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!
Crypto
Decentralized and Centralized Options Trading: A Risk Premia Perspective (Andolfatto et al.)
The paper compares decentralized and centralized options trading, highlighting differences in implied volatilities due to fee structures and trading dynamics.
Geopolitical Risks and Cryptocurrency Returns (Yilmazkuday)
The study finds that major cryptocurrencies generally decline in value following geopolitical risks and threats, offering a poor hedge.
Empirical Asset Pricing
Technical Analysis and Currency Trading: False Discoveries and Informative Covariates (Filippou et al.)
The paper introduces a method using multiple covariates to improve the detection of profitable currency trading strategies while controlling for false discoveries.
Liquid Factor Models (Rosenthal)
The paper proposes a model using liquid, easily tradable instruments to create transparent factors that exhibit low correlations.
What Is the False Discovery Rate in Empirical Research? (Engsted)
Empirical research in social sciences often underestimates the high rate of false discoveries due to statistical misinterpretations.
The 52-Week High, Downside Risk, and Corporate Bond Returns (Keshavarz and Sirmans)
The paper demonstrates that a stock's 52-week high ratio effectively predicts corporate bond returns by signaling potential financial risks.
Ponzi Funds (van der Beck et al.)
The paper examines how concentrated investment funds can create self-inflated returns through price pressure, leading to wealth redistribution among investors and potential market bubbles.
Lecture Notes
Data-Driven Methods in Finance (Cohen)
Naftali Cohen offers this course at Columbia. Great lecture notes are provided. Topics covered include factor models, stock screening, portfolio optimization, rebalancing and transaction costs, and more…
Market Microstructure
Major Issues in High-frequency Financial Data Analysis: A Survey of Solutions (Hua and Zhang)
The authors survey recent research on predicting and modeling high-frequency returns, as well as issues related to high-frequency data.
Trading
James H. Simons, PhD: Using Mathematics to Make Money
A discussion with Jim Simons on quant investing, how he runs his business, competition among quant firms, philanthropy, and much more.
Volatility
Forecasting International Stock Market Variances (Bekaert et al.)
This study consider many different volatility models and specifications and test their ability to predict realized variances one month ahead across a range of developed markets.
Blogs and Podcasts
Evaluating macro trading signals in three simple steps (Macrosynergy)
How to Succeed at Multi-Strategy Hedge Funds (Odd Lots - podcast)
The Life of One of Wall Street’s Greatest Investors (WSJ - podcast)
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