Lazard Insights : An Underappreciated Factor Jason Williams, CFA, Portfolio Manager/Analyst Summary Quantitative investment managers commonly employ value, sentiment, quality, and low risk factors to capture excess returns, but have often overlooked the growth factor An alternative, active approach to identifying growth stocks, however, can deliver a more consistent and diversified pattern of returns There are instances when both value and sentiment will be out of favor; growth will often lead in those down markets Incorporating the perspectives of fundamental analysts offers important insights for a manager Lazard Insights is an ongoing series designed to share valueadded insights from Lazard s thought leaders around the world and is not specific to any Lazard product or service. This paper is published in conjunction with a presentation featuring the author. The original recording can be accessed via www.lazardnet.com/insights. What Is an Investment Factor? An investment factor is a deliberate and consistent exposure that quantitative investment managers may include in their portfolios. Many of these managers employ a series of factors to seek excess returns over time. The most commonly used factors are value, sentiment, quality, and low risk, and are measured based on a particular metric, or set of metrics, that adequately represent the desired exposures. For instance, investors seeking value exposure may evaluate and rank stocks based on their price to earnings (P/E) ratio and, as a result, will only include stocks that are highly ranked on a P/E basis. Does the Factor Matter? While quantitative managers commonly employ a series of factors to capture excess returns, they often ignore growth as an investment signal. Historically, growth stocks have traded at lofty valuations and have underperformed both value and sentiment factors. In this paper, however, we suggest an alternative be considered, namely a customized approach to identifying growth stocks that can deliver excess returns over the long term.
2 Exhibit 1 Factor Performance Rotates through Time (Index) 24 MSCI World Value Sentiment Quality Exhibit 2 The Factor Performs Well Enough to Merit Consideration 16 8 Value 36.9% Sentiment 3.% 18.9% Quality 14.3% 1999 22 25 217 As of 3 June 217 For illustrative purposes only. The information is not representative of any product or strategy managed by Lazard. The indices are unmanaged and have no fees. One cannot invest directly in an index. Performance is based on rolling 24-month differences in price index returns. The performance quoted represents past performance. Past performance is not a reliable indicator of future results., Bernstein As of 3 June 216. Data from the MSCI World Index (1999 216). For illustrative purposes only. The information is not representative of any product or strategy managed by Lazard. The indices are unmanaged and have no fees. One cannot invest directly in an index. Performance is based on rolling 24-month differences in price index returns. The performance quoted represents past performance. Past performance is not a reliable indicator of future results. A Different Approach to Measuring To begin, we measured the effectiveness of four naïvely constructed factor families value, growth, quality, and sentiment (momentum) in the MSCI World Index on a monthly basis from 1998 through 217 (Exhibit 1). While there have been clear drivers of sustained outperformance such as value since 215, there are frequent rotations among the factor categories dominating in any given month. This observation illustrates the challenge of continuously relying on one factor category to deliver outperformance. Likewise, over the 18-year period, while value and sentiment each dominated the rankings about one-third of the time, growth still led about 19% of the time (Exhibit 2). Thus, while growth was not as large a contributor as either value or momentum in an absolute sense, we believe it has dominated market preferences enough of the time to merit consideration. Offers Diversification An important feature of growth as an investment style is its diversifying properties as it shows a low correlation with other factor measures (Exhibit 3). The returns delivered by growth stocks are highly differentiated compared to value, sentiment, and quality factors. This low correlation argues for growth s incorporation in an investor s portfolio if only to achieve greater consistency in terms of excess returns, especially during market cycles when both sentiment and value are out of favor. Yet, despite these diversifying properties, growth s underperformance during the past decade has discouraged managers from including this factor in their overall portfolios. Exhibit 3 Exhibits Low Correlation to Other Factors Value Sentiment Quality 1 Value -.37755 1 Sentiment -.5915 -.59913 1 Quality.17482 -.15296.48514 1 Data from the MSCI World Index from 1999 216 The correlation matrix reflects the correlation of a blended mix of monthly returns expressed in terms of quintile spreads. Value measures: 5% P/E and 5% P/B; measures: 5% 5-year EPS growth and 5% 5-year sales growth; Sentiment measures: 5% 12-month momentum and 5% EPS analyst revisions; and Quality measures: 33% operating margins, 33% return on equity, and 33% leverage. Exhibit 4 shows the performance of a naïve portfolio of growth stocks based on a combination of growth metrics that capture both sales and earnings growth. The performance of the top 2% of stocks minus the bottom 2% of stocks on a cumulative basis is shown since. Not surprisingly, this fairly naïve and simplistic way of identifying growth stocks has failed to deliver excess return, or alpha, over the entire period due largely to the significant drawdown it experienced from May through the end of. During our initial research in, instead of relying on the two simplistic measures employed by the naïve growth factor, we instead identified a series of fourteen individual measures that collectively distinguished companies with superior growth capabilities. We ranked each measure in a binary fashion and indicated whether a positive action or signal versus its peers or its own history was taking place. A positive reading on a significant
3 Exhibit 4 Naïve Has Been a Drag on Performance a (Index, 1=31 May ) 11 Exhibit 5 Active Factors vs. Naïve : A Longer-Term Focus Can Offer Alpha a (Index, 1=31 May ) 11 1 1 Lazard 9 8 Naïve 213 As of 3 September 215 a Naïve growth represents an equal-weighted combination of historic EPS and sales growth along with projected EPS growth applied to a capitalizationweighted universe of stocks with greater than $2 million market capitalization (6, developed markets companies). Returns are computed monthly and reflect the difference between stocks ranked in the highest 2% (most growth) less those in the lowest 2% (least growth). This chart is for illustrative purposes only. majority of these measures would signify a company that has longterm potential to grow at a faster rate than its peers. Unlike the naïve growth factor, this active growth factor actually performed well during the market drawdown in. It was also successful at delivering long-term alpha, particularly in the favorable growth environment of 215 when global central banks heavily leaned on quantitative easing to drive long-term rates lower (Exhibit 5). To further test the effectiveness of our model, we divided our growth rankings into quintiles and measured each company s earnings per share over the following three years. The top 2% of stocks, as ranked by our growth measure and methodology, consistently goes on to achieve the highest level of future growth. This approach was effective in highlighting companies with superior growth in earnings (Exhibit 6). Fundamentally Revisiting 215 In 215, we initiated a research project to re-examine the underpinnings of our growth model. One motive for this initiative was a recognition that the metrics we used to measure growth required more nuance. The project began by meeting with individual Lazard analysts to better understand the criteria they employed to find 9 8 Exhibit 6 Model Forecasting EPS Rate 3-Year Observed EPS by Quintile a (%) 1.4 1.2 1..8.6 27 Naïve 213 As of 3 September 215 a The return of Lazard represents the return constructed using equal weights of the top 2% minus the bottom 2% of securities in the Lazard global stock universe. The top and bottom 2% stocks are selected using the Lazard Quantitative Equity model's proprietary quantitative growth factor. Factor returns shown in US dollars, gross of management fees and other costs for an unconstrained universe. It does not represent any actual portfolio managed by Lazard. Past performance is not a reliable indicator of future results. The value of investments can fall as well as rise. Investors capital may be at risk. Naïve growth represents an equal-weighted combination of historic EPS and sales growth along with projected EPS growth applied to a capitalization-weighted universe of stocks with greater than $2 million market capitalization (6, developed markets companies). Returns are computed monthly and returns reflect the difference between stocks ranked in the highest 2% (most growth) less those in the highest 2% (least growth). This chart is for illustrative purposes only. Fifth Quintile Fourth Quintile Third Quintile Second Quintile First Quintile 213 As of 31 March 217 a The quintiles are selected using the Lazard Quantitative Equity model s proprietary quantitative growth factor. We measured each company s EPS over the next three years. The fifth quintile represents the top-ranked quintile. 215
4 companies with superior growth prospects. From these interactions, we sought to identify central themes and metrics that we could then test to determine their discriminatory power. We discovered that many companies shared common characteristics across different sector groups. It, therefore, made sense to redefine the universe away from these sectors and into new groups in which there was commonality in the business subtleties that drive growth in the companies. This finding that many companies have similar business models across sectors that share drivers of growth led us to redefine our investment universe into five new business groups: Asset Heavy Asset Light Knowledge Based Financials Real Estate These five groups were defined according to classification variables that we used to help classify the respective groups. The insights provided by the fundamental analysts enabled us to create a unique set of growth variables for each business group. These variables can be thought of as the key drivers needed to create the conditions for long-term growth potential in that particular business group. So, how does this new factor perform compared to our older growth factor? The revamped growth factor shows a significant improvement in returns (Exhibit 7). In addition, when the new growth factor is incorporated with our sentiment, value, and quality factors, it provided an 11% alpha improvement (Exhibit 8). We believe our initial research in and improvements since provide a strong incentive to include growth in an overall investment portfolio. Understanding We have long advocated that investors should seek growth at points during economic cycles. Incorporating the growth factor in a quantitative process will provide the opportunity to realize a positive return in such periods and may offer a more consistent and diversified pattern of return. Gaining a better understanding of the specific criteria and indicators of growth used by fundamental analysts has provided us with a number of insights that has enabled Exhibit 7 Revamped Factor Shows a Significant Improvement in Returns... (Index, 1=3 November 1995) 5 4 3 2 1 1996 New Capability 2 24 Previous Capability As of 31 May 216 Capability refers to our new and previous proprietary growth models in the Knowledge-Based Business Group. 216 Exhibit 8 and Added More Alpha when Combined with Other Factors (Index, 1=3 November 1995) 3, 2,4 1,8 1,2 6 1996 As of 31 May 216 2 24 New Alpha Previous Alpha 216 us to improve our forecasting abilities. Their insights can help us enhance how we quantitatively assess the future prospects for stock returns in order to further improve the size and the consistency of returns for investors.
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