Every week, I share a selection of the most interesting investment research from the past seven days, spanning academic studies, practitioner research, and investment blogs. Each summary includes a link to the original source for readers who want to explore the research in more detail.
Asset Allocation
Adaptive Multi-Asset Allocation Conditioned on Geopolitical Risk Signals (Karadeniz)
Adding geopolitical risk to a regime-switching multi-asset model raises the out-of-sample Sharpe from 0.49 to 0.56, but the improvement is not statistically significant. Across seven robustness tests, none show a significant benefit from GPR. Key takeaway: Geopolitical risk can affect asset prices, but it seems less straightforward to use as a useful signal for portfolio allocation.
Crypto
Mispricing and Risk Compensation in Cryptocurrency Returns (Babiak and Bianchi)
Crypto returns reflect both risk compensation and systematic mispricing. Using 600+ cryptocurrencies, the authors find that speculative demand and liquidity drive daily mispricing, while reversal becomes especially important at the weekly horizon. Key takeaway: Lottery-like demand, liquidity, and reversal signals contain information about future crypto returns beyond conventional risk factors.
Fundamentals in Cryptocurrency Valuation: Evidence from DeFi Markets (Harre, Merkley, Miller, and Williams)
Crypto isn’t necessarily all speculation and momentum. Across 95 revenue-generating DeFi protocols, larger positive revenue surprises are associated with higher subsequent token returns: A 1-standard deviation surprise is associated with +29 bps abnormal returns over the next three days. Key takeaway: For some crypto assets, fundamentals do matter.
Predictability on the Move: The Cryptocurrency Cross-Section (Pang and Wang)
Crypto alpha is a moving target. Testing 1,043 signals across a point-in-time Binance universe, this paper finds that established size, momentum, and trend premia are weaker in their sample. At the same time, the strongest predictors vary substantially over time. In later periods, short-horizon liquidity and trading-activity signals dominate. Key takeaway: Crypto predictability migrates across signals rather than consistently coming from the same set of factors.
Equities
Is the Value Premium Dead? Forecasting Value–Growth Cycles with the Implied Value Premium (Li, Ng, and Swaminathan)
The value premium is cyclical and partly predictable. The authors construct an “implied value premium” from the difference in implied costs of capital between value and growth stocks. A 1-standard deviation increase predicts roughly 5–6% higher value-minus-growth returns over the next year, and the signal also works out of sample. Key takeaway: The implied value premium seems more useful for timing value vs. growth than traditional valuation spreads.
Expected vs. Unexpected Extremes: The Origins of the MAX Anomaly (Haghighi Zadeh, Kahibavil, and Safari)
Not all extreme stock returns are created equal. The well-known MAX anomaly, where stocks with extreme positive daily returns subsequently underperform, appears to be driven primarily by unexpected extremes, not predictable tail risk. Stocks with surprisingly large MAX realizations earn significantly lower subsequent returns. Key takeaway: It’s the unexpected component of extreme returns that matters most.
Explaining Realized Returns: Roll’s R2 40 Years Later (Kelly, Su, and Zhang)
Even after the fact, explaining why the stock market moved is surprisingly difficult. Conventional macro, cash-flow, expectations, and flow data explain little of monthly U.S. equity returns. But newspaper-stated reasons extracted from financial news explain roughly 30–40% of daily and monthly returns out of sample. Key takeaway: Market narratives contain useful information that traditional structured data miss.
The Evolution of Quantitative Equity Investing: Half a Century of Alpha Research and Institutional Adaptation (Feng, Cardozo, and Xia)
This comprehensive survey paper traces 50 years of quantitative equity investing, from portfolio theory and factor investing to alternative data, machine learning, and AI. Key takeaway: Finding a return predictor is only the first step. Alpha must survive out-of-sample testing, trading costs, capacity, crowding, and regime change to become a viable investment strategy.
Profit Growth and Expected Stock Returns (Ahn, Black, Huang, Lord, Rizova, and Saito)
Profit growth contains information about future stock returns beyond profitability and momentum. This paper finds that firms with stronger profit growth subsequently earn higher returns, with particularly strong results among small caps. Key takeaway: Profit growth and price momentum capture complementary information about expected returns, and combining the two strengthens the signal.
Fixed Income
Cross-Sectional Corporate Bond Returns (Feng, Liu, and Zheng)
Using large jumps in Fed-funds-futures-implied rates, the authors construct a characteristics-based measure of corporate bonds’ systematic-risk exposure. Out of sample, high-minus-low bonds earn 9.1% annually, with a 1.28 Sharpe (before costs). Key takeaway: Corporate bonds’ exposure to systematic risk contains substantial information about future returns.
Blogs
Can Bond Volatility Improve a 60/40 Portfolio? (Quantseeker)
What Really Drives the Asset Growth Anomaly? New Evidence Points to Mispricing, Not Risk (Alpha Architect)
Practical transaction cost checks for macro trading strategies (Macrosynergy)
Le Boomer Spread: Why France now pays more than Italy to borrow. (Hanno Lustig)
Podcasts
"AI Won't Give You Edge" - Alpaca CEO Yoshi Yokokawa (Odds on Open)
The Game Was Rigged in Their Favor. 28% Went Bust Anyway. Kris Abdelmessih on How to Size Bets (Excess Returns)
US Trading Champion: He Made 520% Competing Against The World’s BEST Traders - Here’s how! (Words of Rizdom)
Social Media & Industry Research
Dont’ Write Off Bonds Yet (Man Group)
Taking an Active Approach in Today’s Fixed Income Market (Man Group)
Rethinking the 60/40 Portfolio (HedgeNordic)
The quants of Babylon (Owen Lamont, Acadian Asset Management)
Last Week’s Most Popular Links
The Capacity of Equity Anomalies (Avramov, Bongaerts, Crego, and Soerlie Kvaerner)
Behavioral Finance at 40 (Nicholas Barberis)
Firm-Specific Price Delay and Momentum (Parajuli)
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