Weekly Recap
Recent 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!
Bonds
Buy the Rumor, Sell the News': Liquidity Provision by Bond Funds Following Corporate News Events (Huang et al.)
Bond funds are documented to trade against corporate news, profiting from liquidity provision and the subsequent reversal in corporate bond prices.
Climate
Course 2023-2024 in Sustainable Finance & Climate Change (Roncalli)
Extensive lecture notes on sustainable finance covering a vast range of topics such as ESG rating systems, impact investing, ESG implications for portfolio construction, climate risk measures, and much more.
Currencies
Conditional Tests for the Profitability of Technical Analysis in Currency Trading and its Economic Fundamentals (Filippou et al.)
The paper presents a multiple-testing framework for predictive signals, controlling for data snooping issues and applied to more than 20000 FX trading rules.
Empirical Asset Pricing
Economic Trend (Brooks et al.)
Trends in macroeconomic variables predict returns across asset classes and economic trend strategies are found to diversify traditional asset classes.
No Sparsity in Asset Pricing: Evidence from a Generic Statistical Test (He et al.)
Dense models are found to be better at pricing portfolios than sparse portfolios, and delivers significantly higher Sharpe ratios.
Safe Equities: An Alternative Allocation to Bonds (Penman)
The author proposes to replace bonds in the traditional 60/40 portfolio with “safe” equities, hedging equity drawdowns and improving diversification.
Machine Learning and Natural Language Processing
Causal ML Book (Chernozhukov et al.)
A new book on applied causal inference with machine learning.
ChatGPT and Corporate Policies (Jha et al.)
The authors constructs an improved measure of expected future investments by applying ChatGPT, finding it to be a significant negative predictor of future returns.
Deep Hedging with Market Impact (Neagu et al.)
The paper considers the application of Deep Reinforcement Learning to dynamic option hedging, integrating market impact and information on the limit order book.
Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities (Tang et al.)
This paper evaluates the ability of large language models for time-series prediction, which perform best with series exhibiting strong trends or seasonal patterns.
Forecasting Wheat Futures with Convolutional Neural Networks (Chan et al.)
The authors train a convolutional neural network using satellite images of wheat crops and weather conditions, finding that it predict returns well up to 2018.
Textual Changes in 10-Ks and Stock Price Crash Risk: Evidence from Neural Network Embeddings (Yilmaz and Reichmann)
Large textual changes in firms’ 10-K filings are found to be associated with an increased risk of future stock price crashes.
Macro
The Long-term Effects of Inflation on Inflation Expectations (Braggion et al.)
The paper examines how historical inflation experiences, particularly from the 1920s, continue to influence current inflation expectations across generations.
Measuring Macroeconomic Tail Risk (Marfe and Penasse)
The authors estimate time-varying probabilities of macro risks across countries, which are found to predict economic crises and stock returns out-of-sample.
Portfolio Construction
Mean-Variance Optimization of Factors and the Cross-Section of Stock Returns (Lalwani)
The authors construct a Sharpe maximizing equity portfolio using 32 base assets, delivering a higher Sharpe ratio than benchmark portfolios.
Data and Code
FNSPID: A Comprehensive Financial News Dataset in Time Series (Dong et al.)
Github: Financial News Dataset in Time Series
"FNSPID is a comprehensive financial dataset. It contains 29.7 million stock prices and 15.7 million financial news records for 4,775 S&P500 companies from 1999 to 2023, gathered from four stock market news websites."
Quant Blogs
Building Intuition for Trading with Convex Optimisation with CVXR (Robot Wealth)
Regression-based macro trading signals (Macrosynergy)
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