Weekly Recap
Latest 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
The Global Cross-Section of Corporate Bonds: Market, Maturity and Liquidity (Bekaert et al.)
This paper explores the ability of several pricing models to price a rich cross-section of corporate bonds, issued in six major currencies.
Crypto
Stylized facts in Web3 (Chen et al.)
This paper provides an overview of the Web3 ecosystem, comparing tokens and their return properties across centralized and decentralized exchanges.
Beneath the Crypto Currents: The Hidden Effect of Crypto “Whales” (Chernoff and Jagtiani)
The paper examines the impact of large Ethereum holders on market dynamics, revealing that big investors benefit from price movements, while smaller investors face adverse effects.
Investor Sentiment, Unexpected Inflation, and Bitcoin Basis Risk (Conlon et al.)
The paper analyzes the impact of investor sentiment and unexpected inflation on Bitcoin futures pricing and finds that extreme levels of market sentiment are associated with a negative Bitcoin basis.
Currencies
Foreign Currency Forecasting: What Can Stock and Bond Markets Tell Us? (Phylaktis and Yamani)
This paper explores whether past stock and bond returns predict currency spot returns and finds that local stock returns, relative to US stock returns, have a significant predictive power in emerging markets.
Equities
Recessions and Market Timing (QuantSeeker)
The release of recent unemployment figures has led to a debate on whether the U.S. economy has entered a recession. I explore what past recessions have meant for stock returns, provide a literature review on forecasting recessions and growth, and conduct a market-timing exercise with the so-called Sahm recession rule. Results suggest that timing equity exposure with recession indicators might enhance risk-adjusted returns.
Narrative Momentum (Lee et al.)
A long-short portfolio based on changes in narrative intensities yields a strongly significant alpha, as investors underreact to changing narratives in media.
Investor Search and Asset Prices (Hulley et al.)
A long-short strategy based on investors' simultaneous searches for related firms on the SEC EDGAR server yields a sizeable alpha and seems unrelated to other measures of closeness between firms.
ESG
Carbon VIX: Carbon Price Uncertainty and Decarbonization Investments (Fuchs et al.)
The authors construct a new measure of carbon price uncertainty in the form of the Carbon VIX, using option prices on EU emission allowances.
Inefficiencies of Carbon Trading Markets (Borri et al.)
This paper analyzes the EU emission allowance market and documents large inefficiencies which might undermine its environmental goals.
Forecasting
Causality-Inspired Models for Financial Time Series Forecasting (Oliveira et al.)
This paper explores several models for causality-based feature selection and compares their return forecasting abilities to non-causal feature selection models.
Machine Learning and Large Language Models
Large Language Model Agent in Financial Trading: A Survey (Ding et al.)
Recent research highlights the potential of large language models in trading, for example, in sentiment-driven strategies. This paper surveys the growing literature and provides a useful reference list for further reading.
An Evaluation of Standard Statistical Models and LLMs on Time Series Forecasting (Can and Wang)
Recent research explores whether large language models are useful in time series forecasting. This paper focuses on the LLMTIME model and finds that it underperforms classical ARIMA models across multiple datasets.
Predicting the distributions of stock returns around the globe in the era of big data and learning (Barunik et al.)
This paper introduces a method based on a quantile neural network for forecasting global stock return distributions, outperforming benchmark models by capturing complex data interactions.
Market Microstructure
Efficient estimation of bid–ask spreads from open, high, low, and close prices (Ardia et al.)
This recently published paper develops an improved method for estimating bid-ask spreads, reducing bias and variance, and achieving enhanced accuracy.
Portfolio and Risk Management
Dynamic Asset Allocation with Asset-Specific Regime Forecasts (Shu et al.)
The paper presents a framework that improves portfolio allocation by predicting specific regimes for individual assets using XGBoost.
On Accelerating Large-Scale Robust Portfolio Optimization (Hsieh and Lu)
The authors introduce a method that improves the computational efficiency in large-scale portfolio optimization, significantly reducing processing time while maintaining robust performance.
Infinite-mean models in risk management: Discussions and recent advances (Chen and Wang)
Infinite-mean models challenge traditional risk management by revealing limitations in classic statistical methods when dealing with fat-tailed data.
Blogs
Cross-country equity futures strategies (Macrosynergy)
Machine Learning and the Probability of Bouncing Back (Quantitativo)
Podcasts
Live Q&A – Return Stacking During Market Corrections (Get Stacked)
119 Great Investors Share the One Lesson They Would Teach the Average Investor (Excess Returns)
Nate Silver and Maria Konnikova on the Art of Election Betting (Odd Lots)
Bonds Behaving Badly ft. Katy Kaminski (Top Traders Unplugged)
A Conversation with Charlie Munger & John Collison (Invest Like the Best)
Cam Harvey: Forecasting Recessions (Enterprising Investor)
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