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U.S. Small Caps: Smoke And Mirrors

Summary The aim of this quick study is to check whether the well-known outperformance of US small caps over US large caps: Is true? Is persistent with respect to market timing? Is persistent with respect to internal selectivity within the index? Every investor – rookie or experience – already would have heard about the well-known, small caps’ outperformance. The topic is not as simple as it seems to be. It has to be followed very cautiously. This article is an attempt to give readers some major keys, enabling them to avoid expensive mistakes. This study relies on two indices: – S&P 500 Total Return – Russell 2000 Total Return Database stands between December 31, 1998 and December 22, 2015. Persistent with Market Timing? We can notice that an investor who checked their performance at the end of each year, and who had kept their equity position until December 22, 2015 would have noticed an outperformance of S&P 500 versus Russell 2000 no matter they had invested at the end of 2004, 2005, 2006, 2007…or 2014. This outperformance varies between 1.7% (investment at the end of 2007) and 24.9% (investment at the end of 2010). Therefore, the post 2008 rally in equities was clearly driven by large caps (here through S&P 500) over small caps (here through Russell 2000). In the table below, the outperformance of large caps is exhibited in the bottom right. Everywhere else in the table, and whatever be the holding period, the Russell 2000 has posted a better performance than the S&P 500. The only period in which we notice a similar outperformance by the S&P 500 was during the equity market crash in 2007-2008 as large caps were being considered safer than small caps – a case of clear defensive reaction. The rally that followed enabled the US equity markets to rise by 162.3% for the S&P 500 since December 31, 2008 and by 150.5% for Russell 2000 since December 31, 2008. Please note that between December 31, 2010 and December 22, 2015, the S&P 500 rose by 80.2% whereas Russell 2000 posted ‘only’ a 55.3% growth. There is one explanation for this: the market has changed, with the increase in ETF investing, smart-beta and systematic strategies. (click to enlarge) Source: Author’s own The 15.9% number in the table shows the difference between S&P 500 Total Return and Russell 2000 Total Return between December 31, 2010 and December 22, 2014. From the table we can infer that until 2010, the Russell 2000 has been outperforming the S&P 500 regularly, except in 2007-2008, where the ‘washout’ was much more important for small caps than for large caps. It seems that since 2010, investor behavior has changed with a big shift towards ETFs and smart-beta, risk premia solutions, focusing on large caps and low-volatility assets (Minimum Variance method, Equal Risk Contribution). Persistent with Internal Selectivity Within the Index – Actuarial and Total Return We check the composition of each index at the last day of year Y-1, and assume the composition remains stable over year Y. Given the huge rotation of US indices, it is a way to minimize the error due to index reshuffle and to birth and death sample bias. Source: Author’s own Look at the 1999 table. The Russell 2000 posted a 21.3% performance, with an average performance of the components of 25.6%. The median is -7.6%! almost 30 points low. Except in 2002, the median performance of the Russell 2000 components has been always below the average performance, or below the performance of the Index. Two explanations: – The median performance of the components is lower than the average performance. This means that the distribution exhibits excessively large returns on the positive side, dramatically shifting the average return on the upside. – The average performance of the components is lower than the index performance. This means that these indices, being capitalization-weighted, give more weight to large capitalizations. Therefore, large capitalizations tend to outperform small, even within the Russell 2000 Index. Shown below is the distribution of the annual performances of the components from S&P 500 and Russell 2000. Source: Author’s own These distributions are very interesting, especially focusing on the extreme left tail, the right hand part of the body and the extreme upper side of the distribution. Without any surprise, tails are a lot thicker for Russell 2000 than for S&P 500. Moreover, on Russell 2000, best annual performances exceed 1000%. Question is: Given the well-known investor asymmetry between gain and loss, do you think that a stock which is up 100% YTD will be kept in the portfolio by the asset manager? Don’t you think that he would cut the position in order to ‘take his profit’? Therefore, in a stock-picker paradigm, and given the behavioral and cognitive biases, it can be considered as very difficult to keep a large (> 100%) winning position. Thus, the contribution of positive extremes to the Russell 2000 cannot be taken into account in a stock-picking framework. Using medians in order to measure each stock performance seems then a much more reasonable assumption (look below). (click to enlarge) Source: Author’s own This table shows the difference between the median of S&P 500 and the median of Russell 2000. Since 2004, the median of S&P 500 outperforms regularly the median of Russell 2000. In other words, if your stock-picking is not able to catch the extreme positive returns on Russell 2000, then you should shift to stock-picking within S&P 500, as the best proxy of your expected return (the median) is by far higher on the latter index. On the other hand, should you be interested in investing through ETFs, then you can choose to invest in Russell 2000 ETFs rather than in S&P 500 ETFs as you get the performance of the index. Until 2010, the Russell 2000 Index used to outperform S&P 500 regularly. Within the Russell 2000, may we exhibit any pattern? In the image below, colors are important – the more positive, the greener, the more negative, the redder. Rows stand for capitalization quartiles, from the smallest (top) to the largest (bottom). Columns stand for volatilities quartiles from the smallest (LHS) to the largest (RHS). Source: Author’s own Looking at the performance (capitalization (row); volatilities (column)), we can notice that although over the period, the performance of the index is largely positive (+249% total return between December 31, 1998 and November 11, 2015) – meaning it was a bull market on average 7.7% per year, the red cells are much more represented on the right column of the table. This happens when the index performance is negative, of course (2002, 2008), but it also happens when the index performance is flat or mildly positive (2000, 2001, 2004, 2011, 2012, 2014, 2015). On the other hand, these high volatility stocks strongly outperform the universe in two periods out of seventeen: 1999 and 2003, with respective total return performance of the Russell 2000 of +21%, +47%. This means that the outperformance of volatile small caps is very hard to capture because over the long run it may be easy to experience huge drawdowns with difficulties to recover. Keep in mind that when a stock drops by 50%, it needs to increase by 100% to come back to the initial level. Regarding capitalization effect, things seem to be more difficult to explain. As a summary for this part, should you want a smooth pattern, focusing on the low-volatility stocks in N-1 is worth in order to succeed in such a challenge, whereas dealing with historically high-volatility stocks may suffer from huge drawdowns (2002, 2008), and only rare astonishing performances, which may struggle in erasing the previous underperformance. The issue is always the same: what is your investment timeframe? For more information: Why US investing differs a lot from European investing Conclusion Due to the weight of extreme returns, the performance of Russell 2000 is pulled up dramatically. Russell 2000 is a non-representative index of small caps given that the small caps universe can be summarized as “many are called, but few are chosen,” but the ones which are chosen exhibit amazing performances (more than +1000% per year) hiding the many which are not chosen and post performances close to -100%. The asymmetry of actuarial returns (compared to logarithmic returns) then emphasizes these extreme positive returns whose upper limit is + infinity, whereas a stock price cannot go below 0, flooring the extreme bad performance to -100%. Second, given the asymmetry of the investor with gain and loss, these extreme positive returns are not sustainable in a stock-picking framework, as everybody knows that investors are likely to take profit on a largely winning position, meaning that it is very unlikely that they keep an equity position whose performance already equals +100% per year. Therefore, studying the small cap universe through the mean does not seem to take this behavioral bias into account. Using the median seems more relevant. In addition to the data explained, investing in US small caps by picking stocks from the Russell 2000 means struggling with scarce liquidity. In a nutshell, should you want to invest in small caps, do it through a Russell ETF; should you want to pick up stocks, you should rather choose an S&P 500-equivalent universe, as the left tail of the distribution of S&P 500 is a lot thinner than the one of Russell 2000. The development of ETFs and the increasing flows on these strategies and smart-beta and risk premia are likely to increase the pattern we exhibit in this paper. So from now, when speaking about the outperformance of small caps, you can say, “Small caps are smoke and mirrors. Should you want to outperform the S&P 500, you have to be good at picking the stocks (the famous 2% positive extremes), AND you have to be good at timing the market ” Companies whose aim is to pick up US Small Caps almost always underperform the Russell 2000 (Median Performance of the Members < Index Performance). Now you are able to understand why. Would you rationally invest in such a strategy? (Too?) many people are convinced that they have the skills to pick up the famous 2% stocks that post astonishing performances. Be careful as too much self-confidence is likely to turn into overconfidence and a long-term underperformance.

Why U.S. Investing Differs A Lot From Europe Investing…

Summary US is definitely not a market for traditional stock pickers, as this market is a flow-driven market. In Europe, the economic knowledge of the population is very low. Stock pickers should focus on Europe, and systematic or factor-based investors on the US. Smart risk management is as important as finding equity ideas to generate alpha. The whole study with all the statistics and charts may be found on SSRN , or just ask the author. We compare European Indices (DJ STOXX 600, EURO STOXX 50, FTSE 100) to US Indices (Russell 2000, S&P 500, NASDAQ Composite, NASDAQ 100) and Japanese Indices (TOPIX, Nikkei 225). First, from 2014 December 31st to 2015 November 11th. Using a longer period could lead to wrong conclusions given the important turnover of the components within each index (roughly 5% per year), and the death-survivorship bias. Therefore, in a second attempt, we compare the behavior of the large indices such as the TOPIX, NASDAQ Composite and Russell 2000 year after year, from 1999 to 2015. We do the same analysis for DJ STOXX 600, even if the sample seems tight. Why year after year and not the 16 years in a row? Because turnover is huge on US indices, and the Russell 2000 or NASDAQ Composite composition as of 2015 is very different from the one as of 1999. Russell 2000 Beta per couple (capitalization; volatility) (click to enlarge) First of all, turnover is huge. Therefore, it is important to stress again that a study over a long period of this index versus its components is not relevant. Second, looking at the performance vs. (capitalization; volatilities), we can notice that although over the period, the performance of the index is largely positive (+249% total return between Dec. 31st 1998 and Nov. 11th 2015) – meaning it was a bull market with on average 7.7% per year – the red cells are much more represented on the right column of the table. This happens when the index performance is negative of course (2002, 2008), but it happens as well when the index performance is flat or mildly positive (2000, 2001, 2004, 2011, 2012, 2014, 2015). On the other hand, these high-volatility stocks strongly outperform the universe in two periods out of 17: 1999 and 2003, with respective total return performance of the Russell 2000 of +21%, +47%. This means that the outperformance of volatile small caps is very hard to capture, because over the long run, it may be easy to experience huge drawdowns with difficulties to recover. Keep in mind that when a stock drops by 50%, it needs to increase by 100% to come back to the initial level. Regarding capitalization effect, things seem to be more difficult to explain. As a summary for this part, should you want a smooth pattern, focusing on the low-volatility stocks in N-1 is worth in order to succeed in such a challenge, whereas dealing with historically high-volatility stocks may suffer from huge drawdowns (2002, 2008), and only rare astonishing performances, which may struggle in erasing the previous underperformance. The issue is always the same: what is your investment time frame? And it has to deal with the way performance fees are calculated and rewarded. If the latter depend on High-Water Mark (HWM), then low volatility should be chosen. If it does not, then the performance fees may be perceived as a yearly call on performance… And when you are long a call, it depends positively on volatility, and do not suffer if the market is negative end of year, as its value is null. Therefore, the asset manager is likely to choose the riskier stocks as he may – even if it is only two years among 17 – sharply outperform the index punctually and underperform most of the time. HWM is strongly needed in order to protect investors from these types of greedy and unconscious asset managers. This phenomenon is likely to persist and be amplified by the emergence of smart-beta, risk premia, through the ETF market which is huge in the US and tends to offset the traditional Mutual and Hedge Funds: flows focus on ETF, and the latter focus on low-volatility stocks creating and feeding the famous “low-volatility puzzle”, challenging the well-known Markowitz theory. In this puzzle, the lower the volatility, the higher the expected return, whereas Markowitz used to state the opposite… Regarding the persistence of the winners and losers, this relationship is quite volatile. According to the numerous papers by Bouchaud (“Two centuries of trend following”), most of the time the market is trend followers, but when the regime changes, it hurts a lot (examining the performance of CTAs may help to understand – CTAs being by construction trend followers). 2009 is a very good example (with the red circle): the losers of 2008 were the winners of 2009, within a strong rebound of the market. It looks as if after a huge drop, the rule is to buy the worst performers. Looking at the beta per volatility quartile, the higher the historical volatility, the higher the beta, whereas there is no clear pattern with respect to capitalization. This can be explained by the fact that small capitalizations are perceived to be more volatile than large, but in practice, this is not the case. Do not forget that beta is the ratio of covariance over the product of standard deviations, therefore the surprising “in-range” beta is much more explained by the low numerator (covariance): small caps are volatile but not correlated with the benchmark, whereas large caps are less volatile but much more correlated with the benchmark. Regarding stock picking, stock pickers are likely to pick their stocks in the upper right hand side of the table: low capitalization, high volatility. Low capitalization, because they aim at being anti-benchmark, and high volatility because their way of choosing relies on fundamental analysis and upsides – the higher the volatility, the higher the upside. The Russell 2000 is definitely not a territory for stock pickers, with 2% of the stocks exhibiting more than 100% YtD performance in 2015, and more than 55% doing worse than the index. Should you want to post performance by picking up small caps and high-volatility stocks within the Russell 2000 universe, then you have to be very sharp in terms of choosing the right ones, and avoiding all the underperformers (which are numerous – “Many are called, but few are chosen”), and be very sharp in terms of market timing, given the number of years small caps largely underperform. NASDAQ Composite Beta per couple (capitalization; volatility) (click to enlarge) Turnover is huge with less than 5% of the components remaining after 16 years. The “capitalization effect” is more important on the NASDAQ Composite than it is on Russell 2000. Russell 2000 only refers to small capitalization (less than 10BlnUSD), whereas the NASDAQ Composite gathers stocks whose capitalization lays between 2MlnUSD and 700BlnUSD in 2015. The beta is decreasing with respect to capitalization, and is increasing with respect to historical volatility, with a beta close to 2 for the couple (1st capitalization; 4th historical volatility). As for Russell 2000, the red part of the table is concentrated on the right hand side, with scarce very high outperformances. Same explanation about the smoothness profile required, and the performance fees policy needed. Regarding the persistence of the winners and losers, this relationship is quite volatile, as for Russell 2000. Most of the time (and easy to see in 2002 and 2015), the winners of N-1 remain the winners of N (momentum effect), whereas in a year such 2009, the breach is very sudden and the relationship no longer holds. Looking again at the couple (1st capitalization; 4th historical volatility), which we use as a proxy for stock picking here the ranking of this couple among the other couple per year. The ranking goes from 1 to 16. We could say that the higher the index performance, the higher the ranking of this “stock-picking couple proxy” (“SP”). Before 2012, it works. But since 2012, we can notice that in spite of the huge performance of the index (respectively +17.8% and +40.2% in 2012 and 2013), this stock-picking proxy lags a lot. We compare the stock-picking proxy to its opposite, the “benchmark proxy” which is the couple (4th capitalization; 1st historical volatility) (“B”). In 2012 and 2013, the respective median performance (in absolute value) of “SP” and “B” were: The impact of ETF and “low-volatility” Smart Beta (“Minimum Variance” products, “Equal Risk Contribution” products) dramatically changed the market, developing, thanks to the high risk-aversion of customers (still traumatized by the 2008 drop in equities). The flows are huge and totally offset any fundamental reasoning since 2010. At this date, two years after the big krach, investors are eager to take some equity risk again, but with strong risk management. This is the promise of these ETFs. On the other hand, one can notice the difference of magnitude between the performance boundaries over the years: It is interesting to look at this table as of logarithmic return, as this type of returns keeps the symmetry. Therefore, we can notice that “B” suffers less from asymmetry than “SP”. The same reasoning we already made on Russell 2000 holds here again about huge drawdowns for “SP”, and the smooth pattern for “B”, with less difficulty to recover. Once again, the performance fees policy is the key to secure the shareholder, and prevent him from any rogue asset manager. As for the Russell 2000, the NASDAQ Composite is definitely not a territory for stock pickers, with 2.5% of the stocks exhibiting more than 100% YtD performance in 2015, almost 2/3 doing worse than the index, and a random stock picking underperforming the index by almost 10%. The market evolution and the emergence of ETF do not allow any stock picker to outperform the index. DJ STOXX 600 Beta per couple (capitalization; volatility) (click to enlarge) Turnover is pretty low compared to the US indices. Beta depends as on capitalization (negative relationship), and historical volatility (positive relationship). The difference between stock pickers (“SP”) as explained for the NASDAQ Composite and benchmark investors (“B”) is pretty clear on the table, with a beta of 0.66 for “B” in the lower left, and a beta of 1.57 in the upper right. Red and green colors seem a lot more balanced than in the US, either among columns or among rows. No pattern with respect to the capitalization or to the historical volatility may be exhibited. The ETF did not significantly modify the European equity market (yet?). We can notice that during years with very positive return (2005, 2006, 2009, 2013), high historical volatility stocks tend to outperform significantly, so do small caps. But the difference between “SP” and “B” performances remains very low compared to the US extremes. Regarding the “momentum effect” and the persistence of winners and losers, we find the same pattern as in the US, meaning a quite strong trend-following process, except during big breaches such as what happened in 2008-2009. Therefore, we can suggest to separate the ETF impact and the “low-volatility” puzzle their flows create in the US, and the trend-following process of the market. The latter does not rely on ETF flows, but on the behavioral and cognitive biases of investors. Europe’s equity market remains a territory for stock pickers. Definitely. The ETF impact remains very contained. The only major pattern that can be exhibited is a trend-following aspect of the returns over the years, but nothing relative to capitalization or historical volatility. TOPIX First of all, looking at the beta per couple, we can notice that the higher the capitalization, the higher the beta. This means that lower capitalizations post very dispersed returns with very low correlated returns among a given class, whereas the big caps exhibit very close behaviors among themselves. Performances are well balanced between columns (volatilities) and rows (capitalizations). Using our former notations (“SP”) and (“B”), let’s have a look at the rankings over the years. On the table, we can notice a change of pattern since 2014 (included), with a more European look-alike pattern before and a US look-alike pattern since then. If we add the latter characteristic to the fact that beta depends positively on the capitalization, TOPIX seems to be at the middle of the road between US and Europe in terms of investment philosophy, US being the “new-way” of investing, flow driven, and Europe being the “old-way” of investing, fundamental driven. “Momentum-wise”, except in 2009, where the worst performers of 2008 posted the best performance of years, it is difficult to sort the Japanese market either on the “trend-following” side or on the “mean-reverting”. The TOPIX remains quite difficult to understand, as it is a mix between European patterns and US ones. We can notice that there is no clear “trend-following” or “mean-reverting” process. Large capitalizations seems to be riskier, due to their high-intra correlated pattern, posting a higher beta than small caps, which suffer from highly dispersed returns. Global Conclusion First of all, we noticed over the past 15 years that US stock returns are much more dispersed than Europe or Japanese. We have much more positive and negative extreme outliers in the US. US is definitely not a market for traditional stock pickers, as this market is a flow-driven market. This relies on a structural fact: US people are all interested in stock exchange performances as their retirement relies on the latter. Therefore, the level of knowledge in the US is by far higher than the one in Europe, meaning that all the Americans are stock-exchange investors, providing huge flows, and expecting the same commitment from their financial advisors in term of risk exposure. People are still scared by the 2008 crisis and their come-back in the equity markets relies on a strict risk-management rule. Today, smart-beta ETFs provide the solution, mainly known as “Minimum Variance” or “Equal Risk Contribution”. This is the reason why last year’s rally in US equities is often described as a “defensive” rally. Therefore, flows concentrate on these products encouraging the pattern to pursue. In Europe, the economic knowledge of the population is very low. In addition to that, financial practitioners and financial-related topics are hated. There is no pension funds in Continental Europe. Therefore, the equity market does not depend on huge flows as in the US, and remains the stronghold of some “happy-fews” whose way of thinking relies on fundamentals. Thus, European equity market still reacts on fundamental data and news, as flows are almost insignificant. The question is: until when these patterns may last? Why they may be threatened? In the US, we have been waiting for six years on an “aggressive” rally. It will happen when the couple (“small caps”, “high vol”) will dramatically outperform the couple (“large caps”, “low vol”). It happened in 2009, after the 2008 krach, but this can be analyzed as a kind of “mean-reverting” process on very low levels of valuation. But, today in the US, valuation standards do not exist anymore. An investor just have to think as follows: Where do the flows go? What are the main drivers of the market with metrics such as capitalizations and historical volatilities? We could challenge this vision: how can a low volatility stock perform a high volatility stock? Because low volatility stocks exhibit positive volatility (volatility on upside moves) and a smooth pattern, whereas high volatility stocks exhibit negative volatility (volatility on downside moves) and jumpy charts. Thus, the question is: given such matter of fact, is the stock exchange the best place for a start-up to raise money? Isn’t Private Equity a better shelter, and just wait to get a decent size or a decent brand-famousness (as Alibaba (NYSE: BABA ) or Uber (Pending: UBER )) to go listed? In Europe, while the money is still in the hands of the 50+ old generations, we will keep this fundamental-driven market. Recently, we noticed the emergence of Fintech actors in Europe, with 40 founders. This 40 generation is interested in stock exchange and portfolio management. When these guys will take the money of the elders, and given the difficulty of savings system in Europe, pension funds are likely to develop dramatically. Therefore, we can assume that today’s US pattern will cross the Atlantic. Thus, when this happens, it will be time to focus on large caps, low volatility names such as the Swiss. Japan is very difficult to understand. It seems to be a merge of Europe and US, but the trend tends towards a more US look-alike market, with stock-picking that is likely to become more and more difficult. In addition to these areas, type of investors – related pattern – there is a “momentum effect” that tends to be persistent. “Winners remains the winners, losers the losers”, same as for good and bad pupils. This stresses the “trend-following” pattern of the equity market, whatever be US, European or Japanese, with a kind of performance clustering over the years, as we can notice about volatility: period of good performance tends to be followed by good performance again. Stock pickers should focus on Europe, and systematic or factor-based investors on the US. Should you want to pick up stocks in the US, first select quantitatively a universe with capitalization and historical volatility factors. It is likely to enhance significantly the performance of this “conditional” stock-picking, and avoid large losses. Moreover, keep in mind that today, fund holders have access to financial information instantaneously, so do the asset managers. There is no more information asymmetry. Information is now the same for everybody, professional and not professional. This means that finance has changed a lot: 30 years ago, the fund holder used to receive information about his funds two times per year. Now, it happens everyday. Therefore, his psychological risk-budget – which has not increased – is filled by far more quickly. The consequence? Implicitly, unconsciously, this phenomenon has dramatically reduced the holding period of the fund by the fund holder. Therefore, risk-management has – now more than ever – to be taken into account ex ante in the asset management process – and not ex post, as it can be seen too often in the French AM industry. Smart risk management is as important as finding equity ideas to generate alpha. It is a way to avoid negative alpha and then create added value for the fund holder. The other requirement is to know and understand the market you invest in. This is the aim of this article: it is not the same to know the companies you invest in (analyst), and to know the market you invest in (asset manager).

401(k) Fund Spotlight: Janus Triton

Summary Janus Triton is a small to mid capitalization growth stock fund. Triton has consistently beaten the Russell small capitalization growth indexes, but not the higher quality S&P 600 Small Cap indexes. Triton is overweight the technology sector, which comprises about 31% of the fund. A look at some of the fund’s largest technology holdings reveal the manager is true to the fund’s promise of investing in companies with “differentiated business models”. Introduction I select funds on behalf of my investment advisory clients in many different defined contribution plans, namely 401(k)s and 403(b)s. I have looked at a lot of different funds over the years. 401(k) Fund Spotlight is an article series that focuses on one particular fund at a time that is widely offered to Americans in their 401(k) plans. 401(k)s are now the foundational retirement savings vehicle for many Americans. They should be maximized to the fullest extent. A detailed understanding of fund options is a worthwhile endeavor. To get the most out of this article, it is helpful to understand my approach to investing in 401(k)s . I strive to write these articles for the benefit of the novice and professional. Please comment if you have a question. I always try to give substantive responses. Janus Triton Fund The Janus Triton Fund has the following share classes: I will assume the “T” shares for this article, since that is the share class that holds the most assets of the fund. It is also the primary share class used by Janus to evaluate historical calendar year returns. The net expense ratio for the T shares is .93. Evaluating Historical Performance Triton is a small/mid capitalization (“cap”) growth fund. Janus compares the fund’s historical performance to the Russell 2000® Growth Index and the Russell 2500™ Growth Index and it comes out favorably, as shown on the following table: as of September 30, 2015 1 Year 3 Year 5 Year 10 Year Janus Triton – T Shares 5.1% 14.2% 14.1% 11.4% Russell 2500™ Growth Index 3.4% 13.8% 13.9% 8.4% Triton Outperformance (Underperformance) 1.7% .4% .2% 3.0% Russell 2000® Growth Index 4.0% 12.9% 13.3% 7.7% Triton Outperformance (Underperformance) 1.1% 1.3% .8% 3.7% Triton has outperformed both growth benchmarks over all four of these time periods. Most notably, Triton’s outperformance in the important (for long term investors at least) 10-year category ranged from 3.0% to 3.7%. This particular 10-year period is also noteworthy, because it included one of the worst bear markets in U.S. stock market history. However, taking a step back, it is important to ask the question: “Are the Russell indexes the best for comparison?” Perhaps they are if your fund is always outperforming them. There are other widely used small cap indexes from S&P that have outperformed the Russell small cap indexes over time. (This article explains the difference between the two.) The S&P Small 600 Index tends to hold a bit higher quality stocks. For example, it requires index members to have at least four consecutive quarters of positive earnings. I drew up a chart of Triton versus the SPDR S&P Small Cap 600 Index ETF (NYSEARCA: SLY ) and the SPDR S&P Small Cap Growth Index ETF (NYSEARCA: SLYG ) since March 1, 2009 (arguably the approximate date of the current secular bull market). Here is what it looks like: JATTX Total Return Price data by YCharts A:JGMAX C:JGMCX I:JSMGX N:JGMNX S:JGMIX R:JGMRX T:JATTX Out of the three, the SPDR S&P Small Cap 600 Growth Index ETF was the winner, but only slightly. Overall, I think it could be said that all three have pretty much been running neck and neck throughout this bull market. According to Barrons , Triton has outperformed 89% of its peers, as measured by the Lipper Small Cap Growth Index, over the last five years. I think the fact that it beat such a large percentage of its peers, but still trailed the S&P Small Cap 600 Growth Index ETF during this bull market, really speaks to the quality of the S&P Small Cap 600 indexes. Overall, the fund has a solid performance track record. If available in a 401(k), I would likely choose either of the similar S&P Small Cap 600 Indexes though instead. The index gives you a lower expense ratio, so you have a slight advantage right out of the gate. Triton, like so many other mutual funds, is so widely diversified that it really cannot stray to far from the index as long as it remains fully invested. The problem is not so much that the fund holds 120 different stocks, it is that there are only four stocks that comprise more than 2% of the fund each. Other Noteworthy Tidbits Triton does have a substantially overweight position in information technology (31% of the fund as of October 31, 2015) compared to the Russell 2500 ™ Growth Index’s (21%). The fund may present a good angle for investors interested in having more exposure to the sector without going overboard. However, the overall fund has a forward Price to Earnings (“P/E”) multiple of 24, which is very high. I suspect that some of the information technology stocks it holds are widely overvalued. Let us dig a little deeper. The industries the fund has most exposure to are Software (12% of fund) and Information Technology Services (9%). The following table lists the fund’s largest holdings within these two sectors and their trailing twelve month (“TTM”) and forward looking P/E multiples (taken from Yahoo! Finance). Company P/E Multiple (Last 12 Months) Forward P/E Multiple SS&C Technologies Holdings ( SSNC ) 98 22 BlackBaud ( BLKB ) 121 36 Cadence Design Systems ( CDNS ) 30 19 Euronet Worldwide ( EEFT ) 44 22 Broadridge Financial Solutions ( BR ) 24 18 Jack Henry & Associates ( JKHY ) 30 26 I tend to focus on forward looking multiples and most of these are too high for my liking, although I was a bit off on my speculation of wild overvaluation. They are not in the extreme territory of some overplayed growth stocks. Janus states in the Triton fund description that: “The Fund invests in small-cap companies with differentiated business models and sustainable competitive advantages that are positioned to grow market share regardless of economic conditions.” Glancing at the business descriptions of just these six companies leads me to believe that Triton’s manager is following through on this promise. These companies strike me as those that are not going away anytime soon and could continue to experience solid growth in their niches (e.g., payment processing for small financial institutions and designing web solutions for non-profits). Conclusion The Janus Triton Fund is a solid option for 401(k) investors looking to get exposure to small/mid cap growth stocks. I would not choose the fund over the S&P Small Cap 600 Growth Index, but that is rarely a choice. Triton has consistently beaten the comparable Russell growth indexes and most of its peers. I would likely choose it, or at least give it a higher allocation, than other such available options. Investing Disclosure 401(k) Spotlight articles focus on the specific attributes of mutual funds that are widely available to Americans within employer provided defined contribution plans. Fund recommendations are general in nature and not geared towards any specific reader. Fund positioning should be considered as part of a comprehensive asset allocation strategy, based upon the financial situation, investment objectives, and particular needs of the investor. Readers are encouraged to obtain experienced, professional advice. Important Regulatory Disclosures I am a Registered Investment Advisor in the State of Pennsylvania. I screen electronic communications from prospective clients in other states to ensure that I do not communicate directly with any prospect in another state where I have not met the registration requirements or do not have an applicable exemption. Positive comments made regarding this article should not be construed by readers to be an endorsement of my abilities to act as an investment adviser.