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Value Investing Strategy (Strategy Overview)

Allocations for February 2023 (Final)

Momentum Investing Strategy (Strategy Overview)

Allocations for February 2023 (Final)
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Value Premium

Is there a reliable benefit from conventional value investing (based on the book-to-market value ratio)? these blog entries relate to the value premium.

Equity Factor Performance Before and After the End of 2000

Do the widely used U.S. stock return factors exhibit long-term trend changes and shorter-term cyclic behaviors? In his November 2022 paper entitled “Trends and Cycles of Style Factors in the 20th and 21st Centuries”, Andrew Ang applies various methods to compare trends and cycles for equity value, size, quality, momentum and low volatility factors, with focus on a breakpoint at the end of 2000. He measures size using market capitalization, value using book-to-market ratio, quality using operating profitability, momentum using return from 12 months ago to one month ago and low volatility using idiosyncratic volatility relative to the Fama-French 3-factor (market, size, book-to-market) model of stock returns. He each month for each factor sorts stocks into tenths, or deciles, and computes gross monthly factor return from a portfolio that is long (short) the average return of the two deciles with the highest (lowest) expected returns. As a benchmark, he uses the value-weighted market return in excess of the U.S. Treasury bill yield. Using market and factor return data from the Kenneth French data library during July 1963 through August 2022, he finds that:

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Are Equity Multifactor ETFs Working?

Are equity multifactor strategies, as implemented by exchange-traded funds (ETF), attractive? To investigate, we consider seven ETFs, all currently available:

We focus on monthly return statistics, along with compound annual growth rates (CAGR) and maximum drawdowns (MaxDD). Using monthly returns for the seven equity multifactor ETFs and benchmarks as available through August 2022, we find that: Keep Reading

O’Shaughnessy Micro Cap Strategy?

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

Failure of Equity Multifactor Funds?

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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Low-carbon Value Strategy?

Are there conflicts inherent in an investment strategy seeking to impose social preferences on a value style? In their May 2022 paper entitled “No Good Deed Goes Unpunished? Social vs. Investment”, Tzee-man Chow and Feifei Li investigate how a carbon reduction requirement affects construction and performance of a global developed market value stock strategy. They measure firm carbon emissions using end-of-year data from Institutional Shareholder Services (ISS), which supplements publicly available self-reported emissions with analyst reviews/estimates. They lag ISS data by three months and merge it with information for large and medium-sized stocks (top 86% of market value) in each country. Their benchmark value portfolio each year holds the market capitalization-weighted cheapest 10% of stocks based on composite valuation (average standardized book-to-price, cash flow-to-price and sales-to-price ratios and dividend yield). They then lower the carbon intensity of this portfolio via an iterative process of shifting weights from firms with relatively high carbon intensity to those with relatively low carbon intensity to achieve portfolio carbon intensities in the range 100% to 50% of that for the full universe. Using carbon emissions, valuation and price data for the specified stock universe during April 2016 through March 2021, they find that:

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Interaction of Long-only Value and Size

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

Measuring the Value Premium with Value and Growth ETFs

Do popular style-based exchange-traded funds (ETF) offer a reliable way to exploit the value premium? To investigate, we compare differences in returns (value-minus-growth, or V – G) for each of the following three matched pairs of value-growth ETFs:

  • iShares Russell 2000 (Smallcap) Growth Index (IWO)
  • iShares Russell 2000 (Smallcap) Value Index (IWN)
  • iShares Russell Midcap Growth Index (IWP)
  • iShares Russell Midcap Value Index (IWS)
  • iShares Russell 1000 (Largecap) Growth Index (IWF)
  • iShares Russell 1000 (Largecap) Value Index (IWD)

To aggregate, we define monthly value return as the equally weighted average monthly return of IWN, IWS and IWD and monthly growth return as the equally weighted average monthly return of IWO, IWP and IWF. Using monthly dividend-adjusted closing prices for these ETFs during August 2001 (limited by IWP and IWS) through March 2022, we find that: Keep Reading

Growth Versus Value and Interest Rates

In his 2007 book The Little Book That Makes You Rich: A Proven Market-Beating Formula for Growth Investing, expert Louis Navellier hypothesizes that growth (value) stocks tend to do relatively better when interest rates are rising (falling). Growth stocks benefit from the economic expansions associated with rising rates. Value stocks benefit from refinancing opportunities as interest rates fall. To test this hypothesis, we compare the performances of the following paired growth and value exchange-traded funds (ETF) and mutual funds as interest rates, proxied by the yield on the 10-year U.S. Treasury note (T-note), vary:

We consider both abstract predictive power based on correlation of changes in T-note yield with future fund returns and explicit performance of a strategy that switches between value and growth according to changes in T-note yield. Using end-of-month dividend-adjusted prices for the selected funds and contemporaneous T-note yield starting January 1983 for the mutual fund (limited by FDGRX) and May 2000 for the ETFs, all through February 2022, we find that: Keep Reading

Stock Factor Anomalies in Pre-1926 U.S. Data

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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Doing Momentum with Style (ETFs)

“Beat the Market with Hot-Anomaly Switching?” concludes that “a trader who periodically switches to the hottest known anomaly based on a rolling window of past performance may be able to beat the market. Anomalies appear to have their own kind of momentum.” Does momentum therefore work for style-based exchange-traded funds (ETF)? To investigate, we apply a simple momentum strategy to the following six ETFs that cut across market 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.

We test a simple Top 1 strategy that allocates all funds each month to the one style ETF with the highest total return over a specified momentum ranking (lookback) interval. We focus on the baseline ranking interval from the Simple Asset Class ETF Momentum Strategy (SACEMS), but test sensitivity of findings to ranking intervals ranging from one to 12 months. As benchmarks, we consider an equally weighted and monthly rebalanced combination of all six style ETFs (EW All), and buying and holding SPDR S&P 500 (SPY). As an enhancement we consider holding the Top 1 style ETF (3-month U.S. Treasury bills, T-bills) when the S&P 500 Index is above (below) its 10-month simple moving average at the end of the prior month (Top 1:SMA10), with a benchmark substituting SPY for Top 1 (SPY:SMA10). We employ the performance metrics used for SACEMS. Using monthly dividend-adjusted closing prices for the six style ETFs and SPY, monthly levels of the S&P 500 Index and monthly yields for T-bills during August 2001 (limited by IWS and IWP) through October 2021, we find that:

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