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!

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Crypto

LiqBoost: Enhancing Liquidity Provision for Blockchain-based Decentralized Exchanges (Jeong et al.)

The paper introduces LiqBoost, a new scheme enhancing liquidity in decentralized exchanges by reallocating inactive positions, reducing trading costs.

The Evolution of Decentralized Exchange: Risks, Benefits, and Oversight (Harvey et al.)

The authors discuss the advantages and risks of decentralized exchanges and emphasize the need for regulatory considerations.

Decomposing cryptocurrencies behavioral anomalies (Shahzad et al.)

The paper analyzes how various behavioral anomalies, like recency bias and salience theory, impact cryptocurrency returns.

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Equities

Inflation and the Carbon Premium (Bolton et al.)

Energy price inflation is found to increase the carbon premium for U.S. companies with high carbon emissions.

Momentum: what do we know 30 years after Jegadeesh and Titman’s seminal paper? (Tobias Wiest)

This is a survey article on momentum with a tilt towards equity momentum, covering the main papers in the literature, discussing variants of the classical momentum strategy, as well as potential explanations for why momentum exists.

Passive Investing and the Rise of Mega-Firms (Jiang et al.)

The paper examines the impact of passive investing on stock prices, highlighting how it disproportionately elevates the prices and volatility of large, overvalued firms, thus skewing the market.

The Cross-Section of Stock Returns before CRSP (Baltussen et al.)

The study investigates historical U.S. stock returns from 1866 to 1926, revealing significant factor premiums.

Forecasting in periods of heightened uncertainty: The Importance of Aggregate Short Interest (Henry et al.)

The ability of short interest to predict returns is amplified in periods of high financial uncertainty.

Creative Destruction, Stock Return Volatility, and the Number of Listed Firms (Bartram et al.)

The paper examines how the increase in publicly listed companies raises idiosyncratic stock return volatility through creative destruction.

Earnings and Free Cash Flow--A Primer (Martin and McNabb)

This paper provides an introduction to financial statement analysis and to the relation between earnings and cash flow and its effect on corporate valuations.

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Investor Beliefs

Institutions' Return Expectations across Assets and Time (Dahlquist and Ibert)

This study examines institutional investors' return expectations across asset classes, finding they move countercyclically and being consistent with rational asset pricing models.

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Machine Learning

DeepUnifiedMom: Unified Time-series Momentum Portfolio Construction via Multi-Task Learning with Multi-Gate Mixture of Experts (Ong and Herremans)

The authors present a deep learning framework that integrates momentum strategies across different timeframes, beating benchmark models.

Predictive Modeling of Foreign Exchange Trading Signals Using Machine Learning Techniques (Enkhbayar and Slepaczuk)

This paper explores trading strategies for six major currency pairs based on a range of machine-learning methods and classical MA-crossover trend following strategies.

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Statistical Arbitrage

Application of Black-Litterman Bayesian in Statistical Arbitrage (Qiqin Zhou)

The author applies the Black-Litterman framework to a pairs trading strategy.

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Volatility

HARd to Beat: The Overlooked Impact of Rolling Windows in the Era of Machine Learning (Audrino and Chassot)

The heterogeneous autoregressive (HAR) model typically serves as a benchmark model when forecasting volatility and is shown to outperform machine learning models.

Cluster GARCH (Tong et al.)

This paper introduces a new multivariate GARCH model called Cluster GARCH, which is shown to outperform more conventional multivariate models.

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Blogs and Podcasts

Macroeconomic trends and financial markets: theory and evidence (Macrosynergy)

The new indicator that improves momentum trading signals – Alex Spiroglou (Better System Trader)

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