Weekly Research Recap
Latest research on investing and trading
Hi there! It’s time for a new recap of last week’s investing research, with direct links to the full articles.
Commodities
Is Gold an Inflation Hedge? (Baur)
Gold is not a consistent hedge against average inflation. Between 1971 and 2025, realized inflation explains less than 3% of gold’s price variation, and the hedge effect evident in the 1970s–80s largely disappears thereafter. Gold does, however, respond strongly to extreme inflation shocks and especially to changes in inflation expectations: 1-year and 5-year expectation shocks deliver R² up to 13%. Thus, gold is a limited hedge against realized inflation but reacts strongly to shifts in inflation expectations.
Cultural Calendars and the Gold Drift: Are Holidays Moving GLD ETF? (Vojtko and Dujava)
The paper uncovers a consistent holiday drift in gold prices, showing that the GLD ETF earns positive abnormal returns around major cultural festivals such as Christmas, Eid al-Fitr, Diwali, and Lunar New Year. A global strategy that holds GLD from two days before to two days after each holiday delivers annualized returns of 2.3% with a Sharpe ratio of 0.71 and modest drawdowns. The findings suggest cultural calendars create systematic, exploitable demand-driven anomalies in gold.
Credit
Predicting Serial Credit Rating Downgrades (Malone, Smales, and Liu)
Companies that have already been downgraded once are typically riskier than their ratings indicate. Studying nearly 29,000 U.S. firm-years, tree-based machine learning predicts further downgrades with roughly 75% accuracy. High leverage, weak interest coverage, low profitability, and volatile equity returns emerge as key predictors. Monitoring these signals enables investors to anticipate rating cuts before rating agencies move.
The Handbook of European Structured Financial Products (Cocco)
This handbook surveys the development of Europe’s securitisation market, detailing instruments from ABS to CDOs. It explains structuring mechanics, tranching, rating approaches, and related techniques, while case studies illustrate how securitisation converts illiquid risks into tradable securities.
Equities
Tracking Speculation from Expectations (Su and Wen)
This paper introduces Expected Trading Profitability (ETP), a new proxy for speculation and market overvaluation based on analysts’ growth forecasts for trading firms. High ETP signals overpriced markets and predicts lower returns, about –0.69% next month and –6.7% over the next year, with effects strongest in volatile periods. Tracking ETP may help investors anticipate market downturns.
Scaled Factor Portfolio (Jiang, Li, Ning, and Xue)
The paper presents a scaled PCA approach to factor investing, amplifying high-Sharpe signals and shrinking portfolio weights with ridge regression. Across 50 equity anomalies, the method delivers 12–19% annual alphas against major factor models and Sharpe ratios near 2.0 pre-costs, remaining above 1.0 net of costs. Sharpe-scaled PCA outperforms standard PCA, offering a robust framework for constructing high-dimensional factor portfolios.
The Determinants of the Time-Varying Equity Premium (AlSalman and Murphy)
The equity risk premium is countercyclical. From 1997 to 2021, it declines when real consumption, commodity inflation, Fed Funds rates, or term spreads rise. A 1% increase in the term spread reduces the premium by 0.57%, while a 1% rise in Fed Funds lowers it by 0.45%. Market sentiment and volatility have no independent effect, but geopolitical and policy uncertainty increase premia. That is, expected returns mainly reflect macroeconomic conditions and uncertainty, not sentiment.
The Term Structure of Return Expectations (Bastianello and Peng)
Investors’ return expectations vary by horizon. Yale ICF survey data show that short-term beliefs are extrapolative, a 1% past annual gain raises next-month forecasts, while long-term views turn contrarian after 6–12 months. Short-horizon expectations are irrational, whereas longer-horizon beliefs are more rational. Interestingly, beliefs about market mispricing drive long-term return views and institutional flows.
Beyond Volatility: Common Factors in Idiosyncratic Quantile Risks (Barunik and Nevrla)
Downside idiosyncratic tail risk is a distinct and priced source of systematic risk. By extracting common idiosyncratic quantile (CIQ) factors from stock-level residuals, the paper shows that only the lower-tail CIQ factor commands a premium: Stocks more exposed to downside shocks earn higher returns. High-minus-low portfolios deliver 6–8% annual return spreads (t-stat about 3) and are unexplained by standard factor models and other downside risk measures.
ESG
Betting Against ESG Sinners: Evidence from Short Selling Around the World (Iwata, Orpiszewski, and Thompson)
Negative ESG events trigger significant stock declines and spikes in shorting activity, with effects varying across the U.S., EU, and Japan. Backtests of ESG-triggered shorting strategies show positive alphas in 17 of 18 cases after borrowing costs, though only 4 are statistically significant. Returns depend on event type and region. Overall, the findings suggest ESG shorting can yield modest alpha, but opportunities seem selective across markets.
Machine Learning and Large Language Models
The Art of Quantum Computing for Finance: Brief Overview and Prospects (Mengara)
This review paper discusses the role of quantum computing in finance, covering option pricing, portfolio optimization, and risk modeling. It also examines quantum machine learning applications in fraud detection, credit scoring, and trading. While still experimental, the paper emphasizes that quantum computing could unlock substantial computational advantages once hardware matures.
AlphaAgents: Large Language Model based Multi-Agents for Equity Portfolio Constructions (Zhao, Lyu, Jones, Garber, Pasquali, and Mehta)
This paper introduces AlphaAgents, a multi-agent LLM framework for stock selection where fundamental, sentiment, and valuation agents collaborate. In backtests on tech stocks, the multi-agent portfolio outperforms benchmarks with higher returns and Sharpe ratios. Risk-averse agents are found to underperform in bullish markets but show smaller drawdowns.
Blogs
Systematic equity allocation across countries for dollar-based investors (Macrosynergy)
Beyond Skewness: Tail Asymmetry as a Commodity Signal (Quantseeker)
Robeco's One-Legged Vol Factor (Eric Falkenstein)
Trading Signals in High Definition (Robot Wealth)
GitHub
Podcasts
Jeff Rosenberg – The Past, Present, and Future of Systematic Fixed Income (Flirting with Models)
The One Rule That Protects My Wealth | Inside Aswath Damodaran’s Personal Portfolio (Excess Returns)
The Four Faces of Trend Following ft. Richard Brennan (Top Traders Unplugged)
Most Investors Don’t Survive | Leigh Drogen on the Real Edge in Crypto (Excess Returns)
Social Media
Mag-7 and Possible Concentration Risks (AQR)
On Stacking Managed Futures (Corey Hoffstein)
Last Week’s Most Popular Links
Trading Games: Beating Passive Strategies in the Bullish Crypto Market (Palazzi)
Unraveling Asset Pricing with AI: A Systematic Literature Review (Chen, Zhang, Xie, Zhang, and Li)
Return Stacking and Portable Alpha, an Investor's Guide (Basnicki and Pickering)
Disclaimer: This newsletter is for informational and educational purposes only and should not be construed as investment advice. The author does not endorse or recommend any specific securities or investments. While information is gathered from sources believed to be reliable, there is no guarantee of its accuracy, completeness, or correctness.
This content does not constitute personalized financial, legal, or investment advice and may not be suitable for your individual circumstances. Investing carries risks, and past performance does not guarantee future results. The author and affiliates may hold positions in securities discussed, and these holdings may change at any time without prior notification.
The author is not affiliated with, sponsored by, or endorsed by any of the companies, organizations, or entities mentioned in this newsletter. Any references to specific companies or entities are for informational purposes only.
The brief summaries and descriptions of research papers and articles provided in this newsletter should not be considered definitive or comprehensive representations of the original works. Readers are encouraged to refer to the original sources for complete and authoritative information.
This newsletter may contain links to external websites and resources. The inclusion of these links does not imply endorsement of the content, products, services, or views expressed on these third-party sites. The author is not responsible for the accuracy, legality, or content of external sites or for that of any subsequent links. Users access these links at their own risk.
The author assumes no liability for losses or damages arising from the use of this content. By accessing, reading, or using this newsletter, you acknowledge and agree to the terms outlined in this disclaimer.