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Investing Research Articles

3597 Research Articles

Beta Males Make Hedge Fund Alpha

Does appearance-based masculinity predict hedge fund manager performance? In their January 2018 paper entitled “Do Alpha Males Deliver Alpha? Testosterone and Hedge Funds”, Yan Lu and Melvyn Teo use facial width-to-height ratio (fWHR) as a positively related proxy for testosterone level to investigate the relationship between male hedge fund manager testosterone level and hedge fund performance. They each… Keep Reading

Ask for Advisor’s Personal Investing Performance?

Are financial advisors expert guides for their client investors? In their December 2017 paper entitled “The Misguided Beliefs of Financial Advisors”, Juhani Linnainmaa, Brian Melzer and Alessandro Previtero compare investing practices/results of Canadian financial advisors to those of their clients, including trading patterns, fees and returns. They estimate account alphas via multi-factor models. Using detailed data from two large… Keep Reading

Chess, Jeopardy, Poker, Go and… Investing?

How can machine investors beat humans? In the introductory chapter of his January 2018 book entitled “Financial Machine Learning as a Distinct Subject”, Marcos Lopez de Prado prescribes success factors for machine learning as applied to finance. He intends that the book: (1) bridge the divide between academia and industry by sharing experience-based knowledge in a… Keep Reading

Mimicking Anything with ETFs

Can a simple set of exchange-traded funds (ETF), weighted judiciously, mimic the behaviors of most financial assets? In their January 2018 paper entitled “Mimicking Portfolios”, Richard Roll and Akshay Srivastava present and test a way of constructing mimicking portfolios using a small set of ETFs as investment factor proxies. They define a mimicking portfolio as a weighted set of… Keep Reading

10 Steps to Becoming a Better Quant

Want your machine to excel in investing? In his January 2018 paper entitled “The 10 Reasons Most Machine Learning Funds Fail”, Marcos Lopez de Prado examines common errors made by machine learning experts when tackling financial data and proposes correctives. Based on more than two decades of experience, he concludes that:

Equity Risk Premium and Investment Horizon

How should an investor’s view of the equity risk premium vary with investment horizon? In the December 2017 update of their paper entitled “Volatility Lessons”, Eugene Fama and Kenneth French examine how the U.S. equity risk premium (difference in returns between the expected equity market return over some horizon and return on U.S. Treasury instrument of matched… Keep Reading

Preliminary Momentum Strategy and Value Strategy Updates

The home page, “Simple Asset Class ETF Momentum Strategy” (SACEMS) and “Simple Asset Class ETF Value Strategy” (SACEVS) now show preliminary positions for February 2018. For SACEMS, past returns for the first and second positions and for the third and fourth positions are close, such that rankings could change by the close. For SACEVS, allocations are… Keep Reading

Momentum Investing in a Nutshell?

How, in a nutshell, do momentum investing strategies work? In his December 2017 paper entitled “Keep Up the Momentum”, Thierry Roncalli summarizes the nature of the momentum premium in a less mathematical way than in the previously available “Understanding the Momentum Risk Premium: An In-Depth Journey Through Trend-Following Strategies”. He distinguishes between: Time-series or trend-following or intrinsic or… Keep Reading

Bitcoin Return Based on Supply and Demand Model

Does the increase in number of Bitcoin wallets at a rate that far exceeds growth in number of Bitcoins explain the dramatic rise in Bitcoin price? In the December revision of his paper entitled “Metcalfe’s Law as a Model for Bitcoin’s Value”, Timothy Peterson models Bitcoin price according to Metcalfe’ Law, which posits that the value of… Keep Reading

P/E10 for Country Stock Market Timing?

“Usefulness of P/E10 as Stock Market Return Predictor” investigates whether P/E10 (or Cyclically Adjusted Price-Earnings ratio, CAPE) usefully predicts U.S. stock market returns over the long run. That analysis employs Robert Shiller’s data set, which defines P/E10 as inflation-adjusted S&P Composite Index level divided by average monthly inflation-adjusted 12-month trailing earnings of index companies over the last ten years…. Keep Reading