Investing Research Articles

How should investors assess the risk of financial advisor misconduct? In their March 2016 paper entitled “The Market for Financial Adviser Misconduct”, Mark Egan, Gregor Matvos and Amit Seru investigate the recent extent of misconduct among registered financial advisors (“advisors”) and financial advisory firms in the U.S. Their data include employment history, customer disputes, disclosed investigations and disciplinary events (civil, criminal… Keep Reading

Can individual investors easily mimic the asset allocation strategies, and thereby the returns, of university endowments? In his March 2016 paper entitled “Invest Like an Endowment”, Drew Knowles reviews the asset allocation policies and resultant investment returns of those college and university endowments who volunteer such data to the National Association of College and University Business Officers (NACUBO). He… Keep Reading

What happens out-of-sample to stock portfolios with weights derived from extreme in-sample fitting? In their February 2016 paper entitled “Stock Portfolio Design and Backtest Overfitting”, David Bailey, Jonathan Borwein and Marcos Lopez de Prado examine backtest overfitting in the context of designing a stock portfolio/fund. Their test approach is: Construct split-adjusted, dividend-reinvested price series for all S&P 500 components as of January 22,… Keep Reading

Is Robert Shiller’s cyclically adjusted price-to-earnings ratio (CAPE or P/E10) a better predictor of long-term stock market performance than other valuation ratios? In his January 2016 paper entitled “Predicting Stock Market Returns Using the Shiller CAPE — An Improvement Towards Traditional Value Indicators?”, Norbert Keimling first examines whether reduced dividend payout, new accounting standards and structural changes to key stock indexes… Keep Reading

How can investors easily estimate the degradation from optimized in-sample Sharpe ratio to out-of-sample expected Sharpe ratio? In their February 2016 paper entitled “Noise Fit, Estimation Error and a Sharpe Information Criterion”, Dirk Paulsen and Jakob Sohl derive a simple correction for the upward bias in an optimized in-sample Sharpe ratio. The upward bias derives from fitting: (1) random… Keep Reading

A subscriber suggested evaluating Sentdex Sentiment Trading Signals. These signals attempt to derive the emotion of a current body of text (over 20 sources, mainly Reuters, Bloomberg, WSJ, LA Times, CNBC, Forbes, Business Insider and Yahoo Finance) regarding financial assets such as individual stocks and stock indexes. Signal values are 24-hour averages, ranging from -3 (strongest negative) to… Keep Reading

How well do mutual funds and exchange-traded funds (ETF) designed to track hedge fund indexes work? In their October 2015 paper entitled “Synthetic Hedge Funds”, Mario Fischer, Matthias Hanauer and Robert Heigermoser examine the performance of synthetic hedge funds, defined as open-end mutual funds and ETFs that explicitly employ hedge fund indexes as their primary benchmarks. They assess replication success:… Keep Reading

“Pervasiveness and Robustness of SMA Effectiveness for Stocks” summarizes research finding that long-term simple moving averages (SMA) pervasively outperform a buy-and-hold approach for U.S. stocks and stock portfolios during 1960-2011 and for seven developed stock markets during 1975-2010. Does this research, which focuses on a 24-month SMA, discover some essential cyclical nature of equity markets?… Keep Reading

Is systematic selling of equity index put or call options an attractive strategy? In their December 2015 paper entitled “Index Options Realized Returns Distributions from Passive Investment Strategies”, Jose Dapena and Julian Siri analyze equity index call and put option returns from the perspective of a seller. They view a systematic option seller as an insurance company: (1) collecting… Keep Reading

What kinds of smart beta work best? In their January 2016 paper entitled “A Taxonomy of Beta Based on Investment Outcomes”, Sanne De Boer, Michael LaBella and Sarah Reifsteck compare and contrast smart beta (simple, transparent, rules-based) strategies via backtesting of 12 long-only smart beta stock portfolios. They assign these portfolios to a framework that translates diversification, fundamental weighting and factor investing… Keep Reading