Lazard Insights

Interpreting Active Share

Erianna Khusainova, CFA, Senior Vice President, Portfolio Analyst

A number of studies and articles have emerged claiming that most Summary active managers underperform their benchmarks and investing in index funds and passive exchange-traded funds (ETFs) is a better • While the value of active management has been called into question, the aggregate performance alternative. However, some of these studies included “closet indexers,” of active managers improves when excluding funds that claim to be active, but in reality, are very similar to the so-called closet indexers, which can be identified index. The inclusion of these funds may lead to inaccurate results. by low active share. In addition to the traditionally used tracking error metric, Martijn • Active share is an important metric that helps Cremers and Antti Petajisto¹ introduced a new statistic for measuring determine how different a portfolio is from its benchmark. Together, tracking error and active active management called active share. Their research demonstrated share complement each other to make a more that funds with the highest active share significantly outperformed robust assessment of an active manager’s process. their benchmarks, both before and after fees. In other words, if you • The active share metric has limitations since it exclude closet indexers, active management’s aggregate results improve. is susceptible to several considerations, such So, what exactly is active share? It is the portion of a portfolio that is as the structure of the benchmark used and the dynamics of an individual portfolio construction invested differently than its benchmark. More precisely, active share is process. calculated by, first, comparing each holding’s weight in the portfolio and the benchmark and computing the absolute value of the difference • Investors should be aware of the factors that may influence the attainable level of active between the weights; then, taking half the sum of these absolute active share. Therefore, investors should view closet weights to represent the portfolio’s active share. More simply, active indexing thresholds as guidelines that need to be share can be described as the sum of a portfolio’s overweights. With re-adjusted upwards or downwards depending on no short positions or leverage, active share will be between 0% (the a specific situation. portfolio is identical to the benchmark) and 100% (the portfolio is entirely different from the benchmark). Conceptually, the higher the percentage, the more “active” the manager is. Lazard Insights is an ongoing series designed to share value- added insights from Lazard’s thought leaders around the Exhibit 1 presents a hypothetical five-stock portfolio with active share world and is not specific to any Lazard product or service. equal to 40%. Column 2 represents weights of securities in the port- This paper is published in conjunction with a presentation folio, while column 3 represents weights of securities in the index. The featuring the author. The original recording can be accessed difference between the two is active weight (shown in column 4), which via www.LazardNet.com. is the underlying basis for the active share computation. Summing up 2

with ten industries and twenty stocks in each, a portfolio could hold Exhibit 1 one stock in each industry, or primarily invest in securities not included Active Share in a Hypothetical Five-Stock Portfolio in the benchmark, while keeping the same industry weights as the Portfolio Index Active ABS Active Overweight benchmark. This hypothetical portfolio would most likely generate a Security Weight (%) Weight (%) Weight (%) Weight (%) (%) low tracking error due to similar industry bets even though the man- A 20 10 10 10 10 ager’s stock positions are very different from the benchmark. B 15 5 10 10 10 C 40 25 15 15 15 On the other hand, factor bet managers can generate a substantial tracking error with minimal deviations from benchmark holdings. D 25 20 5 5 5 Managers classified as concentrated integrate the two approaches, by E 0 40 -40 40 0 taking both factor bets and actively choosing individual stocks (note Sum 100 100 0 80 40 that the term concentrated, as used by Cremers and Petajitso, does not Active Share (%) 40 40 refer to portfolios with few holdings, as used more conventionally). A

This information is for illustrative purposes only and is not intended to represent any “closet indexer” claims to be active; however, scores low on both track- product or strategy managed by Lazard. ing error and active share. An index-tracking vehicle gravitates towards zero on both dimensions (Exhibit 2). absolute active weights and dividing this sum by two will result in 40% active share for this portfolio. Alternatively, as mentioned earlier, active Exhibit 2 share can be calculated as the sum of portfolio stock overweights. Active Management Spectrum ti h A Two-Dimensional Approach for

Measuring Active Management igh Diversified Concentrated The only way to outperform an index is to be different from it. Active Stock Picks Stock Picks managers attempt to do this through two main approaches. The first approach is stock selection, which is selecting individual stocks from a larger universe based on their potential ability to enhance a portfolio’s Closet Factor Bets return. This approach usually results in owning fewer stocks than those Indexing included in the benchmark and often investing in stocks outside of the Pure benchmark. The second approach involves factor bets, which can be Indexing defined as overweighting or underweighting entire sectors, industries, igh or regions. Active managers using this approach will change the port- ing folio’s weights based on their views on systematic economic risks. This information is for illustrative purposes only. Traditionally, a portfolio’s degree of active management has been Source: Cremers and Petajisto (2009) assessed by tracking error, which measures the volatility of excess returns. Due to its nature of computation, tracking error has the potential to be a better indicator of factor bets. Portfolios that take Active Share and Performance large factor bets are associated with high tracking error. However tracking error does not necessarily fully account for the degree of The results of Petajisto’s study of US mutual funds are presented deviation of the portfolio’s individual holdings relative to the bench- in Exhibit 3. The highest active share group, “Stock Pickers,” out- mark. As a result, looking solely at this statistic can be misleading since performed their benchmark by 126 basis points (bps) net-of-fees, low tracking error is not always indicative of a passive management annualized. While strict thresholds are difficult to define, Cremers style. Stock selection within sectors in a portfolio can significantly and Petajisto set the active share cutoff at 60% for a US mutual fund deviate from index holdings even though factor bets can be similar. universe, meaning that funds with active share below this threshold are In contrast, a large tracking error can be generated through systematic potential closet indexers. factor bets without large deviations from index holdings. Active share Since those findings were specific to the US equity universe, we has a better ability to capture effects of stock-picking actions as it looks examined if a similar relationship exists between active share and per- at the positions relative to individual holdings. formance in the global and international equity universes. The results 2 Together, tracking error and active share complement each other to of our research are summarized in Exhibit 4. Although studied over a make a more robust assessment of an active manager’s process. Cremers different and shorter time period (2007 to 2011), the period includes and Petajisto defined a two-dimensional approach to more comprehen- both the financial crisis and the recovery phase of the market cycle. sively classify active and passive management. Diversified stock pickers In our study, the highest active share quintile of our sample corresponds can generate low tracking error despite their active stock selection. To to the highest average outperformance result, which was consistent with emphasize this point, consider the following example. In a benchmark 3

Exhibit 3 Exhibit 4 US Equity Mutual Fund Performance and Characteristics, The Highest Active Share Funds Also Had the Highest 1990–2009 Outperformance in International and Global Equity Funds, 2007–2011 Gross Net Average Average Average Excess Excess Active Tracking Number Active Share Average Active Gross Excess Net Excess Return (%) Return (%) Share (%) Error (%) of Stocks Quintile Share (%) Return (%) Return (%) Stock Pickers 2.61 1.26 97 8.5 66 High 92.8 2.33 1.17 Concentrated 1.64 -0.25 98 15.8 59 86.2 1.69 0.44 Factor Bets 0.06 -1.28 79 10.4 107 81.1 1.52 0.37 Moderately 0.82 -0.52 83 5.9 100 75.1 1.26 0.17 Active Low 59.3 0.10 -0.95 Closet 0.44 -0.91 59 3.5 161 Indexers Fund performance for the period 2007 to 2011 The performance quoted represents past performance. Past performance is not a The performance quoted represents past performance. Past performance is not a reliable indicator of future results. This information is for illustrative purposes only and reliable indicator of future results. This information is for illustrative purposes only and does not represent any product or strategy managed by Lazard. does not represent any product or strategy managed by Lazard. Source: Lazard, “Taking a Closer Look at Active Share” by Khusainova and Mier, 2013 Source: Petajisto (2013) previous active share research. However, international and global funds with active share below 70% fall into the lowest quintile. This contrasts Exhibit 5 Active Share over Time—Trends in Closet Indexing with the previously described threshold of 60% (in a US equity mutual fund universe) to spot closet indexers. As we study other investment tin t n ssts ti h ng universes the interpretation of active share is more nuanced and we emphasize that these thresholds are guidelines rather than strict pass or ng fail tests. Certainly, more empirical tests are warranted to help refine global criteria for interpreting active share. For instance, it would be adar ar ara interesting to extend tests across emerging markets and other invest- ment universes with constituent-light and -heavy benchmarks.

Trends in Closet Indexing Petajisto’s research also evaluates the historical trends in closet index- ing. In 2009, the percent of closet index funds (funds with active share between 20% and 60%) increased from 1.1% in 1980 to 31% in 2009 (Exhibit 5). Closet indexing originally reached high levels during the Source: Petajisto (2013) 1999–2002 time period, then declined until 2006, and hiked again from late 2007–2009 toward its prior peak. Interestingly, market volatil- ity trends were similar: the Chicago Board Options Exchange Market Limitations of Active Share Volatility Index (VIX) hovered around 25% throughout 1998–2002. As The immediate implication from our discussion thus far is that the market recovered strongly and volatility reduced, so did closet index- investors should only seek managers with high active share and avoid ing. Then during the global financial crisis of 2007–2008, volatility potentially expensive investments with closet indexers. However, soared again while markets experienced drastic declines. Closet indexing investors should not rush to conclusions solely based on the proposed followed suit and by 2009 it reached its prior pinnacle level. 60% threshold in every investment universe and circumstance. Active Highly volatile market environments may prompt some managers to share is impacted by a number of factors that will affect its attainable deviate less from their benchmark since return differences tend to be levels. For instance, active share is highly susceptible to the structure of magnified in this kind of environment. There is also a psychological the benchmark used. Depending on the index used, the same portfolio factor, where trailing the index in a declining market is especially hurt- can attain a significantly different active share since indices widely ful when everyone’s capital is already deteriorating. Another factor that vary in number of constituents, distinct weighting methodologies, and could have contributed to the rise of closet indexing is the Security different concentration levels. Using an inappropriate benchmark that Exchange Commission’s additional index disclosure requirements in does not reflect a portfolio’s investment universe, market-capitalization mutual fund prospectuses that were implemented in 1998. While the spectrum, style, or asset class will result in artificially inflated active goal was to provide fund shareholders with more information and share due to fewer overlapping holdings and dominance of false “active increased transparency, it may have also encouraged managers to cur- bets.” Investors should be aware of benchmark inputs when comparing tail benchmark risk through more alignment with the index. active share in a cross section of portfolios of the same style. 4

In the case of a legitimate benchmark selection, the structure of some managers employing the former benchmark versus using one with the indices predisposes them to elevated active share levels. Generally, this opposite characteristics. will include broad, constituent-heavy, less-concentrated indices serv- Exhibit 6 demonstrates the inverse relationship between the level of ing as a proxy for global and/or small-cap universes, for example. The concentration and active share supporting the earlier point that high ranges defining closet indexers should be re-evaluated for portfolios concentration in fewer stocks will structurally limit the manager’s abil- using constituent-heavy benchmarks to offset this structural bias. ity to generate high active share. To construct this chart, we used data Additionally, investors should be aware of multiple security types on US mutual funds’ active share (available on Petajisto’s website). representing a single company such as American Depository Receipt/ We grouped the funds by benchmark and calculated the average active Global Depository Receipt (ADR/GDR) versus ordinary shares, as share for each group; we then plotted these numbers against the bench- well as varying share classes and exchanges. Mismatched security types marks’ concentration in their largest twenty securities. in an investment portfolio versus its benchmark may create artificial bets. Therefore, a conversion to the parent company identifier is Active share is also susceptible to the dynamics of the individual port- needed when calculating active share. folio construction process. If a manager finds attractive investment opportunities in the large-capitalization space, overweighting the larger Factors that can lead to artificially low active share such as a small capitalization spectrum will most likely produce lower active share investment universe or usage of a constituent-light index (such as relative to the portfolio which gravitates toward overweighting the MSCI Emerging Markets Latin America Index, FTSE NAREIT All small- and mid-capitalization spectrum using the same benchmark. The Equity REITs Index) have to be kept in mind. Fewer investment reason is that expressing a bullish view on a position that has a large choices naturally limit a manager’s ability to have meaningfully differ- weight in the index requires the deployment of a good amount of port- ent stock positions across available securities, both within and outside folio capital with limited ability to generate high active weight. of the benchmark. Therefore, attaining a high active share in a small universe may simply not be feasible, and the ranges defining closet indexers should be reevaluated downward. Exhibit 6 To further demonstrate potential benchmark biases, compare, for Benchmark Concentration Will Influence the Size of Active Share example, the MSCI All Country World Index (ACWI) consisting of 2,470 constituents as of December 2014 with the MSCI Emerging ight in ings Markets Latin America Index composed of only 137 constituents. A In manager benchmarked to the ACWI has a greater opportunity set to ss In ss find compelling stocks to overweight and a greater number of stocks In to forgo than a manager using the MSCI Emerging Markets Latin i In America Index. So, the manager in the ACWI universe has a much better chance to score a high active share. Similarly, index concentra- ss i In tion is another variable impacting active share. The top twenty holdings ss In of the FTSE NAREIT All Equity REITs Index represent close to 55% of the market capitalization of this index. Contrast that with around ti h 5% concentration represented by the top twenty securities in the Russell 2500 Index, as of December 2014. High concentration in fewer As of September 2009 stocks poses a greater challenge to increase active share for the fund Data show funds’ average active share by benchmark (total 289 funds). Source: Petajisto (2013), http://www.petajisto.net/data.html

Exhibit 7 Individual Views on Portfolio Construction Influence Active Share

Portfolio A Portfolio B Russell 1000 Value Index Market Capitalization ($B) Weight (%) Number of Securities Weight (%) Number of Securities Weight (%) Number of Securities >40 45.0 24 18.0 9 58.7 72 20 to 40 33.0 36 31.0 25 15.8 83 10 to 20 14.0 8 23.0 19 10.9 117 0 to 10 8.0 12 28.0 27 14.7 432 Total 100.0 80 100.0 80 100.0 704

As of 31 December 2014 For illustrative purposes only. Allocations are subject to change. The data in the chart above is not meant to represent any product or strategy managed by Lazard. 5

Looking at two hypothetical portfolios (Exhibit 7) benchmarked Conclusion against Russell 1000 Value Index one can see that portfolio B is better positioned for higher active share relative to portfolio A. This is due Active share has become an important addition to the toolkit for eval- to the fact that portfolio B allocates more to the small- and mid-cap uating actively managed portfolios. With that said, the measure has market spectrum where the opportunity set of securities to overweight certain limitations. For a more insightful interpretation and to avoid is higher while weights of small- and mid-cap stocks are smaller. On erroneous conclusions, several factors need to be considered. First, the other hand, portfolio A has higher allocations to large cap stocks. the appropriate benchmark used in calculating active share must be This requires more resources to generate meaningful active share while verified. Then, investors should be aware of the benchmark’s structural the manager is being constrained by a smaller sub-universe of large- characteristics, the universe size, and unique portfolio construction weight stocks. processes that may influence the attainable level of active share. When attempting to identify closet indexers, defining the appropriate active share ranges warrants caution. Importantly, investors should view “high active share” and “closet indexing” thresholds as guidelines that need to be re-adjusted upwards or downwards depending on a specific situation.

Notes 1 Active share literature is composed of two key papers: • Cremers, Martijn and Antti Petajisto. “How Active Is Your Fund Manager? A New Measure That Predicts Performance.” The Review of Financial Studies, September 2009. • Petajisto, Antti. “Active Share and Mutual Fund Performance.” Financial Analysts Journal, July/August 2013. Working papers were circulated in 2006 and 2010 respectively. Cremers and Petajisto were professors at the Yale School of Management while working on the first paper. 2 Khusainova, Erianna, and Juan Mier. “Taking a Closer Look at Active Share.” Lazard Investment Research, March 2013. Paper available at: http://www.lazardnet.com/investment-research/

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