Weekly Recap
Research on quant investing and trading.
Welcome to this week’s collection of links to the latest research and insights on quant investing. Below, you’ll find a curated list where each title links to the source for more information. Thank you for reading!
Climate/ESG
Unpacking the ESG Ratings: Does One Size Fit All? (Billio et al.)
The paper analyzes discrepancies in ESG ratings from different agencies, highlighting inconsistent methodologies and their implications for sustainability assessments.
Crypto
Revisiting the Determinants of Cryptocurrency Excess Return: Does Scarcity Matter? (Bui et al.)
This paper studies the cross-section of cryptocurrency returns and introduces a measure of scarcity, found to be a significant driver of cryptocurrency returns.
Volume Versus Returns: Reevaluating the Predictive Power of Salience Theory in the Cryptocurrency Market (Ding et al.)
While previous research has documented that stocks with high salience underperform stocks with low salience, this paper finds an even more pronounced salience effect in crypto markets.
Empirical Asset Pricing
Empirical Asset Pricing with Probability Forecasts (He et al.)
The study shows that combining probability forecasts with return forecasts significantly improves portfolio performance compared to using either forecast alone.
Predicting Winner and Loser Stocks: A Classification Approach (Rihtamo et al.)
Using a binary classification model that predicts future winning and losing stocks is shown to improve signal-to-noise ratios, yielding significant returns out-of-sample.
Which stock return predictors reflect mispricing? (Frey)
The paper examines stock return predictors, distinguishing between those reflecting mispricing due to biased expectations and those related to risk.
Machine learning and natural language processing
Approaching Human-Level Forecasting with Language Models (Halawi et al.)
The paper explores using language models to predict future events, achieving near-human forecasting accuracy by integrating information retrieval and reasoning processes.
Macro
Monetary Policy Shocks: Data or Methods? (Brennan et al.)
The paper examines how different data and methods affect the estimation of monetary policy shocks, finding that discrepancies are most pronounced when the federal funds rate is at its lower bound.
Market microstructure
Limit Order Book Simulations: A Review (Jain et al.)
This review paper provides stylized facts and statistical properties of limit order books, a thorough review of various simulation and modelling techniques, and an extensive reference list for further reading.
Volatility
Volatility Managed Multi-Factor Portfolios (Reschenhofer and Zechner)
This paper finds gains in performance by combining information from historical vol and implied vol when scaling equity portfolios, particularly during high-vol periods.
Harvesting the HAR-X Volatility Model (Clements et al.)
A Heterogeneous AutoRegressive model with low-frequency data in the form of daily data, and augmented with exogenous variables, is found to deliver a similar forecasting performance as the original HAR model.
Book Recommendations
Three quant books recommended (Christina Qi)
Trading systems and methods by Perry J. Kaufman
Lecture Notes
Advanced Time Series and Forecasting by Prof. Bruce E. Hansen
Lecture Notes on International Finance (Jiang)
Lecture notes prepared by Prof. Jiang at the Kellogg School of Management covering a broad range of topics such as currencies, government debt, capital flows, and much more.
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