Determinants of Mutual Fund Performance Persistence: A Cross-Sector Analysis * Aneel Keswani. David Stolin

Transcription

1 Determinants of Mutual Fund Performance Persistence: A Cross-Sector Analysis * Aneel Keswani Cass Business School 106 Bunhill Row London EC1Y 8TZ UK Phone: (+44) , Fax: (+44) A.Keswani@city.ac.uk David Stolin Toulouse Business School 20, bd Lascrosses Toulouse France Phone: (+33) , Fax: (+33) d.stolin@esc-toulouse.fr February 2004 * We would like to thank Vladimir Atanasov, Kenneth Moon and an anonymous referee for helpful comments. We also acknowledge the comments received from participants at the 2003 FMA meeting, and seminars at Warwick and Cass Business School. Thanks are also due to Rebecca Smith, Jan Steinberg, James Sullivan, the Allenbridge Group, and the Investment Management Association for help with data. All errors and omissions are ours.

2 Determinants of Mutual Fund Performance Persistence: A Cross-Sector Analysis Abstract In this paper we examine the nature of performance persistence across sectors of the UK open-ended managed funds industry. Existing UK persistence studies focus on sectors that invest primarily in UK equities. We find that there are significant differences in the level of observed persistence across all sectors. These are most marked between sectors that are restricted to UK equities and those that are not. We also seek to explain why persistence levels differ across sectors by drawing on recent theoretical work that has highlighted that sector competitiveness may influence levels of persistence. We find limited evidence that sector properties that proxy for sector level competitiveness explain the cross sectional behaviour of persistence. We therefore conclude that it is differences in the securities invested in between sectors that cause differences in the observed level of persistence. Keywords: mutual funds; performance persistence JEL classification: G23 2

3 1. Introduction Mutual funds are managed pools of financial assets that can be invested in by retail or institutional investors. Funds can be classified into sectors on the basis of the securities they invest in. These sectors then become a natural peer group within which funds compete and against whom external bodies typically assess performance. Knowing whether there is persistence in mutual fund performance is of concern both to investors and to fund managers. The existence of performance persistence tells us whether fund managers add value and whether past fund performance information should be taken into account by investors when making their investment decisions. The literature on performance persistence is extensive. 1 One question that has not been asked to date is whether past performance information is equally useful for predicting fund performance across different sectors. Knowing whether this is the case could be of interest to those on both the demand and supply side of the fund management industry. We would expect some investors to use such information to focus their investments in sectors where past returns are more useful in predicting performance. On the supply side, fund families might choose to open new funds in sectors where they have a greater 1 See e.g. Hendricks, Patel and Zeckhauser (1992), Brown and Goetzmann (1995), Carhart (1997), Carpenter and Lynch (1999), and Carhart et al (2002). 3

4 chance to do persistently better than other funds (or shun such sectors for fear of doing persistently worse). 2 In order to answer the question of whether performance persistence differs between sectors we use data from the UK open ended managed funds (unit trust) industry. The advantage of working with UK data is that in the UK there is a dominant system for classifying funds into sectors. 3 This is determined and enforced by the Investment Management Association (IMA). 4 This means that there exists a consensus about a given fund s set of competitors. This allows us to test for cross sector differences in persistence cleanly. Whether there is persistence in the UK open-ended managed funds industry has been discussed by practitioners and academics in a recent lively debate. Papers that have contributed to this debate include Blake and Timmermann (1998, 2003), Rhodes (2000), Quigley and Sinquefield (2000), Fletcher and Forbes (2002), and Giles et al. (2002a,2002b). Interestingly the fund industry regulator in the UK considered at one point banning fund advertisements containing past performance information (Financial 2 Nanda, Wang, Zheng (2004) discuss the impact on the flows to a fund family of having a star fund. They find that having such a star fund has a positive spillover effect on a family s funds outside the sector that the star fund is in. 3 By contrast, in the US, there is a proliferation of methods for assigning funds to a peer group, depending on the investment advisor (Morningstar, Wiesenberger, Lipper, each use their own groupings). Interestingly, Morningstar decided in June 2002 to use much narrower group definitions and work with 48 different investment styles rather than the four broad groups it used previously. This change appears to indicate the growing prominence of peer group rankings for US funds. 4 The IMA monitors fund positions. If the holdings of a fund contravene the allocation rules of the sector a fund is in the IMA will warn the fund that it risks being moved into a new sector. Our conversations with the IMA indicate to us that funds typically do alter their positions to adhere to sector classifications and that there have been occasions where the IMA has had to remove a fund from a sector because it did not respond to the IMA s request that it alter its asset allocation. 4

5 Services Authority, 2001). All existing studies of UK performance persistence to date have focused on sectors where funds invest primarily in UK equities. By examining sectors where funds are not restricted to UK equities we are able to test whether existing results concerning performance persistence carry over from the UK equities sectors to other sectors as well (over our sample period the asset share of these sectors grew from 40% to 52% of the unit trust industry). Looking at performance persistence across different fund sectors also allows us to test what determines persistence differences between sectors. Recent work by Berk and Green (2002) has highlighted the role of competition in eliminating persistence in returns. If this is the case we would expect to see a link between levels of sector persistence and characteristics that measure sector competitiveness. We test whether variables that proxy for the competitiveness of a sector are able to explain differential persistence. We find that there are significant differences in the level of persistence across all sectors with the most marked observed differences occurring between sectors that are restricted to UK equities and those that are not. In addition we find limited evidence that sector properties explain the cross sectional behaviour of persistence. We therefore conclude that it is differences in the securities invested in between sectors that cause differences in the observed level of persistence. 5

6 2. Literature and theory There are a number of possible explanations why performance persistence might be detected when the past performance of a sample of managed funds is analysed. Detected persistence might be the result of some managers having superior (poor) stock selection ability and timing ability. 5 In addition persistence might be the result of assetlevel momentum or style-level momentum. 6 It also could be the result of using a sample of funds where funds that cease to exist during the observation window are excluded. 7 There exists a large body of research that has looked at whether open ended fund performance persists. Initial work focused on managed funds within the American context. More recent work has also considered these issues in the UK and other countries. 8 The results of studies that look at whether performance persistence exists are not conclusive. Looking at US funds, papers such as Elton, Gruber and Blake (1996) and Bollen and Busse (2002) find evidence of risk adjusted persistence while Teo and Woo (2003) find evidence of style adjusted persistence. On the other hand, papers such as Carhart (1997) and Phelps and Detzel (1997) find no evidence of persistence. 5 Timing ability refers to the ability of fund managers to alter their investment style to pick the style that maximises the current (adjusted) return. 6 Barberis and Schleifer (2003) discuss the impact of style investing on asset price behaviour and fund behaviour. Davis (2001) finds evidence of performance persistence differing across investment styles. 7 Brown and Goetzmann (1995) explain how using a panel of firms that contains survivorship bias may lead to performance persistence being detected. 6

7 UK studies have been no more conclusive. While Allen and Tan (1999), Blake and Timmermann (1998) and Quigley and Sinquefield find clear evidence of persistence, Fletcher and Forbes (2002) and Rhodes (2000) do not. The existing literature has analysed funds that invest in either domestic equity or a mix of domestic equity and bonds and few papers have considered pure bond funds and international bond or equity funds. 9 Our study considers sectors that invest outside of UK equities. By doing so we hope to not only understand whether persistence is materially different outside of the UK equity sectors but also to contribute to the existing debate on UK performance persistence. While a number of papers have noted that performance persistence differs across sectors, no empirical work has been done to explain why. While papers such as Kosowski et al. (2001), Wermers (2003) and Blake and Timmermann (1998) do discuss differential persistence between fund sectors they do not perform statistical tests. 10 Why should we expect persistence to differ across sectors? Market efficiency predicts that in the long run performance persistence should disappear. 8 Six studies have examined performance persistence in the UK: Blake and Timmermann (1998), Allen and Tan (1999), Fletcher and Forbes (2002), Giles et al. (2002b), Quigley and Sinquefield (2000) and Rhodes (2000). 9 Blake, Elton and Gruber (1993) examine the persistence of performance of bond mutual funds. 10 Wermers (2003) finds that levels of persistence differ between US based value-oriented and growthoriented funds while Kosowski et al. (2001) using US data also find that growth-oriented funds exhibit much stronger abilities in picking stocks that beat their benchmark than value oriented funds. 7

8 Consistent outperformance by a fund advertises the potential opportunities for active fund management within its sector. As a result, the fund may face intensified competition for these opportunities from new and existing funds seeking to emulate its success. In addition, new investors will be attracted to the fund. Recent work by Berk and Green (2002) has suggested that funds that perform well will grow to the point where outperformance is no longer possible because of decreasing returns to scale. 11 These mechanisms that drive out performance persistence suggest that the competitive environment of a sector is what is important in determining its level of persistence. They also suggest a number of factors that might explain the cross sectional pattern of observed persistence. 12 For example, lower fund size concentration within a sector should lead to more competition and less persistence. As regards sector size, if this is large relative to the set of securities available for investment then there should be lower scope for consistent outperformance. Sector maturity may also play a role as competitive mechanisms will have acted over a longer period, resulting in lower level of persistence. 11 Berk and Green (2002) convincingly make the argument that decreasing returns to scale must exist in fund management. They argue that, in the presence of managerial ability differences, if marginal returns did not diminish as fund sizes grew, all funds would flow to the most able fund manager. Chen et al. (2003) document that US fund returns decline with lagged fund size both using raw and risk adjusted returns. 12 Waring (1996) seeks to explain why certain industries have highly persistent differences in profitability between their firms while other industries have little persistence in firm-specific rents. Using variables that proxy for industry competitiveness he seeks to explain cross sectional differences in observed persistence. 8

9 3. Data and Methodology UK unit trusts are ideal for studying persistence within peer groups. In contrast to the US, where many different investment advisors assign funds to categories in their own way, 13 in the UK there is a dominant system, determined by the Investment Management Association (IMA) 14 for assigning funds to peer groups. IMA s sector definitions and assignment of funds to sectors are followed by virtually all investment services providers. 15 [Table 2 here] Our data set consists of net annual returns on all UK unit trusts over the period. Fund size and sector membership information were also collected. The source of the data is historical issues of Money Management magazine containing a comprehensive list of funds in existence. Our data set therefore has no survivorship bias. Table 2 shows the evolution of sector membership. In addition, it shows whether sector membership is restricted to funds which invest in domestic securities only, and whether it is restricted to funds which invest in equities only. It can be seen that the number of funds varies greatly across sectors, and it also evolves within sectors over time. Further, sector definitions themselves evolve. 13 In the US, there is a proliferation of methods for assigning funds to a peer group, depending on the investment advisor (Morningstar, Wiesenberger, Lipper, each use their own groupings). 14 The Investment Management Association was formed in 2002 through a merger of the Association of Unit Trusts and Investment Funds (AUTIF) and the Fund Managers Association (FMA). Fund sectors were formerly defined by AUTIF. 15 Investment services providers such as Standard & Poor s ( Allenbridge ( and Hemscott ( all use IMA s classification system. 9

10 Performance persistence can be measured using both absolute and relative performance. We measure persistence in this paper using relative performance for two reasons. First, existing research has highlighted that relative fund performance matters for determining fund flows above and beyond absolute performance. 16 In addition, measures of absolute performance persistence may depend e.g. on the volatility of securities invested in by a given sector making comparisons of absolute persistence across sectors misleading. In order to determine relative performance we use raw and not risk adjusted returns. Well accepted benchmarks exist for UK equity sectors which would allow us to risk adjust returns for these sectors better than for other sectors. If one believes that risk adjustment has an impact on measured persistence then it is quite possible that the quality of benchmarks would have an impact on detected persistence. This explains why existing papers on the UK managed funds sector that look at risk adjusted performance persistence focus on UK equity sector funds. As we are interested in examining persistence across not just UK equity sectors and do not wish risk adjustment to affect measured differences in persistence we use raw and not risk adjusted returns. There are two reasons why using raw returns may be appropriate for our purposes. First, while investors should care about alphas, evidence on the returns-flow relationship indicates that they do, in fact, care about raw returns as well. Second, numerous 10

11 information providers such as Money Management magazine, Unit Trust Yearbook, Standard and Poor s website and others rank funds based on raw return within a sector. Common statistics for studying relative persistence within a peer group include the Spearman rank correlation coefficient and the log-odds ratio for a two-by-two winner/loser contingency table. We therefore use these variables (henceforth SCORR and LOGODDS, respectively), calculated based on raw performance over successive calendar years, as our measures of sector-level persistence. In order to make these measures comparable across sectors with different numbers of funds, we additionally use the t-statistic for Spearman correlation (SCORR_T) and the Z-statistic for the logodds ratio (LOGODDS_Z) which for sufficiently large sample sizes has the effect of normalizing these statistics. To avoid our results being influenced by the small sample properties of Spearman correlation and the log-odds ratio, we only include sectors-years with at least 20 funds in existence over both years over which performance is measured. 4. Results [Table 3 here] Table 3 summarizes our persistence statistics across sectors and years. For UK equity sectors, the average Spearman correlation is and highly statistically significant as is the Spearman correlation t-statistic (1.641), as well as the log-odds ratio (0.518) 16 Sirri and Tufano (1998) and Chevalier and Ellison (1997) make this point by highlighting the importance of relative performance in determining fund flows. Loranth and Sciubba (2002) quote a fund manager 11

12 and its Z-statistic (1.192). This confirms the presence of persistence in raw returns. For comparison, the average log-odds ratio based on raw annual returns as reported by Fletcher and Forbes (2002) for UK equity unit trusts over is 0.516, and the associated Z-statistic Similarly, Allen and Tan (1999) find that the mean Spearman correlation coefficient based on raw annual returns is over Thus our estimates are consistent with comparable estimates in the literature. These last results simply confirm the findings of several recent UK studies that work with UK equity sectors. The unit trust literature had not, however, examined persistence in sectors other than UK equity. As Table 3 shows, these sectors exhibit a level of persistence which is significantly positive. However, its level is detectably lower than for UK equity sectors and the average Spearman correlation drops to 0.064, which is significantly different from zero at the 5% level, but also significantly different from the average correlation for UK equity sectors; the behavior of the log-odds ratio is similar. The normalized versions of these statistics, SCORR_T and LOGODDS_Z which provide us with more powerful tests, result in even lower p-values for differences from both UK equity results and from the null of no persistence. We can therefore conclude that the unit trust sectors examined in the literature to date are characterized by a greater level of relative persistence in raw returns than the unit trust industry as a whole. 17 [Table 4 here] making this point. 12

13 This last finding raises the question of the explanation for this marked difference. Broadly speaking, the difference may be due either to the nature of securities in which the sector funds invest, or to the organization of the sector itself. Our data do not allow us to examine the former possibility, and we therefore focus on the latter. A glance at Table 2 indicates that UK equity sectors are more populous than other sectors. There are other differences, too. Panel A of Table 4 shows, by sector category, additional characteristics including sector relative size (RELSIZE, sector assets as a proportion of total unit trust assets at the time) and the Herfindahl concentration index of fund assets (HERFINDAHL). UK equity sectors are characterized by a much greater number of funds (109 as opposed to 59), greater size (0.113 versus 0.036) and less concentration (0.036 versus 0.077). All of these differences are statistically significant at the 1% level. Panel B of Table 4 contains a correlation matrix for these variables and for a dummy variable indicating sector membership in the UK equity category (UK_EQUITY), as well as a dummy variable taking on the value of one for the second half ( ) of our time period, and zero otherwise (LATER). These correlations confirm the results of Panel A regarding the association of the sector objective with its organization, and they also show that sector characteristics do not appear to have changed over time (correlations with LATER are never significant). If size, the number of funds or (the inverse of) concentration are regarded as representing the level of competition among 17 We also examined whether UK equity sectors share this elevated persistence with UK non-equity sectors, or perhaps with non-uk equity sectors. We found that they do not. 13

14 funds in a sector, one may expect these variables to take on lower values when the level of persistence is higher. Yet, if anything, the opposite appears to be the case here. [Table 5 here] To disentangle the possible contributions of individual sector-level variables to persistence, Table 5 reports results of twelve regressions of our persistence measures on different sets of sector-year characteristics. Regression (1) shows membership in the UK equity category is associated with a significant increase in Spearman correlation coefficient (recall that the average value of the same coefficient for UK equity sectors is 0.153), while RELSIZE, HERFINDAHL, and LATER are not significant (significance levels are based on White heteroscedastity adjusted standard errors). Regression (2) shows that the number of funds in a sector does not have a significant effect on its persistence either. Regression (3) introduces a further control variable, CROSSRET. This variable represents the product of average returns for sector funds in the two years over which persistence is examined. While we do not adjust for differences in fund exposure to different risk factors, these differences can generate persistence in raw returns when there is persistence in factor realizations. Thus when a sector as a whole experiences momentum, one can expect greater persistence based on raw returns. The positive and highly significant coefficient on CROSSRET captures this effect. However, our main results remain the same in that UK_EQUITY is positive and significant, and the remaining variables are insignificant. Regressions (4)-(6), (7-9) and (10)-(12) show the above results to be robust to measuring persistence instead with SCORR_T, LOGODDS, and LOGODDS_Z, respectively. Furthermore, in unreported 14

15 regressions, we also introduced individual year dummies as independent variables. This did not qualitatively change the results. [Table 6 here] As a check on the robustness of our pooled regression results, we implemented a Fama-Macbeth procedure, whereby coefficients from annual cross-sectional regressions are averaged across the years and statistical significance is determined based on the time-series standard deviation of coefficient estimates. These results are reported in Table 6, and are fully consistent with the earlier findings. UK_EQUITY is always positive and significant, while N, RELSIZE, HERFINDAHL and LATER are not. Overall, we have documented that there exists a difference in persistence between sectors invested in UK equities and remaining sectors, and that this difference is not explained by other sector characteristics. 5. Conclusion The UK unit trust industry is particularly amenable to a study of sector-level persistence, as it is characterized by well-defined and commonly used sectors. All work to date on UK fund persistence has focused on just a handful of these sectors that invest primarily in UK equities. 15

16 Using survivorship bias free data between 1991 and 2001, we investigate the nature of relative performance persistence in the remaining sectors and compare it with the persistence of the UK equity sectors. We find that persistence levels of UK equity sectors are statistically significantly higher than persistence levels of other sectors not restricted to investing in UK equities. This seems to indicate that by omitting sectors that invest outside UK equities, studies may be missing important information if their aim is to reach meaningful conclusions about the level of persistence in the overall managed funds sector. Our finding also raises the question as to whether the conclusions of US persistence studies, which also mainly examine domestic equities, would hold for other fund categories. Our analysis also allows us to test the determinants of persistence across managed fund sectors. We examine whether variables that proxy for sector competitiveness are useful for explaining persistence differences. We find that this is not the case. This suggests that persistence differences are the result of differences in the underlying securities that a sector invests in. 16

17 References Allen, D. E. and M. L. Tan, 1999, A test of the persistence in the performance of UK managed funds, Journal of Business Finance and Accounting 26, Barberis, Nicholas and Andrei Schleifer, 2003, Style Investing, Journal of Financial Economics, 68, Berk, Jonathan B. and Richard C. Green, 2002, Mutual fund flows and performance in rational markets, NBER Working Paper 9275 Bollen, Nicolas P. B. and Jeffrey A. Busse, 2002, Short-term persistence in mutual fund performance, Working Paper, Vanderbilt University. Blake, Christopher R., Edwin J. Elton and Martin J. Gruber, 1993, The performance of bond mutual funds, Journal of Business, 66(3), Blake, David, and Allan Timmermann, 1998, Mutual fund performance: Evidence from the UK, European Finance Review 2, Blake, David and Allan Timmermann, 2003, Performance persistence in mutual funds: An independent assessment of the studies prepared by Charles River Associates for the Investment Management Association, Report commissioned by the Financial Services Authority 17

18 Brown, Stephen J., and William N. Goetzmann, 1995, Performance persistence, Journal of Finance 50, Carhart, Mark M., 1997, On persistence in mutual fund performance, Journal of Finance 52, Carhart, Mark M., Jennifer N. Carpenter, Anthony W. Lynch, and David K. Musto, 2002, Mutual Fund Survivorship, Review of Financial Studies 15, Carpenter, Jennifer N., and Anthony W. Lynch, 1999, Survivorship bias and attrition effects in measures of performance persistence, Journal of Financial Economics 54, Chen, Joseph, Harrison Hong, Ming Huang and Jeffrey Kubik, 2003, Does Fund Size Erode Mutual fund Performance? The Role of Liquidity and organization, Working paper, Stanford University. Chevalier, Judith, and Glenn Ellison, 1997, Risk taking by mutual funds as a response to incentives, Journal of Political Economy 105, Davis, James L., 2001, Mutual fund performance and manager style, Financial Analysts Journal, January/February,

19 Elton, Edwin G., Martin Gruber and Christopher R. Blake, 1996, The persistence of riskadjusted mutual fund performance, Journal of Business, 69, Financial Services Authority, 2001, Report of the Task Force on Past Performance Giles, Tim, Tim Wilsdon and Tim Worboys, 2002a, Performance persistence in UK equity funds a literature review, Report prepared by Charles River Associates for the Association of Unit Trust and Investment Funds Giles, Tim, Tim Wilsdon and Tim Worboys, 2002b, Performance persistence in UK equity funds an empirical analysis, Report prepared by Charles River Associates for the Association of Unit Trust and Investment Funds Hallahan, Terrence A. and Robert W. Faff, 2001, Induced persistence or reversal in fund performance? The effect of survivorship bias, Applied Financial Economics 11, Hendricks, Daryll, Jayendu Patel, and Richard Zeckhauser, 1993, Hot hands in mutual funds: Short-run persistence of performance, Journal of Finance 48, Hulbert, Mark, 2002, A ratings tweak for Morningstar, International Herald Tribune, May 18 Ibbotson, Roger and Amita Patel, 2002, Do winners repeat with style?, Working Paper, Yale ICF Working Paper No

20 Kosowski, Robert, Allan Timmermann, Hal White and Russ Wermers, 2001, Can mutual fund "stars" really pick stocks? New evidence from a bootstrap analysis, Working Paper, London School of Economics. Loranth, Gyongyi and Emanuela Sciubba, 2002, Relative Performance, Risk and Entry in the Mutual Fund Industry, Working Paper, University of Cambridge Nanda, Vikram, Z. Jay Wang and Lu Zheng, 2004, Family values and the star phenomenon, Review of Financial Studies, Forthcoming. Phelps, S. and L. Detzel, 1997, The Non persistence of Mutual Fund Performance, Quarterly Journal of Business, Finance and Economics 36, Quigley, Garrett and Rex Sinquefield, 2000, Performance of UK Equity Unit Trusts, Journal of Asset Management, Vol 1(1), Rhodes, Mark, 2000, Past imperfect? The performance of UK equity managed funds, Financial Services Authority Occasional Paper No. 9 Sirri, Erik R. and Peter Tufano, 1998, Costly search and mutual fund flows, Journal of Finance 53,

21 Teo, Melvyn and Sung-Jun Woo, 2001, Persistence in style-adjusted mutual fund returns, Working Paper, Harvard University. Waring, Geoffrey F., 1996, Industry differences in the persistence of firm-specific returns, American Economic Review, 86(5), Wermers, Russ, 2003, Is money really smart? New evidence on the relation between mutual fund flows, manager behavior, and performance persistence, Working Paper, University of Maryland. 21

22 Table 1. Unit trust persistence studies Study Data Sectors(Number) Persistence Detected In Raw Returns Risk Adjusted Returns Allen and Tan (1999) UK Not stated Yes Yes Blake and Timmermann (1998) UK Domestic equity and balanced (5) Yes Yes Fletcher and Forbes (2002) UK Domestic equity (3) Yes Yes/No a Giles et al (2002b) UK Domestic equity and balanced (4) Yes Not examined Quigley and Sinquefield (2000) UK Domestic equity (4) Yes Yes Rhodes (2000) UK Domestic equity (4) Yes/No b Not examined a depending on the type of risk adjustment b depending on the time period examined 22

23 Table 2. Unit trust sectors INVESTMENTS LIMITED TO NUMBER OF FUNDS IN YEAR SECTOR NAME UK EQUITIES ACTIVE MANAGED NO NO AUSTRALASIA NO YES BALANCED MANAGED NO NO CAUTIOUS MANAGED NO NO COMMODITY AND ENERGY NO NO CONVERTIBLES NO NO EMERGING MARKETS NO YES EUROPE NO YES EUROPE EXCLUDING UK NO YES EUROPE INCLUDING UK NO YES EUROPEAN SMALLER COMPANIES NO YES EUROPEAN SPECIALIST NO YES 21 FAR EAST EXCLUDING JAPAN NO YES FAR EAST INCLUDING JAPAN NO YES FAR EAST SPECIALIST NO YES 11 FINANCIAL AND PROPERTY NO NO FUND OF FUNDS NO NO FUTURES AND OPTIONS NO NO GILT AND FIXED INCOME YES NO GLOBAL BOND NO NO GLOBAL EQUITY AND BOND NO NO GLOBAL EQUITY INCOME NO YES GLOBAL GROWTH NO YES GLOBAL SPECIALIST NO NO 34 GUARANTEED/PROTECTED NO NO INDEX BEAR NO NO INTERNATIONAL BALANCED NO NO INTERNATIONAL EQUITY AND BOND NO NO INTERNATIONAL EQUITY INCOME NO YES INTERNATIONAL FIXED INCOME NO NO INTERNATIONAL GROWTH NO YES INVESTMENT TRUST UNITS NO NO JAPAN NO YES JAPANESE SMALLER COMPANIES NO YES LATIN AMERICA NO YES 10 MANAGED NO NO 45 MANAGED INCOME NO NO MONEY MARKET NO NO NORTH AMERICA YES YES NORTH AMERICAN SMALLER COMPANIES NO YES NORTH AMERICAN SPECIALIST NO YES 22 PROPERTY YES NO SPECIALIST NO NO 61 TECHNOLOGY AND TELECOMS NO YES 28 UK ALL COMPANIES YES YES UK BALANCED YES NO UK CORPORATE BOND YES NO UK EQUITY AND BOND YES NO UK EQUITY AND BOND INCOME YES NO UK EQUITY GROWTH YES YES UK EQUITY INCOME YES YES UK FIXED INTEREST YES NO UK GENERAL YES YES UK GENERAL BONDS YES NO 90 UK GILT YES NO UK GILT AND FIXED INTEREST YES NO 106 UK GROWTH AND INCOME YES YES UK OTHER BOND YES NO UK SMALLER COMPANIES YES YES UK SPECIALIST YES YES 18 TOTAL

24 Table 3. Relative persistence across sectors UK Equities sectors Other sectors (not restricted to UK Equities) (47 sector-years) (119 sector-years) Difference Variable Mean p-value Median Min Max Mean p-value Median Min Max Mean p-value SCORR SCORR_T LOGODDS LOGODDS_Z This table reports desriptive statistics for the following measures of persistence: SCORR (the Spearman correlation coefficient), SCORR_T (its t-value), LOGODDS (the log-odds ratio) and LOGODDS_Z (its Z-statistic). Persistence statistics are based on raw (not risk adjusted) annual returns in consecutive calendar years. Only sector-years with 20 or more funds were included. P-values are based on a t-test. 24

25 Table 4. Descriptive statistics for sector-level variables Panel A. Moments UK Equities sectors Other sectors (not restricted to UK Equities) (47 sector-years) (119 sector-years) Difference Variable Mean St. Dev Median Min Max Mean St. Dev Median Min Max Mean p-value N RELSIZE HERFINDAHL Panel B. Correlations N RELSIZE HERFINDAHL LATER UK_EQUITY *** *** *** N *** *** RELSIZE *** HERFINDAHL Panel A characterizes the distribution of sector-year variables. N is the number of funds within a sector, RELSIZE is the ratio of fund assets within a sector to fund assets across all unit trust sectors. HERFINDAHL is the Herfindahl index of concentration of fund sizes within a sector. Panel B shows correlations among sector-year variables. Additional variables include UK_EQUITY (a dummy equal to one if sector funds are restricted to UK equities, and zero otherwise) and LATER (a dummy equal to one for years and zero for ). *, **, and *** denote significance at the ten, five, and one percent levels, respectively. 25

26 Table 5. Explaining sector-level persistence Panel A. Explaining sector-level rank correlation Variable Dependent variable is SCORR Dependent variable is SCORR_T (1) (2) (3) (4) (5) (6) INTERCEPT UK_EQUITY ** * * ** * ** N RELSIZE HERFINDAHL LATER CROSSRET *** *** R-squared Panel B. Explaining sector-level odds ratio Dependent variable is LOGODDS Dependent variable is LOGODDS_Z (7) (8) (9) (10) (11) (12) INTERCEPT UK_EQUITY *** ** ** *** ** ** N RELSIZE HERFINDAHL LATER CROSSRET *** *** R-squared This table reports results of pooled regressions of sector-year persistence measures on sector-year characteristics. The persistence measures used are SCORR (the Spearman correlation coefficient), SCORR_T (its t-value), LOGODDS (the log-odds ratio) and LOGODDS_Z (its Z-statistic). Persistence measures are based on raw (not risk adjusted) annual returns in consecutive calendar years. Only sector-years with 20 or more funds were included. Independent variables are as follows. UK_EQUITY is a dummy equal to one if sector funds are restricted to UK equities, and zero otherwise. N is the number of funds within a sector. RELSIZE is the ratio of fund assets within a sector to fund assets across all unit trust sectors. HERFINDAHL is the Herfindahl index of concentration of fund sizes within a sector. LATER is a dummy equal to one for years and zero for ). CROSSRET is the product of average returns for sector funds in the two years over which persistence is examined. *, **, and *** denote significance at the ten, five, and one percent levels, respectively. Significance levels are based on heteroscedasticityconsistent standard errors. 26

27 Table 6. Explaining sector-level persistence (average coefficients of cross-sectional regressions) Panel A: Explaining sector-level rank correlation Variable Dependent variable is SCORR Dependent variable is SCORR_T (1) (2) (3) (4) (5) (6) INTERCEPT UK_EQUITY ** * ** ** * ** N RELSIZE HERFINDAHL CROSSRET Panel B: Explaining sector-level odds-ratio Dependent variable is LOGODDS Dependent variable is LOGODDS_Z (7) (8) (9) (10) (11) (12) INTERCEPT UK_EQUITY *** ** *** *** ** ** N RELSIZE HERFINDAHL CROSSRET This table reports average coefficients from ten cross-sectional regressions of sector-year persistence measures on sector-year characteristics. The persistence measures used are SCORR (the Spearman correlation coefficient), SCORR_T (its t-value), LOGODDS (the log-odds ratio) and LOGODDS_Z (its Z-statistic). Persistence measures are based on raw (not risk adjusted) annual returns in consecutive calendar years. Only sector-years with 20 or more funds were included. Independent variables are as follows. UK_EQUITY is a dummy equal to one if sector funds are restricted to UK equities, and zero otherwise. N is the number of funds within a sector. RELSIZE is the ratio of fund assets within a sector to fund assets across all unit trust sectors. HERFINDAHL is the Herfindahl index of concentration of fund sizes within a sector. CROSSRET is the product of average returns for sector funds in the two years over which persistence is examined. *, **, and *** denote significance at the ten, five, and one percent levels, respectively. Significance levels are based on the standard deviation of the coefficient estimates from cross-sectional regressions (the Fama-Macbeth procedure). 27