Investing Research Articles

A reader asked whether Charles Nenner, self-described as “the talk of Wall Street since accurately predicting some of the biggest moves in the Markets over the past few years,” accurately forecasts equity and commodity markets. We consider the following: In his July 2007 discussion of the “Nenner Methodology at the Bloomberg Studio”, Charles Nenner cites sunspot… Keep Reading

Is there a flip side of cyclic relative weakness to the cyclic relative strength described in “Pervasive 12-Month (and 5-Day) Relative Strength Cycles?”? In their October 2018 paper entitled “Seasonal Reversals in Expected Stock Returns”, Matti Keloharju,Juhani Linnainmaa and Peter Nyberg test whether cyclic weakness (seasonal reversal) balances the cyclic strength (seasonality) effect. For example, if a stock… Keep Reading

Is there a distinct systematic asset risk, as measured by its market beta, associated with each return measurement interval (frequency, such as daily, monthly or annually)? In other words, is return measurement frequency a risk factor? In their October 2018 paper entitled “Measuring Horizon-Specific Systematic Risk via Spectral Betas”, Federico Bandi, Shomesh Chaudhuri, Andrew Lo and Andrea Tamoni  introduce… Keep Reading

Below is a weekly summary of our research findings for 12/3/18 through 12/7/18. 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.

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.