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!
Bonds
Finding value in the U.S. corporate bond market (Wu and Zaman)
A corporate-bond valuation model is proposed that captures the cross-section of yields well, and where yield residuals based on the model significantly predict future bond returns.
Crypto
Unlocking Ethereum's Potential: The Rise of Spot ETFs in Cryptocurrency Investment (David Krause)
The approval of Ethereum spot ETFs by the SEC offers investors managed access, potentially increasing market liquidity and diversification opportunities.
Review of deep learning models for crypto price prediction: implementation and evaluation (Wu et al.)
This is a survey paper on applications of deep learning models for predicting returns on cryptocurrencies.
Equities
Mosaics of Predictability (Cong et al.)
The paper introduces a new method for clustering assets to reveal patterns in return predictability, highlighting significant heterogeneity across different asset characteristics and economic conditions.
Manager Uncertainty and the Cross-Section of Stock Returns (Tengfei Zhang)
The paper introduces a new measure of managerial uncertainty, demonstrating its predictive power and significant negative impact on stock returns.
The Social Media Risk Premium (Hosseini et al.)
Social media risk is shown to be priced in the cross section of stocks and bonds, warranting a significant premium.
Futures
"Spreads" in U.S. Treasury Futures Markets: Calendar Spreads vs. Offsets (Onur et al.)
The paper reveals that most "spread" positions in U.S. Treasury futures are offsets, significantly increasing traders' exposure to interest rate risks.
Market Microstructure
Deep Limit Order Book Forecasting (Briola et al.)
The paper explores the use of deep learning to predict stock price movements in high-frequency trading, highlighting the influence of market microstructure and the limitations of traditional evaluation metrics.
Do Low Latency Traders Destabilize Prices? Evidence from News Releases (Chordia et al.)
The paper examines how rapid traders, by exploiting news releases, amplify stock overpricing and disrupt market efficiency, especially when retail investors are involved.
Options
Factor Dispersions (Gerchik et al.)
The paper analyzes how dispersion strategies, which measure variance differences between a basket and its components, can predict investment opportunities and risks
Portfolio Allocation
Quantitative Wealth and Investment Management (QWIM): Advanced Portfolio Diversification (He et al.)
The authors discuss shortcomings of the classical mean-variance framework and explores the potential benefits of hierarchical clustering techniques in portfolio construction.
Portfolio Optimization with Robust Covariance and Conditional Value-at-Risk Constraints (Qiqin Zhou)
This study evaluates robust covariance estimators for portfolio optimization, highlighting Gerber covariance's superior performance during bull markets but noting limitations in extreme conditions
The Economic Value of Mean Squared Error: Evidence from Portfolio Selection (Cai et al.)
The authors demonstrate that the mean squared error (MSE) is economically valuable for portfolio selection.
Conditional Correlation via Generalized Random Forests; Application to Hedge Funds (Aghapour et al.)
The paper presents a random-forest approach to estimating correlations between financial assets, detecting non-linearities.
Blogs and Podcasts
Finding Edges: The Importance of Being a Pirate (Robot Wealth)
6 ways to detect a failing trading strategy – with Kevin Davey (Better System Trader)
Sharing the Trend Following Pie ft. Andrew Beer (Top Traders Unplugged)
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