Size Effect

Why do equal-weighted (EW) portfolios outperform their market capitalization-weighted, or value-weighted (VW), counterparts over multiple decades in various investment universes? In their November 2022 paper entitled “Why Do Equally Weighted Portfolios Beat Value-Weighted Ones?”, Alexander Swade, Sandra Nolte, Mark Shackleton and Harald Lohre analyze drivers of differences in performance between EW and VW U.S. stock portfolios over six decades. They also assess consistency of performance drivers. Using monthly returns for a very broad sample of U.S. common stocks and monthly stock factor returns during July 1963 through December 2021, they find that:

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A subscriber, referring to a March 2016 commentary stating that “microcap stocks offer investors one of the best opportunities for consistent, long-term excess returns,” inquired about the performance of quality-value-momentum microcap strategy described therein. To assessment this strategy, we compare the self-reported annual performance of the O’Shaughnessy Micro Cap strategy (OSMC) as of June 2022 (now maintained by Franklin Templeton) to that of simply buying and holding SPDR S&P 500 ETF Trust (SPY). Using annual self-reported OSMC net returns and matched dividend-adjusted SPY returns during August 2007 through June 2022, we find that: Keep Reading

Multifactor funds offer rules-based, diversified exposures to firm/stock factors found to beat the market in academic studies. Do the funds beat the market in real life? In his June 2022 paper entitled “Multifactor Funds: An Early (Bearish) Assessment”, Javier Estrada assesses performance of such funds across U.S., global and emerging markets relative to that of corresponding broad capitalization-weighted indexes and associated exchange-traded funds (ETF). He focuses on multifactor funds with exposure to at least three factors that are explicitly marketed as multifactor funds. Using monthly total returns for 56 U.S.-based equity multifactor funds with at least three years of data and $10 million in assets from respective inceptions (earliest June 2014) through March 2022, and total returns for matched broad market indexes and ETFs, he finds that:

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Does the finding from long-short factor analysis that the value premium is stronger among small stocks than large stocks hold for long-only value portfolios? In his April 2022 paper entitled “Long-Only Value Investing: Does Size Matter?”, Jack Vogel investigates interactions between the value premium and market capitalization for U.S. and international stocks. The steps in his main analysis are to each year on June 30:

• Group the 3,000 largest U.S. stocks by market capitalization with non-zero market value of equity into the 1,000 largest firms (large-cap) and the 2,000 smallest (small-cap).
• Rank each group into thirds (terciles), fifths (quintiles) or tenths (deciles) based on each of: (1) book-to-market ratio (B/M); (2) earnings-to-price ratio (E/P); (3) free cash flow-to-price ratio (FCF/P); (4) earnings before interest and taxes-to-total enterprise value ratio (EBIT/TEV); and, (5) the composite rank of these four ratios.
• Measure average monthly returns over the next year of the top ranks based on either equal weights (EW) or value weights (VW).

Using the specified accounting data and stock prices for a broad sample of U.S. firms since July 1973 and for a comparable sample of international developed market firms since January 1994, all through December 2020, he finds that: Keep Reading

Do popular capitalization-based exchange-traded funds (ETF) offer a reliable way to exploit an equity size effect? To investigate, we look at the difference in returns (small minus big) between:

• iShares Russell 2000 Index (Smallcap) Index (IWM), and
• SPDR S&P 500 (SPY)

Using monthly dividend-adjusted closing prices for these ETFs during May 2000 (limited by IWM) through March 2022, we find that: Keep Reading

Do widely accepted equity factor premiums exist in data older than generally employed in academic studies? In their November 2021 paper entitled “The Cross-Section of Stock Returns before 1926 (And Beyond)”, Guido Baltussen, Bart van Vliet and Pim van Vliet look for some of the most widely accepted factor premiums in a newly assembled sample of U.S. stocks spanning January 1866 through December 1926 (61 years of additional and independent data). Specifically, they look at: size as measured by market capitalization; value as measured by dividend yield (strongly associated with earnings during the sample period); stock price momentum from 12 months ago to one month ago; short-term (1-month) return reversal; and, risk as measured by market beta. They use only those stocks which trade frequently and apply liquidity/data quality filters. To measure factor premiums, they each month for each factor:

• Regress next-month stock return versus stock factor value and compute slopes of the relationship.
• Reform a value-weighted hedge portfolio that is long (short) stocks with high (low) expected returns based on factor values to measure: (1) average factor portfolio gross return; and, (2) gross factor (CAPM) alphas and betas based on regression of factor portfolio excess return versus market excess return.

They further investigate economic explanations of factor premiums and test machine learning methods found successful with recent data. Using monthly prices, dividends and market capitalizations for 1,488 stocks in the new database, they find that:

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Trading Calendar presents full-year and monthly cumulative performance profiles for the overall stock market (S&P 500 Index) based on its average daily behavior. How much do the corresponding monthly behaviors of the various size and value/growth styles deviate from an overall equity market profile? To investigate, we consider the the following six exchange-traded funds (ETF) that cut across capitalization (large, medium and small) and value versus growth:

iShares Russell 1000 Value Index (IWD) – large capitalization value stocks.
iShares Russell 1000 Growth Index (IWF) – large capitalization growth stocks.
iShares Russell Midcap Value Index (IWS) – mid-capitalization value stocks.
iShares Russell Midcap Growth Index (IWP) – mid-capitalization growth stocks.
iShares Russell 2000 Value Index (IWN) – small capitalization value stocks.
iShares Russell 2000 Growth Index (IWO) – small capitalization growth stocks.

Using monthly dividend-adjusted closing prices for the style ETFs and SPDR S&P 500 (SPY) during August 2001 through October 2021 (limited by data for IWS/IWP), we find that: Keep Reading

Does the Fama-French  5-factor model (market, size, book-to-market, profitability, investment) of stock returns work for stocks worldwide? In their May 2021 paper entitled “Size, Value, Profitability, and Investment Effects in International Stock Returns: Are They Really There?”, Nusret Cakici and Adam Zaremba test the performance of the 5-factor model in global developed markets. They consider big and small stocks separately. They consider four regions (North America, Europe, Japan and Asia-Pacific), as well as the global market. They lag all accounting data by six months and calculate returns in U.S. dollars. Using data in U.S. dollars for 65,000 stocks from 23 countries during December 1987 through March 2019 (with tests starting July 1990), they find that:

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How have value, quality, low-volatility and momentum equity factors, and combinations of these factors, performed in recent years. In their October 2020 paper entitled “Equity Factor Investing: Historical Perspective of Recent Performance”, Benoit Bellone, Thomas Heckel, François Soupé and Raul Leote de Carvalho review and put into context recent performances of these these factors/combinations as applied to medium-capitalization and large-capitalization World, U.S. and European stock universes. They consider both long-short and long-only factor portfolios and further investigate effects of (1) neutralizing beta and sector dependencies, (2) using multiple metrics for each factor and (3) including small stocks. Using firm accounting data and stock returns to support factor portfolio construction during 1995 through early 2020, they find that:

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The conventional size (market capitalization) premium is notoriously weak since discovery almost 40 years ago. Does this poor live track record mean it is useless to investors? In their September 2020 paper entitled “Settling the Size Matter”, David Blitz and Matthias Hanauer examine whether the size premium is exploitable as a standalone anomaly or in combination with other anomalies. They consider six versions of a size factor from prior research, as follows:

1. Adjusted for value – average of three small-cap stock portfolios minus average of three big-cap stock portfolios after sorting for book-to-market ratio.
2. Adjusted for value, investment and profitability – average of nine small-cap stock portfolios minus average of nine big-cap stock portfolios after separately sorting on the other three factors.
3. Adjusted for profitability – average of three small-cap stock portfolios minus average of three big-cap stock portfolios after sorting for profitability.
4. Adjusted for quality – average of three small-cap stock portfolios minus average of three big-cap stock portfolios after sorting for quality.
5. Adjusted for quality beta – average of three small-cap stock portfolios minus average of three big-cap stock portfolios after sorting for quality beta.
6. Adjusted for size, investment and return on equity – average of nine small-cap stock portfolios minus average of nine big-cap stock portfolios after separately sorting on the other three factors.

All factor portfolio segments are capitalization-weighted, and all returns are in U.S. dollars. They consider regressions (implying long-short implementations) and long-only sides of these factors. They also consider size factor definitions that do not overweight size inputs, as do those above. Using data required by these definitions for U.S. stocks since July 1963 (or January 1967 for some inputs) and for international stocks since July 1990 (or July 1993 for some inputs), all through December 2019, they find that: Keep Reading