Momentum Investing

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

Can investors achieve attractive asset class momentum strategy performance by applying slow relative momentum to different risk-on (offensive) and risk-off (defensive) sets of exchange-traded funds (ETF), and fast absolute momentum to a separate risk mode identification set of ETFs? In his July 2022 paper entitled “Relative and Absolute Momentum in Times of Rising/Low Yields: Bold Asset Allocation (BAA)”, Wouter Keller presents an aggressive asset allocation strategy that combines features of his previous models (Protective Asset Allocation, Vigilant Asset Allocation and Defensive Asset Allocation). This Bold Asset Allocation strategy consists of the following baseline asset universes and rules:

1. When none (any) of SPY, VWO, VEA and BND have negative weighted returns over the past 1, 3, 6 and 12 months, use the offensive (defensive) mode. Weights for past 1, 3, 6 and 12 months returns are 12, 4, 2 and 1, respectively.
2. When in offensive mode, hold the equal-weighted six of SPY, QQQ, IWM, VGK, EWJ, VWO, VNQ, DBC, GLD, TLT, HYG and LQD with the highest ratios of current monthly price to average of the last 13 prices (including current price).
3. When in defensive mode, hold the equal-weighted three of TIP, DBC, BIL, IEF, TLT, LQD and BND with the highest ratios of current monthly price to average of the last 13 prices (including current price), except replace with BIL any of these top three with past price ratio less than that of BIL.

He reforms the BAA portfolio monthly, assuming constant 0.1% 1-way trading frictions. Using modeled monthly total returns prior to ETF inception and actual monthly total returns after inception for each specified ETF during December 1970 through Jun 2022, he finds that:

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Do individual investors who chase stocks with high recent returns benefit from momentum or suffer from reversal? In their June 2022 paper entitled “Who Chases Returns? Evidence from the Chinese Stock Market”, Weihua Chen, Shushu Liang and Donghui Shi investigate the characteristics, performance and market impact of retail stock investors who exhibit return-chasing behavior. Each month, they measure:

1. Each retail investor’s return chasing propensity (RCP) as the average of returns during the 12 months prior to purchase across the stocks in the investor’s portfolio. For robustness they also consider past return intervals of one, two, three and six months.
2. Each stock’s return chasing ownership (RCO) by wealth-weighting the RCPs of its retail holders (excluding this stock from holder RCP calculations).

Using monthly stock holdings, trading records and investor demographics, plus associated monthly stock prices, for 18 million Shanghai Stock Exchange retail investors during January 2011 through December 2019, they find that:

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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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What determines whether a stock will exhibit short-term momentum or short-term reversal? In their May 2022 paper entitled “Short-term Relative-Strength Strategies, Turnover, and the Connection between Winner Returns and the 52-week High”, building upon prior research, Chen Chen, Chris Stivers and Licheng Sun investigate interactions among proximity to 52-week high, share turnover and 1-month return momentum/reversal behaviors for U.S. stocks.  Specifically, at the end of each month t, they form 125 portfolios by:

1. Sorting stocks into fifths (quintiles) based on return during month t.
2. Further sorting these quintiles stocks into sub-quintiles based on ratio of price at the end of month t-1 to highest price over the preceding 52 weeks.
3. Further sorting the sub-quintiles into sub-sub-quintiles based on share turnover during month t.

They then use month t+1 value-weighted returns of the resulting 125 portfolios to evaluate short-term momentum/reversal strategies in multiple ways: buying winners and shorting losers (momentum); buying losers and shorting winners (reversal); and, winners-only or losers-only strategies based on 52-week high proximity. Using the specified trading data for a broad sample of U.S. common stocks priced at least $1 during July 1963 to December 2020, they find that:

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A subscriber suggested review of a Follow the Leader (FTL) strategy that, in simplest form, each month holds iShares MSCI Emerging Markets ETF (EEM) when prior-month SPDR S&P 500 ETF Trust (SPY) return is positive and iShares 20+ Year Treasury Bond ETF (TLT) when prior-month SPY return is negative. To investigate, we run this simplest FTL strategy over the available history of EEM. We use buy-and-hold SPY as a benchmark. Using monthly dividend-adjusted returns for SPY since March 2003 and for EEM and TLT since April 2003, all through April 2022, we find that: Keep Reading

Do intraday (open-to-close, trading-driven/technical) and overnight (close-to-open, news-driven) stock returns play different roles in signaling short-term reversal, intermediate-term momentum and long-term reversion? In their March 2022 paper entitled “What Drives Momentum and Reversal? Evidence from Day and Night Signals”, Yashar Barardehi, Vincent Bogousslavsky and Dmitriy Muravyev investigate by relating past cumulative daily, intraday and dividend-adjusted overnight returns over various lookback intervals to future returns. The lookback intervals they consider are:

• For reversal: last month.
• For momentum: from seven or 12 months ago to one month ago.
• For reversion: from 36, 48 or 60 months ago to 12 months ago.

They measure reversal, momentum and reversion effects via monthly gross 3-factor (market, size, book-to-market) alphas of hedge portfolios that are each month long (short) the extreme tenth, or decile, of stocks with the highest (lowest) past returns. Using the specified inputs for a narrow sample of U.S. common stocks during January 1926 through December 1962, and for a broad sample of U.S. common stocks during January 1963 through December 2019, they find that: Keep Reading

A subscriber proposed substituting SPDR S&P Global Natural Resources ETF (GNR) for Invesco DB Commodity Index Tracking Fund (DBC) as a proxy for commodities in the Simple Asset Class ETF Momentum Strategy (SACEMS). GNR holds stocks of relatively large firms engaged in natural resources and commodities businesses. DBC holds a range of commodity futures contracts. To investigate, we run SACEMS since June 2006 but substitute GNR for DBC as soon as GNR becomes available in September 2010 (dovetailing with older data). Using dividend-adjusted closing prices for SACEMS asset class proxies and GNR and the yield for Cash during February 2006 (per tracked SACEMS) through April 2022, we find that: Keep Reading

Can investors improve the performance of stock momentum portfolios by isolating stocks that “hold” their momentum? In their April 2022 paper entitled “Enduring Momentum”, Hui Zeng, Ben Marshall, Nhut Nguyen and Nuttawat Visaltanachoti exploit firm characteristics to identify stocks that continue to be winners or losers after selection as momentum stocks (stocks with enduring momentum). They measure momentum by each month ranking stocks into equal-weighted tenths, or deciles, based on past 6-month returns, with the top (bottom) decile designated winners (losers). They then develop a model that uses information from 37 firm characteristics to estimate each month the probability that each winner or loser stock will continue as a winner or loser during each of the next six months. They verify that the model reasonably predicts momentum persistence and proceed to test the economic value of the predictions by each month reforming an enduring momentum hedge portfolio that is long (short) the 10 equal-weighted winner (loser) stocks with the highest probabilities of remaining winners (losers) and holding the portfolio for six months. They compare the performance of this portfolio to that of a conventional momentum portfolio that is each month long the entire winner decile and short the entire loser decile, also held for six months. Using returns for a broad sample of U.S. common stocks priced over $1.00 and 37 associated firm characteristics during January 1980 through December 2018, they find that: Keep Reading

Do U.S. stock momentum exchange-traded funds (ETF) deliver attractive performance? In their February 2022 paper entitled “A Look Under the Hood of Momentum Funds”, Ayelen Banegas and Carlo Rosa examine the performance of U.S. stock momentum funds. To measure performance uncontaminated by discretionary stock picking and portfolio construction methods, they focus on mechanical (passive) momentum ETFs. They segment selected ETFs into large-cap and small-cap groups to avoid any confounding size effect. Using monthly net returns and assets under management (AUM) for live and dead U.S. equity momentum ETFs with AUM greater than $50 million during January 2006 through October 2021, they find that: Keep Reading