by Thomson Reuters.
In recent years, passive investment through indices has been growing significantly, and investors’ interest in index mutual funds and exchange-traded funds (ETFs) has dramatically increased. According to the Investment Company Institute, “from 2007 through 2016, index domestic equity mutual funds and ETFs received $1.4 trillion in net new cash and reinvested dividends, while actively managed domestic equity mutual funds experienced a net outflow of $1.1 trillion.” 1 With the explosive growth in passive ETFs, constructing appropriate investing strategies using these ETFs is more important now than ever.
StarMine has created a number of unique and highly effective quantitative equity alpha models. These StarMine models have a long and proven track record of being strong predictive tools to rank individual securities and generate alpha. Khela and Renick found in 2011 that aggregating StarMine Value-Momentum (Val-Mo) model scores within countries is a profitable methodology to determine future outperformance at a country level.2
Can we use these StarMine models to construct profitable trading strategies using country index products and ETFs?
We examine whether country selection based on aggregating StarMine signals is profitable. We include the StarMine Analyst Revisions model, Price Momentum model, Intrinsic Valuation model, Relative Valuation model, Value-Momentum model, Earnings Quality model, Smart Holdings model and Combined Alpha model. We create a long-short strategy based on a market capitalization-weighted average of StarMine signals within each country, where the individual securities comprising each aggregate are selected using Global Equity Indices. With the success of that proof-of-concept we subsequently demonstrate how this strategy is profitable when applied to tradable liquid country ETFs.
Based on monthly data from 2007 to 2016, most aggregated StarMine signals show consistent ability to sort country proxies and outperform an equally weighted portfolio of all country proxies on both a long-only and long-short basis. The StarMine Earnings Quality model dominates the performance and generates an average annualized quintile spread of 10.4% and a long-only quintile return of 2.3%. StarMine Price Momentum model and Combined Alpha model perform consistently solid and strongly outperform the benchmark as well. The Figure below delineates the cumulative quintile spread for the five top performing StarMine signals.
Moreover, we have discovered that a linear combination of multiple StarMine signals achieves long-short quintile spread returns of 13.7% annually over a 10 year period.
Furthermore, we show a simplified and more practical version of this strategy, requiring knowing only the top holdings of ETFs, is also profitable.