (on a log scale) of the long strategy, the short strategy and the portfolio (long/short) strategy.  The third chart shows the cumulative return of each decile.

Value

In 1992-1993, Eugene Fama and Kenneth French published several academic papers that provided investing ideas that expanded on the classic Capital Asset Pricing Model (CAPM). They showed that over long periods, 90% of returns from diversified portfolios could be explained by 1) beta (the overall stock market return, adjusted for correlation and volatility), 2) valuation, and 3) size.

We recognize that no model is infallible and believe that human behavior is impossible to quantify. However, the Fama-French findings are useful for screening potential investment candidates to include in a diversified portfolio. Below are some of the value factors we consider in our investment decision framework.   Note: the data is presented with price as the DENOMINATOR in the Ken French research, whereas the same ratio is usually presented with price as the NUMERATOR in the media.

Earnings to Price (or (E/P) ratio): The Price/Earnings ratio is the ratio of a company’s stock market price to its net earnings per share. The P/E ratio is a widely known concept, but we prefer the inverse ratio, the E/P ratio or earnings yield, for comparative analysis to bonds, REITs, preferred stocks, and various arbitrage strategies.  An analysis based on E/P rather than P/E is better able to manage situations where earnings are very small or negative. A typical growth company is valued by the stock market based on earnings well into the future and will tend to have relatively low E/P ratio.  A company with a low E/P ratio (e.g., an E/P of 2%: P/E ratio of 50) will have to grow its earnings much faster than a company with a high E/P (e.g., E/P of 10%: P/E ratio of 10) to justify its low E/P.  The factor research indicates that, on average, companies with high E/P have achieved higher investment returns than those with low E/P.  This is attributed to investors tending to be overoptimistic about the future earnings growth of the low E/P companies.

Cash Flow to Price (or CF/P ratio): The CF/P ratio is the ratio of a company’s operating cash flow per share to its share price. Operating cash flow (OCF), as the name implies, is the cash a company earns from its normal business operations. One standard definition: OCF = EBIT (Earnings Before Interest & Taxes) + Depreciation – Taxes. OCF is a good measure of the strength of a company. In theory, companies with a higher CF/P will tend to perform better than those with a lower CF/P as the market ultimately will recognize the company’s underlying strength. We prefer to invest in companies with consistent cash flow and solid cash flow margins. Growth companies frequently are relatively young and unestablished. As a result, they may have little to no stable operating cash flow and correspondingly exhibit low CF/P ratios.

Price-to-Book (P/B) ratio: This is the ratio of a company’s market value relative to its GAAP book value. Book value is found on a company’s balance sheet and represents the total value of a company’s assets minus the value of its debt and other liabilities. We focus on this metric when analyzing the value of a company. We prefer to invest in companies with low price-to-book ratios.

As an example of the potential benefit of Value investing, the chart shows the cumulative difference in return between the MSCI ACWI enhanced value index and the MSCI ACWI (capitalization-weighted) index. Similar to Atlas Capital, MSCI enhanced value indices utilize price to earnings, enterprise value to cash flow, and price to book. Investors in the value index would have earned more than double the total return of the capitalization-weighted index in the period from December 1998 to June 2021. However, this benefit combines solid relative returns for Value stocks through 2010 and steady underperformance by Value stocks since then.

Momentum

In 1997, Mark Carhart expanded on the Fama-French three-factor model by adding momentum as a fourth factor. Stock momentum is the empirically observed phenomenon that a stock that has performed well recently will tend to continue to perform well, and a stock that has performed poorly will tend to continue to perform poorly. As an observation from behavioral finance, people tend to become increasingly optimistic about stocks that have consistently appreciated. Similarly, a stock that continues to plummet tends to cause investors to become more averse to it, resulting in a self-reinforcing downward spiral. Momentum signals are transient – outperformance eventually turns to underperformance. But momentum is still a valuable indicator, especially when used in conjunction with other factors such as Value.

Short-Term Reversal

The empirical evidence for short-term reversal in the stock market has been established for more than thirty years in academic studies by Fama, French, Jegadeesh, and others. The behavioral explanation is that investors can initially overreact to bad or good information. A portion of the overreaction is reversed shortly after that as the information is evaluated with more composure. There is also a supply/demand explanation, whereby sudden large movements in a stock price attract value-oriented investors who buy the stock which has plunged or sell the stock which has soared.

The concept of the short-term reversal seems at first to be contrary to that of momentum. However, the period of time considered is the key difference. Stock price momentum is a persistent signal over six months to a year. For example, screening for momentum on December 31st, you might rank the total return over the period from January 1st of that same year up until the end of October or November (most recent twelve months minus the most recent one or two months). The most recent month (at a minimum) is excluded because price action during this period is not a good signal to use for momentum of single stocks, on average. In fact, analyzing recent period price action tends to give the opposite signal, hence the concept of the short-term reversal.

While this approach has been profitable over the long term, it is also quite volatile and has the least weight among the factors utilized in the Atlas Capital investment decision process.   Note: Short Term Reversal is defined as the NEGATIVE of the most recent one-month return.

Long-Term Reversal

Long-Term Reversal is an equity factor which is based on prior performance, like Momentum and Short-Term Reversal.  For this factor, stocks are ranked based upon their performance from five years ago to one year ago.  The stocks which have the lowest performance over that period are the ones which are favored for investment.  Choices made using the Long-Term Reversal factor often overlap with choices made using Value-related factors such as Cash Flow to Price.  Stocks which have had a long period of poor performance can become attractive Value stocks.

The behavioral explanation is that a stock whose performance has been lagging for a number of years can be seen as a relative “bargain” to investors, especially if the relationship of the price to earnings or cash flow has become favorable.  The concept of the long-term reversal (choosing stocks which have done badly from five years ago to one year ago) seems contrary to momentum (choosing stocks which have done well within the past year). However, the period of time considered is the key difference. 

Size

Size is one of the original equity factors identified more than thirty years ago in academic studies by Fama and French. Their research conclussion was that stocks with smaller market capitalization have tended to have higher future performance than larger stocks.

As companies grow in market value it becomes harder to continue to grow at the same pace.  The history of the stock market shows regular turnover among the top companies by market capitilization.  Smaller companies can be better positioned to achieve high earnings growth.  Moreover, smaller companies are inherently riskier, with that risk reflected in market prices.  This, in turn, can lead investors to be compensated for the higher risk by obtaining higher returns.

The graph below provides the annual return of the size factor in US stocks, as indicated by the Fama/French website maintained by Dartmouth professor Kenneth French. The chart indicates the results of a strategy with monthly trading whereby the 20% of stocks with the smallest size are purchased.

Multi-Factor

A cardinal rule of investing is that diversified portfolios offer a better relationship of expected return to risk than concentrated portfolios.  This is especially true if the diversified portfolio contains differentiated investments with a low correlation to each other.  The Momentum factor tends to have a negative correlation with the Value factors, and thus combining Momentum with Value is beneficial to the investment result.

The graphs below show the annual results of a combination of the factor portfolios described here.  This combination portfolio has a better relationship of historical return to risk (the uncertainty in that return) than any of the factors individually.