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Applied Economics LettersPublication details, including instructions for authors and subscription information:http://www.tandfonline.com/loi/rael20

Mutual fund performance: banking versus independentmanagersJuan Carlos Matallin-Saez a , Amparo Soler-Dominguez a & Emili Tortosa-Ausina ba Departament de Finances i Comptabilitat , Universitat Jaume I , 12071, Castellón, Spainb Departament d'Economia and Ivie , Universitat Jaume I , 12071, Castellón, SpainPublished online: 09 Sep 2011.

To cite this article: Juan Carlos Matallin-Saez , Amparo Soler-Dominguez & Emili Tortosa-Ausina (2012) Mutualfund performance: banking versus independent managers, Applied Economics Letters, 19:8, 755-758, DOI:10.1080/13504851.2011.602008

To link to this article: http://dx.doi.org/10.1080/13504851.2011.602008

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Mutual fund performance: banking

versus independent managers

Juan Carlos Matallin-Saeza,*, Amparo Soler-Domingueza andEmili Tortosa-Ausinab

aDepartament de Finances i Comptabilitat, Universitat Jaume I, 12071Castellon, SpainbDepartament d’Economia and Ivie, Universitat Jaume I, 12071Castellon, Spain

We examine the performance of mutual fund managers for a sample ofSpanish mutual funds considering data on active management, loads, sizeand the number of funds managed per manager. We find evidence ofdifferences in fund performance according to management: independentmanagers outperform their banking counterparts even when the lowerassociated fees are considered. Overall, our results suggest that superioractive managers do exist and the slight discrepancies which arise betweenmanagers can be interpreted as agency problems.

Keywords: mutual fund; performance; manager; active management

JEL Classification: G23; G11

I. Introduction

In the context of mutual fund performance there is noclear evidence as to whether managers are able to add

value. Results may differ for different methodologiesor samples. The traditional evidence is that, on aggre-gate, performance is not significantly different fromzero and in some cases is negative. However, Puckett

and Yan (2011) reported different positions for andagainst managers’ skills in generating wealth and,among other studies, Rodriguez (2008) evidenced a

positive added value for investors for a sample ofEuropean fund managers. Against this inconclusivebackground, this article focuses on the analysis ofmutual fund performance relating active management

to managers’ profiles and other characteristics.As themanager decision-making process is not easily

observed, it is difficult to initially assess active manage-ment. Menkhoff and Schmidt (2005), Lutje (2009) andMenkhoff (2011) resolved this dilemma by directly ask-

ing managers in an attempt to capture their strategiesand attitudes. However, as data on mutual fund results

are more readily available, they are frequently used toinfer active management. Hence, some studies haveexamined strategies and risk level of mutual funds:Flavin (2006), among others. Beyond the strategiesfollowed by managers, agency problems have alsobeen documented. One example is Mehran and Stulz’s(2007) comprehensive review on conflicts of interest infinancial institutions. Chen et al. (2007) comparedactive funds managed by insurance companies withother mutual funds, finding that the former underper-form the latter. Alves and Mendes (2010) found thatmutual funds tend to overweight the stocks issued bytheir parent and underweight the stocks of competitors,thus eroding the performance of fund investors. Incontrast, significant side effects stem from the conflictof interest between independent managers and inves-tors, which occurs because of managers’ prioritizingcareer concerns rather than shareholder interests(Kempf et al., 2009). In this context, we contribute tothe literature by focusing on the profile of the profes-sional manager – banking or independent – in mutualfund performance. The results show that this role is

*Corresponding author. E-mail: matallin@cofin.uji.es

Applied Economics Letters ISSN 1350–4851 print/ISSN 1466–4291 online # 2012 Taylor & Francishttp://www.informaworld.com

DOI: 10.1080/13504851.2011.602008

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Applied Economics Letters, 2012, 19, 755–758

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related to the degree of active management of the port-folio and the loads charged to the fund. Manager pro-file could therefore be implemented as a keydeterminant in investors’ selection of mutual funds.

II. Data and Performance Measurement

The empirical analysis uses a sample of Spanishmutual funds from June 1998 to March 2007. Thesample is made up of all the domestic equity mutualfunds with a net asset value during this period.1

Following the Spanish Stock Market NationalCommission (CNMV), two types of funds can be dis-tinguished: Balanced Equity-Bond Funds (BF) andEquity Funds (EF). The daily return was calculatedas the variation relative to the net asset value. Mutualfunds data such as the net asset value, size and loadswere provided by the CNMV.Performance is measured exogenously by the multi-

factor linear model 1, widely used in mutual fundliterature, whose expression is

rpt ¼ ap þXJ

j

bpjrjt þ ept ð1Þ

where rpt is the excess return, over the risk-free return,of portfolio p in period and e is the error term of themodel. This return is adjusted to risk factors bpj withrespect to rjt, the excess return of the benchmark j.

Then, as an extended version of Jensen’s alpha, apmeasures performance. Considering the nature of themutual funds analysed, and to avoid benchmark omis-sion bias (Matallin-Saez, 2007), the following bench-marks are considered: the Ibex 35 index for broad stockinvestment, the Morgan Stanley Capital International(MSCI) Spanish market index for Small Caps, Valueand Growth styles, the Analistas FinancierosInternacionales (AFI) Government Debt index andMSCI World index.

III. Results

Panel 1 in Table 1 shows a summary of the results ofthe performance of mutual funds using model 1. As inthe previous literature, the aggregate performance isnegative or close to zero. Results for BF, with anannual average performance of -1.98%, are worsethan for EF, at 0.04%. Moreover, results for EF aremore dispersed, and comparing the data of the medianand mean, the latter improves slightly due to theresults of the best mutual funds on the right side ofthe distribution.We analyse the role of banking and independent

managers in determining performance. Panel 2 ofTable 1 shows the differences between the two for anytype of fund. Banking managers handle approximately4 timesmoremutual funds than independentmanagers.We use the chi-squared statistic to test the null hypoth-esis of independence between type of mutual fund and

Table 1. Mutual fund sample and performance

Panel 1

TypeNumber of

Annualized performance in percentage

managed funds Mean Median Minimum Maximum SD

BF 131 -1.98 -1.96 -7.25 6.90 2.16EF 74 0.04 -0.09 -7.98 10.33 2.89

Panel 2

Number of managed funds Average annualized performance in percentage

Type Banking Independent Banking Independent Difference: independent – banking (p-value)

BF 106 25 -2.22 -0.96 1.26 (0.002)EF 59 15 -0.27 1.25 1.51 (0.042)

Notes: The table presents the results of the performance measured as ap in Model 1. The sample period runs from 30 June 1998to 31 March 2007. The heteroscedasticity and autocorrelation consistent covariance estimator is by Newey and West (1987).The estimated coefficient ap is an annualized percentage.

1 The Spanish mutual fund industry essentially developed in the second half of the 1990s. For this reason, if we had selected anearlier starting date for the sample period, the number of funds in the sample would have been dramatically reduced. Thus, theuse of daily data enables the possibility of analysing a large volume of information for all the funds existing from 30 June 1998.

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type of manager. The null hypothesis was not rejected

(p-value = 0.979); the difference in performance is

therefore not driven by a heterogeneous distribution

of BF and EF across manager type. The right side of

panel shows how, for both types of funds, the perfor-

mance of independent managers is better than that of

banking managers; BF show a 1.26% annual improve-

ment, and EF, 1.51%. Due to the different variance in

performance distribution, instead of using a classic

ANOVA test to analyse the significance of the differ-

ences found, bootstrapping is applied. The results indi-

cate that these differences are indeed significant.Bearing in mind that independently managed funds

achieve a better performance, we now analyse what

inputs related to portfolio management could explain

performance. The first one is the level of activemanage-

ment of the fund portfolio. Sharpe (1992) linked passive

management to the fund’s style estimated in the model

1 and active management to tracking error. We there-

fore define the variable vp (active management) as the

value of 1 – R2, that is, the percentage of residual var-

iance in the model 1. If a manager follows a passive

(active) strategy, vp will be close to (far from) 1. The

second variable is lp (mutual fund loads). This is com-

puted as the costs (from manager fees and turnover)

over assets. Commonly, higher loads will erase perfor-

mance for investors. Another variable considered in the

literature is the size (sp) of themutual fund (Beckers and

Vaughan (2001) among others). To avoid the bias

reported by Matallin-Saez (2010), the size of a fund is

measured in relative terms with regard to the total

assets managed by all the funds at the beginning of

the sample period. Lastly, np represents the number of

mutual funds in the sample managed by the same man-

agers. A low (high) number of funds managed could be

inferred as a more concentrated (dispersed) manage-

ment of these funds. For this variable, Hu and Chang

(2008) found a negative relationship with respect to

performance. Table 2 shows the mean of the values of

these variables for each group of funds and type of

managers. In general, BF are more actively managed

and less expensive than EF. A comparison of banking

and independent managed funds reveals that the for-

mer aremore passive, somewhat larger in size, and their

managers handle a higher number of funds. From this

data and performance results, the model 2 is applied;

whereDp is a dummy variable that takes the value of 0

(1) for banking (independent) managed funds.

ap ¼ cp þ �1 þ f1Dp

� �vp þ �2 þ f2Dp

� �lp

þ �3 þ f3Dp

� �sp þ �4 þ f4Dp

� �np þ ep ð2Þ

Table 3 shows the results of estimating model 2. From

the results of �1 and f1 in both types of funds, active

management is inferred to be significant (at the 1%

Table 2. Descriptive data of performance inputs and type of manager

BF EF

Variable Banking managers Independent managers Banking managers Independent managers

Active management 0.20 0.26 0.08 0.16Loads 1.92 1.68 2.04 2.12Size 0.005 0.004 0.005 0.004Number of managed funds 5.66 2.16 6.15 2.53

Note: BF, Balanced Equity-Bond Funds; EF, Equity Funds.

Table 3. Performance inputs and type of manager

BF EF

Variable Estimated value p-Value Estimated value p-Value

cp -0.0054 0.351 0.0176 0.159Active management �1 -0.0168 0.218 0.0037 0.878

f1 0.0862 0.007 0.2207 0.000Loads �2 -0.0068 0.001 -0.0085 0.091

f2 -0.0002 0.969 0.0063 0.381Size �3 -0.2200 0.368 -0.3298 0.440

f3 0.8486 0.211 1.2559 0.367Number of managed funds �4 0.0002 0.786 -0.0003 0.742

f4 -0.0063 0.102 -0.0158 0.020

Note: BF, Balanced Equity-Bond Funds; EF, Equity Funds.

Mutual fund performance 757

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level) only for the mutual funds managed by indepen-dents. But for EF the coefficient is 2.5 times higherthan for BF. In other words, independent managers,on aggregate, add value to mutual funds through theiractive management, and this contribution is higherwhen they manage equity mutual funds, possiblybecause there are more strategies, risks and possibili-ties involved in investment in stock markets. Withrespect to the variable loads (�2), it is significant forboth types of managers and funds. As expected, ittakes negative value, namely, loads erode perfor-mance. Concretely, it is clearly significant for BF(p-value , 0.01), but somewhat lower for EF(p-value = 0.091). On the other hand, only for inde-pendent managers does the number of funds managedhave a negative impact on performance. It is clearlysignificant for EF but on the border for BF.In sum, performance by independent managers is

related positively to the level of active management,but negatively to the loads and the number of fundsmanaged. It seems that, on aggregate, when managersare independent and centre their efforts on the mana-ged portfolio, management adds value. However,banking managers appear to follow passive strategies(see Table 2) that do not add value, and consequentlyonly the loads charged are the most relevant variableto explain their underperformance.Overall, the results demonstrate that superior active

managers do exist and the slight discrepancies arisingbetween managers can be interpreted as agency pro-blems. The manager’s professional profile should beconsidered as a readily available source of informationfor the investor, providing ex ante evidence of theportfolio’s added value reported previously in theliterature.

Acknowledgement

This study is part of research project SEJ2007-67204/ECON supported by Ministerio de Ciencia yTecnologıa and P1-1B2009-54 by Fundacio CaixaCastello/Bancaixa and Universitat Jaume I.

References

Alves, C. and Mendes, V. (2010) Mutual funds biased pre-ference for the parent’s stock: evidence and explana-tion, Applied Financial Economics, 20, 1309–20.

Beckers, S. and Vaughan, G. (2001) Small is beautiful, TheJournal of Portfolio Management, 27, 9–17.

Chen, X., Yao, T. and Yu, T. (2007) Prudent man or agencyproblem? On the performance of insurance mutualfunds, Journal of Financial Intermediation, 16,175–203.

Flavin, T. (2006) How risk averse are fund managers?Evidence from Irish mutual funds, Applied FinancialEconomics, 16, 1355–63.

Hu, J. L. and Chang, T. P. (2008) Decomposition of mutualfund underperformance, Applied Financial EconomicsLetters, 4, 363–7.

Kempf, A., Ruenzi, S. and Thiele, T. (2009) Employmentrisk, compensation incentives, and managerial risk tak-ing: evidence from the mutual fund industry, Journal ofFinancial Economics, 92, 92–108.

Lutje, T. (2009) To be good or to be better: asset managers’attitudes towards herding, Applied FinancialEconomics, 19, 825–39.

Matallin-Saez, J. (2007) Portfolio performance: Factorsor benchmarks? Applied Financial Economics, 17,1167–78.

Matallin-Saez, J. (2010) On causality in the size-efficiencyrelationship: the effect of investor cash flows on themutual fund industry, Applied Economics. DOI:10.1080/00036841003800849.

Mehran, H. and Stulz, R. M. (2007) The economics of con-flicts of interest in financial institutions, Journal ofFinancial Economics, 85, 267–96.

Menkhoff, L. (2011) Are momentum traders different?Implications for the momentum puzzle, AppliedEconomics. DOI: 10.1080/00036846.2010.491462.

Menkhoff, L. and Schmidt, U. (2005) The use of tradingstrategies by fundmanagers: some first survey evidence,Applied Economics, 37, 1719–30.

Newey, W. and West, D. (1987) A simple, positive semi-definite, heteroskedasticity and autocorrelation consis-tent covariance matrix, Econometrica, 55, 703–8.

Puckett, A. and Yan, X. (2011) The interim trading skills ofinstitutional investors, The Journal of Finance, 66,601–33.

Rodriguez, J. (2008) European mutual funds and portfolio’scountry exposure: Does active management add value?,Applied Financial Economics, 18, 683–9.

Sharpe, W. (1992) Asset allocation: management style andperformance measurement, The Journal of PortfolioManagement, 18, 7–19.

758 J. C. Matallin-Saez et al.

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Indi

an I

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anag

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t - S

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