Every Tuesday, I highlight the most interesting investment research and ideas from the past week, drawing on academic papers, industry research, and blogs. Links to the original sources are included throughout.
Behavioral Finance
Behavioral Finance at 40 (Nicholas Barberis)
This review of 40 years of behavioral finance highlights several useful insights for investors. For example, investors tend to underreact to near-term earnings news but overreact to long-term growth expectations. That combination can help explain both momentum and value: Near-term fundamentals are incorporated too slowly, while long-term growth stories can get priced too aggressively. Key takeaway: Markets can be slow with facts and fast with stories.
Equities
Survivorship Bias in the Cross-Section of Winner Portfolios (Jha, Jaffri, and Butt)
Survivorship bias can dramatically inflate the performance of past winners. Among the top 20 U.S. stocks ranked by trailing returns, a survivor-only backtest outperformed the full-universe portfolio by 6.2 percentage points after 1 year and 37.4 percentage points after 5 years. Key takeaway: Survivorship bias in backtests can be sizeable.
The Capacity of Equity Anomalies (Avramov, Bongaerts, Crego, and Soerlie Kvaerner)
A high-alpha strategy isn’t necessarily scalable. Across 35 equity anomalies, the highest-alpha long legs could support less than $2B, while lower-alpha profitability strategies could support $20 to 33B before trading costs erase returns. Key takeaway: A great backtest can become a much less attractive strategy once you try to deploy serious capital.
Size Anomalies in U.S. Bank Stock Returns: A Fiscal Explanation (Gandhi and Lustig)
Bigger banks have historically earned lower risk-adjusted returns. In U.S. bank stocks, a portfolio long the largest banks and short the smallest underperformed by roughly 7–8% per year, even though larger banks were more levered. The authors’ explanation: Too-big-to-fail protection lowers the tail-risk premium investors demand for owning large banks. Key takeaway: The small-minus-big risk premium is alive in bank stocks.
Firm-Specific Price Delay and Momentum (Parajuli)
Momentum is highly conditional on how efficiently stocks incorporate firm-specific information. It is strong among stocks with high price delay, but essentially absent among low-delay stocks. Price delay measures how persistently a stock’s own past returns predict future returns, controlling for market and industry effects. Takeaway: Momentum works best where information diffuses slowly.
Speculative Leverage and Factor Momentum (Sun and Xia)
Factor momentum is strongest when speculation is being fueled by leverage. Since 1997, a one-standard-deviation increase in quarterly margin-debt growth predicts 49 bps/month higher abnormal returns for short-horizon factor momentum. The effect fades as the momentum signal ages and is strongest in hard-to-arbitrage factors. Takeaway: Leverage-financed performance chasing could explain why factor momentum persists.
Risk Mitigation of Momentum Strategy Using Stop-Loss Rules (Sadaqat, Butt, Demirer)
Exit rules can radically change the performance of momentum strategies. Across five Asian markets where conventional momentum was essentially unprofitable, adding a 15% stop-loss increased average monthly returns to 2.8–5.3% and cut average momentum crashes to below 10%. Key takeaway: Momentum’s failure in some markets can partly be resurrected by properly managing downside risk.
Asymmetric Reversals (Baldi-Lanfranchi, Collin-Dufresne, and Daniel)
Short-term reversal is more nuanced than “losers rebound and winners fall.” Decomposing stock returns shows that systematic and news-driven moves tend to continue, while residual moves reverse. Negative residual shocks reverse quickly, while positive shocks unwind much more slowly. Key takeaway: Short-term reversal is mostly about idiosyncratic price moves, not systematic or news-driven returns.
Fixed Income
Credit When it’s Due: Corporate Bond Factors on a Schedule (Dickerson and Nozawa)
Corporate bond returns have a striking calendar pattern. The first 5 trading days of the month, just 24% of trading days, account for 83% of the U.S. corporate bond market’s credit premium and 51% of premia across 103 bond factors. Key takeaway: In corporate bonds, it matters considerably when you take credit risk. Much of the credit premium is concentrated in the first few trading days of the month.
Options
Taming the Option Factor Zoo: A High-Dimensional Analysis (Walter, Zimmer, and Ulrich)
Most option-implied equity factors don’t add much beyond the traditional factor zoo. Across 137 option characteristics, equity factors explain about 91% of the variation in the 20 selected option factors, while adding them does not significantly improve the maximum Sharpe ratio. Key takeaway: Most option signals overlap with what we already know from equity factors. The real added information seems to be in jumps, kurtosis, and the shape of the volatility surface.
Blogs
The Holdout That Made the Sharpe Bigger (Jonathan Kinlay)
Timing Short Volatility with VIX Curve Momentum (Quantseeker)
The NAAIM Exposure Index: Contrarian or Continuation Indicator? (Portfolio Optimizer)
Global bond markets. Marked to Market. Part I. (Hanno Lustig)
Podcasts
Retail Trader vs. Hedge Fund Manager: Where Is the Real Alpha? (Odds on Open)
50 Years of Trading Lessons in 90 Minutes | Exclusive with Market Wizard Peter Brandt (TraderLion)
Trend Following Re-education (Michael Covel)
Last Week’s Most Popular Links
Option Prices, Analyst Expectations, and Stock Returns (Martin, Rodenkirchen, Wagner, and Wang)
Label alchemy: Target engineering for improved stock selection (Coqueret and Guida)
The Common Source of Option Return Anomalies (Gerchik)
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