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
Cross-Bond Momentum Spillovers (Wang et al.)
This paper constructs a measure of connectedness between firms and uses past momentum in corporate bonds of peer firms to predict future corporate bond returns.
Commodities
Weathering Market Swings: Does Climate Risk Matter for Agricultural Commodity Price Predictability? (Ma et al.)
This paper finds that climate risk predicts returns on agricultural commodities.
Mean-Reverting Statistical Arbitrage Strategies in Crude Oil Markets (Fanelli)
This paper considers a statistical arbitrage portfolio involving WTI, Brent, and Dubai oil futures and finds meaningful out-of-sample performance net of costs.
Crypto
Decoding DAI: Exploring Collateral Evolution and Price Dynamics (Oefele et al.)
The authors explore the drivers of DAI prices and how the collateral of DAI has changed over time.
Currencies
Currency Return Dynamics: What Is the Role of U.S. Macroeconomic Regimes? (Feng et al.)
This paper explores the influence of U.S. economic conditions on currency returns using a Bayesian regime-switching model.
Debtors, creditors, and the carry trade (Eriksen and Kjaer)
An FX carry strategy within debtor countries is shown to generate at least the same Sharpe ratio as the standard carry trade but without crash risk.
Equities
Downside Risk Reduction Using Regime-Switching Signals: A Statistical Jump Model Approach (Shu et al.)
A market timing strategy using a statistical jump model to identify bull and bear markets outperforms using Markov-switching models, achieving higher Sharpe ratios and lower turnover.
Predicting Analysts’ S&P 500 Earnings Forecast Errors and Stock Market Returns using Macroeconomic Data and Nowcasts (Sharpe and Cruz)
The authors find that the difference between forecasts from a parsimonious macro model and from analysts predicts stock returns and provides value for market timing.
Does Accounting Information Identify Bubbles for Fama? Evidence from Accruals (Arif and Sul)
Changes in net operating asset accruals are found to be a robust negative predictor of industry returns and positively associated with future crashes.
Predicting public market behavior from private equity deals (Barucca and Morone)
This paper uses data on private equity deals from FactSet in a logit model and finds that it predicts returns on overall market returns and sector-specific returns.
Idiosyncratic Earnings and Market Efficiency (Han et al.)
This paper decomposes firm profitability into market, industry, and firm-specific components and sorting stocks on the latter component yields a strongly significant cross-sectional return spread.
Machine Learning and Large Language Models
Large Language Models in Finance: A Survey (Li et al.)
This is a comprehensive survey paper on the applications of large language models in finance and provides an extensive reference list for further reading.
Robust Stock Index Return Predictions Using Deep Learning (Jagannathan et al.)
The authors propose a neural-network model to predict index returns, producing robust short-term forecasts.
Hedge Fund Replication with Deep Neural Networks and Generative Adversarial Networks (Chatterji)
The author finds that recurrent neural networks together with GANs show promise in replicating hedge fund returns as they capture non-linear exposures and identifies relevant factors.
Market Microstructure
Unwinding Toxic Flow with Partial Information (Barzykin et al.)
This paper proposes a model for managing toxic order flow by deciding whether to internalize or externalize orders, considering feedback effects, and accounting for momentum or mean reversion in order flow.
Mutual Funds
Forecasting Mutual Fund Performance – Combining Return-Based with Portfolio Holdings-Based Predictors (Muller et al.)
The authors aggregate information from 19 different predictors and find significant predictability of future fund performance.
Options
Valuation and Hedging of Cryptocurrency Inverse Options (Lucic and Sepp)
This paper explores the pricing and hedging of inverse options and provides backtests for several systematic option strategies using Deribit options data.
Variance Risk Premiums in Emerging Markets (Qiao et al.)
The authors construct variance risk premiums for a range of emerging markets and find that they predict stock returns, in particular for horizons longer than six months.
Pricing and Calibration in the 4-Factor Path-Dependent Volatility Model (Gazzani and Guyon)
This paper revisits the 4-factor path-dependent volatility model of Guyon and Lekeufack (2023), proposes a faster and more robust calibration process, and showcases the impact of an additional parameter.
Greeks-based implied volatility interpolation (Rolloos)
This paper enhances implied volatility interpolation by incorporating higher-order Greeks and demonstrates its effectiveness using the Heston and Variance Gamma models.
Blogs
Diversification for Trend Following Models: The Small Variations Matter (ATS Trading Solutions)
A portfolio of strategies (Quantitativo)
Books
The Predictive Edge: Outsmart the Market using Generative AI and ChatGPT in Financial Forecasting (Alejandro Lopez-Lira)
Bayesian Sports Models in R (Andrew Mack)
Podcasts
The Key to Trend Following Success ft. Cole Wilcox (Top Traders Unplugged)
Uncovering hidden market reaction zones - with Fabio Ruggeri (Better System Trader)
Karen Karniol-Tambour: Market Outlook, Portfolio Construction (The Insightful Investor)
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