Investing Research Articles

Is it possible that all the 300+ published factors that predict stock returns (such as size, value, profitability, investment, momentum…) derive from data snooping? In his October 2018 paper entitled “The Limits of Data Mining: A Thought Experiment”, Andrew Chen estimates how much data snooping would be required to “discover” all these factors by pure luck. Specifically,… Keep Reading

How should researchers applying machine learning to quantitative finance address the field’s data limitations, which exacerbate data snooping bias? In their October 2018 paper entitled “A Backtesting Protocol in the Era of Machine Learning”, Robert Arnott, Campbell Harvey and Harry Markowitz take a step back and re-examine financial markets research methods, with focus on suppressing backtest overfitting of investment… Keep Reading

Do employees of financial intermediaries such as brokers, financial analysts and fund managers take advantage of their access to private information? In their March 2018 paper entitled “Personal Trading by Brokers, Analysts, and Fund Managers”, Henk Berkman, Paul Koch and Joakim Westerholm examine the personal trading of employees at Finnish financial intermediaries (experts) who have regular access to material… Keep Reading

Do exchange-traded funds (ETF) exhibit statistically reliable short-term reversal and intermediate-term momentum? In their October 2018 paper entitled “Momentum Strategies for the ETF-Based Portfolios”, Daniel Nadler and Anatoly Schmidt look for reversal and momentum in next-month performance of past winners and past losers for the following 13 universes: U.S. Equity ETFs: 28 US equity ETFs with returns available… Keep Reading

How have costs of U.S. stock trading data evolved in recent years? In his October 2018 paper entitled “Retail Investors Get a Sweet Deal: The Cost of a SIP of Stock Market Data”, James Angel examines costs of U.S. stock market data. He also describes the production of these data and their consolidation/distribution via Securities Information Processors (SIP)…. Keep Reading

Below is a weekly summary of our research findings for 11/26/18 through 11/30/18. These summaries give you a quick snapshot of our content the past week so that you can quickly decide what’s relevant to your investing needs. Subscribers: To receive these weekly digests via email, click here to sign up for our mailing list.

How do journalists develop the information that appears in the financial media? In their November 2018 paper entitled “Meet the Press: Survey Evidence on Financial Journalists As Information Intermediaries”, Andrew Call, Scott Emett, Eldar Maksymov and Nathan Sharp report results of a survey of and follow-up interviews with financial journalists on inputs, incentives and beliefs that shape their reporting. Using 462… Keep Reading

Is there a single variable based on accounting data that reliably captures expected returns of individual stocks? In their October 2018 paper entitled “A Fundamental Factor Model”, Stephen Penman and Julie Zhu construct and test a fundamental expected returns factor based on array of accounting inputs, encompassing earnings, book value and items that sum to these income statement and… Keep Reading

What is the best way to construct equity multifactor portfolios? In the November 2018 revision of their paper entitled “Equity Multi-Factor Approaches: Sum of Factors vs. Multi-Factor Ranking”, Farouk Jivraj, David Haefliger, Zein Khan and Benedict Redmond compare two approaches for forming long-only equity multifactor portfolios. They first specify ranking rules for four equity factors: value, momentum, low volatility… Keep Reading

Is the U.S. equity turn-of-the-month (TOTM) effect exploitable as a diversifier of other assets? In their October 2018 paper entitled “A Seasonality Factor in Asset Allocation”, Frank McGroarty, Emmanouil Platanakis, Athanasios Sakkas and Andrew Urquhart test U.S. asset allocation strategies that include a TOTM portfolio as an asset. The TOTM portfolio buys each stock at the open on… Keep Reading