Weekly Recap
Latest research on investing and trading
Welcome to this week’s roundup of cutting-edge research on investing and other valuable resources to inform and inspire new ideas. I hope you all had a fantastic Christmas and a great start to the New Year! Below, you’ll find a carefully curated list of highlights, with each title linking directly to its source for further reading. Don’t forget to hit the like button if you find this recap useful.
Bonds
Factor Investing with Delays (Dickerson, Nozawa, and Robotti)
Several corporate bond factors deliver significant alphas before costs, but accounting for bid-ask spreads and delayed execution renders the strategies largely unprofitable.
Canada Eh? The Curious Case of Arbitrage Opportunities in the Canadian Bond Markets (Tian)
The author describes a potential arbitrage opportunity involving Canadian government bonds, stemming from different day count conventions for the quoted price vs. the accrued interest calculation.
Crypto
Ponzi or Pioneer? Evaluating the Viability of MicroStrategy's Bitcoin-Focused Model (Krause)
Is MicroStrategy's Bitcoin-focused corporate strategy innovative or unsustainable? This paper provides an extensive analysis of the company's shift to becoming a major Bitcoin holder, examining its financial performance, risks, and possible payoffs.
Equities
Does Trend-Following Still Work on Stocks? (Zarattini, Pagani, and Wilcox)
The paper examines a trend-following strategy for stocks, using new all-time highs as entry signals. It documents the importance of a small number of large winners in driving overall profitability.
The Directionality of Earnings Surprises (Villanueva)
Earnings surprises have some predictive power for stock price movements, with a 62% hit ratio, but negative earnings surprises have stronger predictive power than positive surprises.
The Day of the Week Effect (Vidal-Garcia and Vidal)
This paper finds evidence of statistically significant day-of-the-week effects in stock markets across 35 countries.
The Holiday Effect (Vidal-Garcia and Vidal)
The authors find evidence of holiday effects in global stock returns, with some regions experiencing higher returns on the day before and after holidays than on other days.
News Complexity and Short Sellers (Ren)
Past research has shown that highly shorted stocks underperform. This paper finds this underperformance to be larger when firm news is more complex, suggesting that short sellers have an advantage in interpreting complex information.
Equity Term Structure Expectations and the Cross-Section of Stock Returns (Gonzalez-Urteaga, Rubio, Serrano, and Vaello-Sebastia)
The authors use options data to estimate the expected market risk premium across different horizons. Shocks to the first three principal components of this term structure are priced in the cross-section of stock returns, and the first principal component shows some predictive power for index returns.
ESG
A Review on ESG Investing (Vidal-Garcia and Vidal)
This comprehensive review paper explores research on ESG investing and financial performance.
Financial Crime
Ponzi Schemes: A Review (Boyle and Peng)
This is an extensive literature review that explores the nature, impact, and modeling of Ponzi schemes.
Hedge Funds and Mutual Funds
Hidden Risk (Barth, Monin, Siriwardane, and Sunderam)
Using hedge fund managers’ perception of their fund's equity market beta from the SEC form PF, the authors document significant differences between managers’ perceptions and estimated fund betas. Accounting for this difference can improve hedge fund allocations for investors.
Machine Learning and Large Language Models
Bottom Up vs Top Down: What Does Firm 10-K Tell Us? (Ross, Horn, Pilanci, Luo, and Zhou)
Using 10-K filings and lasso regressions, this paper constructs a data-driven dictionary of words that predict stock returns. Long-short portfolios formed using this approach outperform pre-defined dictionaries and the BERT model.
Autoencoder Option Pricing Models (Freire and Vladimirov)
This study explores the performance of non-parametric affine and non-affine option pricing models using autoencoders. It finds that non-affine models outperform affine models when using a few factors, but affine models are preferable for long-term forecasting.
Developing Cryptocurrency Trading Strategy Based on Autoencoder-CNN-GANs Algorithms (Hu, Yu, Zhang, Zheng, Liu, and Zhou)
The authors set up a trading model featuring autoencoders, Convolutional Neural Networks, and GANs to predict Bitcoin returns, finding that it outperforms benchmark models and produces a meaningful Sharpe ratio.
Sentiment trading with large language models (Kirtac and Germano)
Using large language models for sentiment analysis of corporate news generates significant returns and Sharpe ratios.
Macro
Rate Cycles (Forbes, Ha, and Kose)
This paper studies the recent tightening of global interest rates and compares it to previous rate cycles, finding that the tightening of rates post COVID-19 stands out in its speed and aggressiveness.
Nowcasting made easier: a toolbox for economists (Linzenich and Meunier)
This paper introduces a comprehensive toolkit that streamlines the development and application of nowcasting models. GitHub
Portfolio Selection
A Note on Markowitz Model (Vidal-Garcia and Vidal)
Markowitz-optimized portfolios of UK equity mutual funds generate higher Sharpe ratios than market indices.
Real Estate
Housing Is the Financial Cycle: Evidence from 100 Years of Local Building Permits (Cortes and LaPoint)
Using a novel, hand-collected, dataset of monthly building permits, the authors find the volatility of permit growth rates to be a significant predictor of equity market volatility, as well as corporate bond volatility.
Institutional Investors and House Prices (Bandoni, De Nora, Giuzio, Ryan, and Storz)
The increased presence of institutional investors in housing markets may increase the sensitivity of housing to shocks and monetary policy and weaken the link between house prices and economic determinants such as household income.
Blogs
Do less liquid assets trend better or is that they are just more diversified? (Rob Carver)
Private consumption (Macrosynergy)
Crowded trades and consequences (Macrosynergy)
Macro-quantamental investment handbook (Macrosynergy)
Drawdown Implied Correlations (Part 1) (CSSA)
Anatomy of the Bank Runs in March 2023 (New York Fed)
GitHub
Medium
Top 128 Utile Python Libraries for Aspiring Data Scientists to Try (Alexzap)
Stock Market heatmap with Python (Babayan)
Top 12 Skills Data Scientists Need to Succeed in 2025 (Bodner)
Podcasts
Interview with Brett Steenbarger (Line Your Own Pockets)
The One Factor That Explains the Struggles of Value, International and Small-Cap Stocks (Excess Returns)
CTAs: Innovation Meets Legacy & the BlackRock Effect ft. Andrew Beer & Tom Wrobel (Top Traders Unplugged)
Peter Mladina: Factor Betas and ICAPM in Practice (Rational Reminder)
Last Week’s Most Popular Links
Algorithmic Trading with Python
Fast trend following (Quantitativo)
FX trading signals: Common sense and machine learning (Macrosynergy)
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