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
Riding the Waves: How Do Interest Rate Changes Affect Corporate Bond Mutual Fund Flows? (Huang et al.)
Expansionary monetary policy shocks are found to be associated with an inflow to investment-grade bond funds while flows into high-yield bond funds are largely unaffected.
Commodities
An unexpected easing in forward guidance is shown to immediately raises oil prices while also predicting positive long-term oil returns.
Crypto
This paper explores Ether staking and discusses Proof-of-Stake, different staking options, staking yields, associated risks, and more.
Data
I recently came across this source of free historical FX data, which some of you might find useful. It's top-of-book, tick-by-tick millisecond data, across a range of FX pairs.
Equities
Explaining and Forecasting Abnormal Returns and Volume by Investor Sentiment Indicators (Lis et al.)
This paper explores various measures of investor sentiment and find sentiment to have a significant impact on stock returns and volume, including predictability of returns.
Valuing Stocks With Earnings (Hillenbrand and McCarthy)
The authors highlight that Street earnings are less noisy than GAAP earnings and PE ratios based on Street earnings better predict returns.
Business News and Business Cycles (Bybee et al.)
This recently published paper uses a topic model to condense a large dataset of news articles into distinct topics and where estimates of topic attention predict macro variables and stock market returns.
The paper develops an industry-specific measure that predicts stock returns by analyzing inflation's impact across interrelated industries.
FX
Quantities and Covered-Interest Parity (Moskowitz et al.)
The authors examine how banks' balance sheet constraints and market segmentation affect deviations from covered-interest parity.
Lecture Notes
Linear Model and Extensions (Ding)
Extensive lecture notes by Peng Ding at Berkeley, covering OLS, Ridge, Lasso, WLS, Logistic regressions, Quantile regressions, and much more.
A Course in Dynamic Optimization (Light)
Lecture notes based on a graduate course in dynamic optimization, prepared by Bar Light at the Tel Aviv University’s School of Mathematics.
Machine Learning and Large Language Models
KAN based Autoencoders for Factor Models (Wang and Singh)
This paper introduces an asset-pricing model featuring a Kolmogorov-Arnold Networks-based autoencoder, which outperforms benchmark models in accuracy and interpretability.
Interpretable Machine Learning (Molnar)
This book covers interpretable machine learning across a range of models and techniques and is useful for both practitioners and students.
A novel approach to hedge fund portfolio construction is proposed that outperforms fund on fund benchmarks.
Macro
Has the Recession Started? (Michaillat and Saez)
The unemployment numbers that came out August 2nd triggered the so-called Sahm recession rule, suggesting that the US economy might have entered a recession. This paper constructs a related recession indicator that improves on the Sahm rule, detecting recessions earlier.
Market Microstructure
Dealer Trading at the Fix (Osler and Turnbull)
The paper explores how dealers manipulate foreign exchange, silver, and gold prices at market fixes through strategic trading, leading to increased volatility and potential collusion.
Forecasting High Frequency Order Flow Imbalance (Anantha and Jain)
This study constructs a high-frequency indicator of order flow imbalance (OFI) and explores several predictive models for the OFI, applied on tick data for Nifty futures.
Portfolio Management
Marginal Sharpe Ratio (Sestovic)
The author derives simple and useful expressions for the marginal Sharpe ratio and provides numerical examples of how adding investments to an existing portfolio impact risk-adjusted returns.
Trading
Algorithmic Trading in Financial and Sports (Exchanges) (Goodacre and Schlagman)
The paper explores how algorithmic trading is transforming both financial and sports exchanges, highlighting their similarities and differences.
Volatility
Cryptos Have Rough Volatility and Correlated Jumps (Krain et al.)
The paper analyzes Bitcoin's price dynamics, highlighting the importance of rough volatility and correlated jumps for predicting returns.
Smile Dynamics and Rough Volatility (Bourgey et al.)
This paper explores various stochastic volatility models and their generated dynamics for implied volatility, focusing on the Skew-Stickiness Ratio.
DeepVol: Volatility Forecasting from High-Frequency Data with Dilated Causal Convolutions (Moreno-Pino and Zohren)
The authors propose a volatility forecasting deep-learning model which is found to outperform more traditional volatility models.
Blogs
A Mean Reversion Strategy from First Principles Thinking (Quantitativo)
So You Want to Start a Trading Business (Robot Wealth)
The DeFi Intermediation Chain (Federal Reserve Bank of New York)
Podcasts
Successful Investing in a Disrupted World ft. Aswath Damodaran (Top Traders Unplugged)
Major Market Moves - What Now, Trend Followers? ft. Nick Baltas (Top Traders Unplugged)
Andrew Chen: "Is Everything I was Taught About Cross-Sectional Asset Pricing Wrong?! (The Rational Reminder)
Tom Basso - Trading Serenity Within the Chaos (The Algorithmic Advantage)
Cashing in Through Exploiting Volatility w/ Greg Magadini (Chat with Traders)
Challenging Conventional Investing Beliefs with Meb Faber (Excess Returns)
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