A Quant's Approach to Getting Sentimental about Security Selection

FactSet | July 20, 2015

In this study, FactSet explores the usefulness of RavenPack Indicators in both isolation and as a supplement to other factors within the Russell 2000 index.

Executive Summary:

RavenPack Equity Indicators deliver value on the Russell 2000 as standalone factors or in conjunction with traditional factors, says Joe Importico, Vice President, Analytics Specialist at FactSet.

In both cases, the sentiment indicators show promise with respect to how sentiment is affecting security price movements.

RavenPack Indicators help identify both potential winners and losers. The chart below shows active returns for Russell 2000 constituents by sentiment decile.

Quant Approach security selection

RavenPack Indicators enhance returns associated with traditional factors. The chart below shows cumulative returns for Earnings Yield, Top 100 Sentiment and combined portfolios.

Quant Approach security selection

Quant Approach security selection

1. Introduction

No matter how you define your ideal subset of securities, there are often a number of quantitative metrics available to help identify the type of company you're looking for. Say you're a manager following a value strategy. How might you go about identifying your top candidates within a given market? For starters, you could comb through a variety of quantitative measures, such as relative valuation multiples, levels of sustained profitability, rates of return on capital vs. costs of capital, and so on. Then, once you've identified the desired characteristics, you may apply thresholds to ensure the only companies that pass, and thus warrant additional analysis, are those meeting your predefined preferences. This method is common within the investment community as a way of introducing efficiencies to the sometimes arduous task of security selection.

Identifying quantitative measures to screen on and applying constraints is seemingly straightforward, but there are, as always, limitations to the flexibility offered by such an approach. One notable limitation comes in the form of being able to integrate qualitative information into the screening process. Where quantitative measures can assist in identifying the profile of a company, or in this case, set of companies, qualitative measures will help us better understand the market's perception surrounding these companies.

So how can individuals harnessing a security selection process go about integrating qualitative metrics like investor sentiment into their process? Some investors back into this approach by using quantitative measures that capture negative sentiment, such as increased short sale volume relative to a predefined trading interval or insider trading patterns, as ways to denote market sentiment. Both short sale volume and insider trading are implicit ways to capture sentiment, but we're still missing the ever­changing landscape of news and media. One readily available way to integrate qualitative, sentiment driven analytics into a security selection process is through a pre­defined database like RavenPack, which offers a variety of indicators that quantify positive and negative perceptions based on opinions and facts reported through the media. The specific metrics available span sentiment, volume, and abnormality indicators.

To test the usefulness of these indicators, I focused on the sentiment strength indicator over the trailing 91 day period, applying the RavenPack indicators via FactSet's alpha testing tool. The sentiment strength indicator can be applied in isolation or as a complement to augment another factor. I'll detail both approaches at a high­level, starting with evaluating the efficacy of this factor in isolation within the Russell 2000 index.

Sentiment Strength Factor Profile

To start, let's get a closer look at the profile of this factor from a risk and return perspective. In the charts below, I've partitioned the companies in the Russell 2000 into deciles based on their 91­day sentiment strength scores. From there I've annualized the returns and volatilities attributable to each group. As you can see, there is a clean...

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