Each week, I highlight interesting investment research from academic papers, industry reports, and financial blogs. Links to the original sources are included for those who want to learn more.
Equities
Pre-announcement drift around Bank of Canada meetings (Amedee-Manesme, Fu, and Mengaptche-Toukap)
Does the pre-FOMC announcement drift also exist in Canada? Studying 201 Bank of Canada meetings, Canadian equities earn approximately 14 bps higher excess returns three trading days before policy announcements, rising to 18 bps since 2013. Unlike the familiar pre-FOMC pattern, the Canadian effect emerges earlier. A reminder that the timing of calendar anomalies can vary considerably across markets.
Cost-Aware Generative Portfolios (Cong, He, He, and Ye)
What happens when machine learning accounts for transaction costs when constructing portfolios? Using data on US equities (1984–2023), the authors find that monthly turnover falls from 86% to 53%, while the net Sharpe ratio rises from 0.17 to 0.98. About 92% of the Sharpe improvement comes from how stocks are grouped into portfolios, rather than how capital is allocated across them. The model also favors slower-moving fundamental signals over momentum and short-term reversal.
The Logic of Factor Portfolios: Boolean Rules, Interactions, and Trading Costs (Wang, Rachev, and Fabozzi)
Does combining more signals improve factor strategies? This paper studies US equities and finds that higher-order signal interactions tend to generate smaller return premia and higher trading costs. Yet they can still improve portfolio performance. Adding two-signal interactions raises the out-of-sample Sharpe ratio from 0.11 to 0.32 after costs, while including three-signal interactions increases it further to 0.45.
The End-of-Day Reversal After 2019: A Pre-Registered Test on S&P 500 Stocks Excluding Heavily Traded Names (Vidovich and Zerjal)
Previous research has found that stocks that fall early in the day tend to outperform during the final 30 minutes of trading. Does this end-of-day reversal still exist? The authors find a reversal averaging 3.05 bps per day in 2023–2026, almost unchanged from 2016–2019. But there’s a catch: Among the 80 most heavily traded S&P 500 stocks, the effect has largely disappeared.
This paper applies portfolio diversification principles to machine learning, combining linear models, neural networks, and decision trees trained on different samples and factor subsets. Testing on CSI 300 stocks (2017–2020), the ensemble achieves a backtested Sharpe ratio of 1.85 versus 1.76 for XGBoost.
FX
Economic Fundamentals and Short-Run Exchange Rate Prediction: A Machine-Learning Perspective (Filippou, Rapach, Taylor, and Zhou)
Can economic fundamentals predict short-term currency movements after all? Using machine learning across 10 developed currencies (1995–2020), the authors achieve an out-of-sample R² of 1.86%, outperforming the random-walk benchmark. Interest rate and inflation differentials become more useful predictors when FX volatility rises. The information in traditional macroeconomic indicators appears to depend heavily on market conditions.
Portfolio Allocation
Dynamic Strategy Selection (Cordoni, Sancetta, and Zhao)
This paper uses reinforcement learning to rotate monthly among momentum, value, profitability, and defensive equity factors from 1973 to 2025. The strategy achieves an out-of-sample Sharpe ratio of 0.715, versus 0.511 for a myopic rotation strategy and 0.445 for buy-and-hold momentum. Interestingly, adding macroeconomic predictors worsens performance. More information doesn’t necessarily mean better investment decisions.
Blogs
The Midterm Rally: What Happened in 2026, and What Comes Next? (Quantseeker)
The Part Time Trader · Part 6: Where Momentum Lives (The Algorithmic Advantage)
Correlation Acceleration: Detecting Market Stress Through Rising ETF Correlations (Quantpedia)
Sizing Bitcoin: A First-Principles Approach for a Risk-Parity Portfolio (Beyond Passive Investing)
Are Value and Momentum Still Everywhere? (Alpha Architect)
Why optimising for the left tail of outcomes is like playing chess... (Rob Carver)
Podcasts
Welcome to Gas Vegas: Commodities Trading From First Principles With Ex-Goldman Commodities Trader (Odds on Open)
How Ben Felix & Dan Bortolotti Invest Their Own Money (Rational Reminder)
Social Media & Industry Research
Houston, Do We Have A Problem? (Citadel)
Earnings-Day Volatility Is a Feature, Not a Bug (Acadian Asset Management)
Reads You May Have Missed (Man Group)
Trend Following: More than a Crisis Strategy (AQR)
Last Week’s Most Popular Links
The Hidden Sharpe Ratio (Chernov, Kelly, Malamud, and Schwab)
Outperforming the S&P500 with macro factors (Macrosynergy)
Synthesizing Information-Driven Insider Trade Signals (Heckmann, Jacobs, and Schwarz)
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