Skip to content
Thomson Reuters
Asset Management

ETFs and the predictive power of StarMine signals

Brenda Zhang

05 Mar 2018

Photographer: Akhtar Soomro
Photographer: Akhtar Soomro

As passive ETFs continue their explosive growth, we examine the predictive power of StarMine signals in building profitable trading strategies using country ETFs.

Download the full research note: Using Thomson Reuters StarMine signals for country selection

In recent years, passive investment and interest in index mutual funds and exchange-traded funds (ETFs) has dramatically increased.

Between 2007 and 2016, the Investment Company Institute estimates that index domestic equity mutual funds and ETFs received US$1.4 trillion in net new cash and reinvested dividends.

In contrast, actively managed domestic equity mutual funds experienced a net outflow of $1.1 trillion.

In light of this rapid growth, constructing appropriate investing strategies using ETFs is now more important than ever.

Watch: What does an entire quant team in a single platform look like?

StarMine models

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.

In 2011, research by Jasmeet Khela and Dirk Renick found that aggregating StarMine Value-Momentum (Val-Mo) model scores within countries is a profitable methodology to determine future outperformance at a country level.

Can the other StarMine alpha models be used to select country index products? And how can these signals be used to construct profitable trading strategies using index ETFs?

Learn how Thomson Reuters can help you to apply scientific methods to your quantitative research and trading

Portfolio out-performance

To find out the answer, our research covered the StarMine Analyst Revisions model and the Price Momentum, Intrinsic Valuation, Relative Valuation, Value-Momentum, Earnings Quality, Smart Holdings and Combined Alpha models.

We created 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 Thomson Reuters 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.

Download the full research note: Using Thomson Reuters StarMine signals for country selection

Download the report: StarMine Signals for Country Selection

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 percent and a long-only quintile return of 2.3 percent.

Find out how Asset Management Solutions from Thomson Reuters can give can give you the edge to grow your AUM

Top performing StarMine signals

The StarMine Price Momentum model and Combined Alpha model are consistently solid and outperform the benchmark as well. The chart below delineates the cumulative quintile spread for the five top performing StarMine signals.

Cumulative Return - Top Performing StarMine Portfolios

Moreover, we have discovered that a linear combination of multiple StarMine signals achieves long-short quintile spread returns of 13.7 percent annually over a ten-year period.

Furthermore, we show that a simplified and more practical version of this strategy, which requires knowing only the top holdings of ETFs, is also profitable.

Download the research note to get the full analysis

StarMine Quantitative Analytics

Why dealmakers have great expectations for 2018 Destination Quant: Where analysts explore the power of data Eikon App Studio: A powerful tool for internal apps Equity funds still positive despite market volatility How FIX is changing post-trade FX for the sell-side Record inflows boost European ETF industry Quant funds and a trillion dollar question of risk Eikon App Studio: New apps for February Building a data strategy for trading automation Millennials and why your organization should care about ESG