Persistence of Mutual Fund Performance in India

Persistence of Mutual Fund Performance in IndiaSummer Project 2012

Motivation of the study-1

• MFs offer diversification, expertise and pooling• MFs offer small investors access to investment with a small

amount of capital

• At any point of time, there exists a large no. of scheme to choose from

• Question is: How to choose the scheme (s), specially by un-initiated investors

• It’s a common practice in India to choose the MF scheme that has exhibited the best past performance• Over the past 1/2/3 years

• A second factor is about ability of fund managers

Motivation of the study-2

• A fund manager may be able to generate abnormal return from her portfolio during a particular period

• This may be due to certain coincidences • E.g., chance selection of a promising stock or sector

• However, is the fund manager capable of repeating the performance

• In other words, does past performance is any indicator of future performance?

• Empirical evidence from the US and other markets show that fund managers cannot beat the market • Persistently over long-run

• Wherein a passive investment is more efficient

Indian MF Industry

• Evolution• 1963 - Unit Trust of India• 1987 – LIC and General Insurance Corporation, PSBs are

allowed to launch• 1993 – Foreign and private players were allowed• AMFI reported Rs.47,004 crores AUM.

• In 2012, there are 42 AMCs with AUM of Rs.692,705 crores

• A slight decline after entry-load ban was imposed w.e.f. 1st August 2009 (from around Rs.8 lakh crores).

Objective

• Analyze performance of the equity diversified mutual funds deploying standard measures risk-adjusted performance.

• Past 36-months data were used to compute performance measure

• Regressed on following 12-, 24- and 36-month performances• Starting from April 1997 (first complete 36-month past

performance window)• Rolling the process forward by a month until April 2009• Thus a maximum of sets of 180 observations for a scheme• Match with future average return and the return by the buy and

hold strategy of the investor over the next 1year, 2years & 3years

DataApril 1994 – March 2012

Net Asset Value

• The period covers the different bull and bear phases of the Indian equity market.

• The monthly closing NAV of 242 equity diversified mutual funds collected from the websites of AMFI (Association of Mutual Funds in India) and from the smctradeonline.com.

• For the final analysis only 169 mutual fund schemes have been taken into account for which the data was available for at least 72 months (past 36 & future 36 months) i.e., • funds launched up to March 2008.

Benchmark and T-Bill

• The monthly closing price data of each index is collected from the websites of BSE (Bombay Stock Exchange) and NSE (National Stock Exchange).

• The monthly T-Bill returns (proxy for risk-free rate) data were collected from the Handbook of Statistics on Indian Economy, various issues, published by RBI.

Sample

AMC Ownership

Number of AMC

Number of Schemes

Private Indian 12 64

Indian Joint Venture

9 57

Foreign 9 29

Public 2 19

MethodologyFormulae and Techniques

NAV Return

• The monthly return of each fund has been calculated from the monthly closing NAV by using the following formula:

Rt+1 = NAVt+1 - NAVt

NAVt

where Rt+1 = Return of the mutual over month ‘t+1’.

NAVt = Closing NAV of the month ‘t’.

NAVt+1 = Closing NAV of the month ‘t+1’.

Benchmark Return

• The monthly return of all the 15 indices has been calculated using the following formula where RB stands for the return of the benchmark :

RB.t+1 = Pt+1 - Pt

Pt

where RB.t+1 = Return of the benchmark over the month ‘t’

Pt = Closing price of the month ‘t’

Pt+1 = Closing price of the month ‘t+1’

Sharpe Ratio

• The most commonly used measure of risk adjusted performance is the Sharpe ratio which measures the fund’s excess return per unit of its risk

• Given that

Rp = Return of the portfolio (Mutual Fund)

Rf = Risk free rate of return (T-Bill)

ϬP = Standard dev. of the portfolio return

P

fP RRRatiosSharpe

_'

Security Market Line

• Security Market Line (from CAPM) represents the expected total return of every security or portfolio i as a linear function of the return of the market portfolio m :

Ei = Rf + βi [Em - Rf ]

where Ei ≡ E[Ri] denotes the unconditional continuous expected return of the portfolio I

βi = cov(Ri , Rm) is the beta of the portfolio i. ϭ2(Rm)

• This equilibrium relation corresponds to the market model

rit = αi + βirm + ϵit ,

where ri = Ri – Rf denotes excess return on the portfolio i.

Jensen’s Alpha

• Total risk is captured by ϭ • Consists of systematic risk (explained by market index)• And capture by beta (β)• And non-systematic risk (not explained by the CAPM

regression)

• The intercept term for a stock should be zero theoretically• And is indeed so for most individual stocks empirically• Jensen proposed that the intercept for an actively-

managed portfolio should be a performance of the manager

• A measure of how much additional return a manager can generate over the benchmark• Without exceeding the systematic risk of the benchmark

Treynor Ratio & Information Ratio

• We don’t directly use Jensen’s alpha here (thoough we computed) for reasons explained later

• The Treynor Ratio (TR) is the ratio of Jensen’s alpha over the portfolio beta

• Another measure deployed here is the Information ratio, which is Jensen’s alpha per unit of non-systematic risk of the portfolio (measured by the standard deviation of the market model residuals)

ˆˆ

TR)(ˆ

ˆ

IR

Coefficient of Variation

• Since none of the above measures takes into account the benchmark, we deploy another measure

• Excess of the return per unit of total risk of the portfolio over that of th benchmark:

CR = Rp/Ϭp - Rb/Ϭb

where Rp = Return of the portfolio (Mutual Fund)

Rb = Return of the benchmark

Ϭp = Standard deviation of return of portfolio

Ϭb = Standard deviation of return of benchmark

A Sample Table

Average of monthly returns -

R_p - R_f

Average of monthly returns -

R_p - R_f

BAHR - Portfolio -

Benchmark

Past Performance Measure Future Returns

Scheme Date

Sharpe IR TR Coeff_Vrar Fut1Y Fut2Y Fut3Y Fut1Y Fut2Y Fut3Y Fut1Y Fut2Y Fut3Y

Birla Sun Life Asset Allocation Aggressive

31-Mar-2007 0.358 0.339 -2.620 0.116 0.007

-0.008

230.016

0010.009

0450.004

9980.015

426

-0.103

60.063

30.061

0

30-Apr-

2007 0.369 0.349 -3.286 0.1120.006

627

-0.005

20.015

8610.005

626

-0.012

17

-0.001

17

-0.128

30.061

70.073

0

31-May-2007

0.539951

0.477031

-3.899

630.278

9910.000

5160.002

5390.015

6770.003

476

-0.007

240.000

164

-0.077

40.047

70.073

4

Literature Review

International Fund Market

• Grinblatt and Titman (1992), Carhart (1994), Sharpe(1995) among others, provided evidence that confirmed the predictability of future performance by past performance – returns persists

• Elton, Gruber and Blake (1996) reported that the past carries the information about the future performance of the funds and they highlighted that both the 1 year and 3 year alphas convey the future information.

• Michael Stutzer, on the contrary, observed that the fund managers who can beat the benchmark for the long run surprisingly still have significant probability of underperforming • which extends over a long period of time.

Indian Evidence

• A sample of 50 Indian mutual fund was analyzed over 26 months by Roy and Bhattacharjee found that though in short term the mutual funds were able to generate above normal return.

• Deb, Banerjee and Chakrabarti observed that on an average fund managers have not been able to beat their style benchmark.

• Analysis of open ended equity mutual fund schemes indicate that the performance of majority of sample was not significantly related to their market movements during the study period.

• Managerial Ability• Dey, Yi Wang and Yexiao Xu (2001) highlighted that the

fund managers may possess superior stock selection skills• Deb, Banerjee and Chakrabarti (2007) found very little

evidence of market timing skill of fund managers though their stock selection ability was decent enough to produce good returns from the market.

• Bear Market• Dr. S Narayan Rao observed that the fund managers were

able to diversify the risk and even managed to give returns greater than risk free return.• But the debt funds were ultimate winners

CalculationsPerformance Measure and Returns

Past Performance

• The performance measures such as Sharpe, IR, Treynor, and CR for each scheme has been calculated using the data of past 36 months and this is rolled up to March 2008. • Sharpe/IR/Treynor/CR

• April 1997Apr 94 – Mar

97

• Sharpe/IR/Treynor/CR• May 1997

May 94 – Apr 97

Continued… Till March 2008

Future Performance

• The future performance measures were computed for the next 1 year, 2years & 3 years has using following indicators:

• Future returns :

1. Rp – Rf

2. Rp – Rb

3. Buy and Hold return over its benchmark

ResultsRegression

Example - Morgan Stanley Growth

Future Performance Coefficient Intercept Adjusted Significance

Value p-value Value p-value R2 F-Statistic

Sharpe -0.0454 0.0000 0.0140 0.0000 0.0901 0.0000

IR Ratio -0.0254 0.0651 0.0091 0.0000 0.0144 0.0651

Treynor -1.0561 0.0028 0.0106 0.0000 0.0464 0.0028

Coeff_Var -0.0049 0.8992 0.0091 0.0001 -0.0059 0.8992

1 yr Rp-Rf


Future Performance Coefficient Intercept Adjusted

Significance


Sharpe -0.0395 0.0000 0.0146 0.0000 0.1794 0.0000

IR Ratio -0.0238 0.0087 0.0103 0.0000 0.0374 0.0087

Treynor -1.4222 0.0000 0.0125 0.0000 0.2350 0.0000

Coeff_Var -0.0697 0.0052 0.0108 0.0000 0.0431 0.0052

2 yr Rp-Rf



Sharpe 0.0145 0.0000 0.0137 0.0000 0.1159 0.0000

IR Ratio 0.0239 0.0000 0.0146 0.0000 0.1398 0.0000

Treynor 0.1167 0.3115 0.0152 0.0000 0.0002 0.3115

Coeff_Var 0.0220 0.0724 0.0152 0.0000 0.0156 0.0724

3 yr Rp-Rf




Sharpe -0.0201 0.0052 0.0094 0.0000 0.0401 0.0052

IR Ratio -0.0080 0.3677 0.0073 0.0000 -0.0011 0.3677

Treynor -0.3453 0.1312 0.0078 0.0000 0.0077 0.1312

Coeff_Var 0.0163 0.5132 0.0071 0.0000 -0.0034 0.5132

1 yr Rp-Rm




Sharpe -0.0193 0.0001 0.0100 0.0000 0.0910 0.0001

IR Ratio -0.0098 0.1099 0.0079 0.0000 0.0101 0.1099

Treynor -0.6296 0.0000 0.0089 0.0000 0.0975 0.0000

Coeff_Var -0.0244 0.1515 0.0081 0.0000 0.0069 0.1515

2 yr Rp-Rm




Sharpe -0.0171 0.0000 0.0096 0.0000 0.1149 0.0000

IR Ratio -0.0134 0.0284 0.0080 0.0000 0.0264 0.0284

Treynor -0.5173 0.0001 0.0087 0.0000 0.0948 0.0001

Coeff_Var -0.0234 0.1066 0.0079 0.0000 0.0112 0.1066

3 yr Rp-Rm




Sharpe -0.2833 0.0000 0.0437 0.0000 0.1750 0.0000

IR Ratio -0.1353 0.0301 0.0135 0.1719 0.0220 0.0301

Treynor -5.6421 0.0004 0.0213 0.0329 0.0665 0.0004

Coeff_Var -0.1917 0.2775 0.0149 0.1412 0.0011 0.2775

1 yr BAHR




Sharpe -0.2265 0.0000 0.0312 0.0000 0.3003 0.0000

IR Ratio -0.0870 0.0323 0.0063 0.3321 0.0229 0.0323

Treynor -2.8130 0.0064 0.0100 0.1318 0.0409 0.0064

Coeff_Var -0.0460 0.6836 0.0058 0.3841 -0.0054 0.6836

2 yr BAHR




Sharpe -0.1459 0.0000 0.0134 0.0001 0.4480 0.0000

IR Ratio -0.0653 0.0157 -0.0020 0.6015 0.0334 0.0157

Treynor -0.7157 0.2338 -0.0028 0.4782 0.0030 0.2338

Coeff_Var 0.0699 0.2764 -0.0055 0.1550 0.0013 0.2764

3 yr BAHR


Main ResultsAMC Groupwise

Indian Joint Venture AMC



Sharpe -0.0341 0.0000 0.0152 0.0000 0.0585 0.0000

IR Ratio -0.0306 0.0000 0.0139 0.0000 0.0372 0.0000

Treynor -0.0002 0.3107 0.0087 0.0000 0.0000 0.3107

Coeff_Var 0.0131 -0.0090 0.0083 0.0000 0.0003 0.2455

1 yr Rp-Rf



Sharpe -0.0228 0.0000 0.0160 0.0000 0.0930 0.0000

IR Ratio -0.0211 0.0000 0.0152 0.0000 0.0606 0.0000

Treynor 0.0000 0.6312 0.0109 0.0000 0.0002 0.6312

Coeff_Var 0.0017 0.8016 0.0108 0.0000 -0.0010 0.8016

2 yr Rp-Rf




Sharpe 0.0183 0.0000 0.0142 0.0000 0.2214 0.0000

IR Ratio 0.0223 0.0000 0.0137 0.0000 0.2288 0.0000

Treynor -0.0001 0.1229 0.0193 0.0000 0.0020 0.1229

Coeff_Var 0.0623 0.0000 0.0166 0.0000 0.3510 0.0000

3 yr Rp-Rf




Sharpe -0.0172 0.0000 0.0105 0.0000 0.0315 0.0000

IR Ratio -0.0160 0.0000 0.0100 0.0000 0.0215 0.0000

Treynor -0.0002 0.0254 0.0072 0.0000 0.0033 0.0254

Coeff_Var 0.0145 0.0603 0.0068 0.0000 0.0021 0.0603

1 yr Rp-Rm





Sharpe -0.0118 0.0000 0.0109 0.0000 0.0346 0.0000

IR Ratio -0.0113 0.0000 0.0105 0.0000 0.0242 0.0000

Treynor 0.0000 0.4983 0.0082 0.0000 -0.0006 0.4983

Coeff_Var -0.0029 0.6125 0.0083 0.0000 -0.0008 0.6125

2 yr Rp-Rm




Sharpe -0.0128 0.0000 0.0119 0.0000 0.0605 0.0000

IR Ratio -0.0132 0.0000 0.0000 0.0116 0.0449 0.0000

Treynor -0.0001 0.1026 0.0083 0.0000 0.0024 0.1026

Coeff_Var -0.0003 0.9579 0.0083 0.0000 -0.0014 0.9579

3 yr Rp-Rm




Sharpe -0.0715 0.0000 0.0493 0.0000 0.0219 0.0000

IR Ratio -0.0684 0.0000 0.0473 0.0000 0.0157 0.0000

Treynor -0.0007 0.1459 0.0357 0.0000 0.0009 0.1459

Coeff_Var 0.0514 0.1804 0.0341 0.0000 0.0007 0.1804

1 yr BAHR




Sharpe -0.0898 0.0000 0.0588 0.0000 0.0775 0.0000

IR Ratio -0.0816 0.0000 0.0550 0.0000 0.0488 0.0000

Treynor -0.0001 0.8056 0.0383 0.0000 -0.0010 0.8056

Coeff_Var -0.0392 0.1776 0.0397 0.0000 0.0009 0.1776

2 yr BAHR




Sharpe -0.0979 0.0000 0.0647 0.0000 0.1358 0.0000

IR Ratio -0.1005 0.0000 0.0628 0.0000 0.0996 0.0000

Treynor 0.0002 0.5327 0.0377 0.0000 -0.0009 0.5327

Coeff_Var -0.0398 0.1385 0.0394 0.0000 0.0017 0.1385

3 yr BAHR

Private Indian AMC



Sharpe -0.0250 0.0000 0.0178 0.0000 0.0323 0.0000

IR Ratio -0.0146 0.0004 0.0157 0.0000 0.0087 0.0004

Treynor 0.0001 0.7292 0.0128 0.0000 -0.0007 0.7292

Coeff_Var 0.0453 0.0000 0.0096 0.0000 0.0260 0.0000

1 yr Rp-Rf

Private Indian AMC



Sharpe -0.0198 0.0000 0.0197 0.0000 0.0570 0.0000

IR Ratio -0.0121 0.0000 0.0179 0.0000 0.0169 0.0000

Treynor 0.0003 0.1281 0.0152 0.0000 0.0012 0.1281

Coeff_Var 0.0304 0.0000 0.0128 0.0000 0.0341 0.0000

2 yr Rp-Rf

Private Indian AMC



Sharpe 0.0200 0.0000 0.0173 0.0000 0.1950 0.0000

IR Ratio 0.0291 0.0000 0.0153 0.0000 0.3249 0.0000

Treynor 0.0002 0.1483 0.0225 0.0000 0.0012 0.1483

Coeff_Var 0.0626 0.0000 0.0168 0.0000 0.4959 0.0000

3 yr Rp-Rf

Private Indian AMC



Sharpe -0.0127 0.0000 0.0117 0.0000 0.0194 0.0000

IR Ratio -0.0065 0.0155 0.0105 0.0000 0.0036 0.0155

Treynor -0.0001 0.5428 0.0092 0.0000 -0.0005 0.5428

Coeff_Var 0.0249 0.0000 0.0075 0.0000 0.0184 0.0000

1 yr Rp-Rm

Private Indian AMC



Sharpe -0.0106 0.0000 0.0128 0.0000 0.0321 0.0000

IR Ratio -0.0063 0.0012 0.0117 0.0000 0.0087 0.0012

Treynor 0.0001 0.6567 0.0104 0.0000 -0.0007 0.6567

Coeff_Var 0.0135 0.0001 0.0093 0.0000 0.0129 0.0001

2 yr Rp-Rm

Private Indian AMC



Sharpe -0.0122 0.0000 0.0139 0.0000 0.0645 0.0000

IR Ratio -0.0080 0.0000 0.0127 0.0000 0.0207 0.0000

Treynor -0.0002 0.1618 0.0108 0.0000 0.0011 0.1618

Coeff_Var 0.0137 0.0000 0.0095 0.0000 0.0202 0.0000

3 yr Rp-Rm

Private Indian AMC



Sharpe -0.2392 0.0000 0.1445 0.0000 0.0919 0.0000

IR Ratio -0.2016 0.0000 0.1370 0.0000 0.0546 0.0000

Treynor -0.0023 0.2460 0.0971 0.0000 0.0003 0.2460

Coeff_Var 0.1872 0.0000 0.0837 0.0000 0.0133 0.0000

1 yr BAHR

Private Indian AMC



Sharpe -0.2401 0.0000 0.1530 0.0000 0.1740 0.0000

IR Ratio -0.2051 0.0000 0.1429 0.0000 0.1054 0.0000

Treynor -0.0015 0.3384 0.0984 0.0000 -0.0001 0.3384

Coeff_Var 0.0807 0.0180 0.0919 0.0000 0.0042 0.0180

2 yr BAHR

Private Indian AMC



Sharpe -0.2225 0.0000 0.1609 0.0000 0.2255 0.0000

IR Ratio -0.1947 0.0000 0.1514 0.0000 0.1353 0.0000

Treynor -0.0011 0.3822 0.1035 0.0000 -0.0003 0.3822

Coeff_Var 0.0779 0.0107 0.0962 0.0000 0.0061 0.0107

3 yr BAHR

Foreign AMC



Sharpe -0.0250 0.0000 0.0166 0.0000 0.0341 0.0000

IR Ratio -0.0075 0.0743 0.0130 0.0000 0.0023 0.0743

Treynor -0.0001 0.8466 0.0121 0.0000 -0.0010 0.8466

Coeff_Var 0.0476 0.0000 0.0102 0.0000 0.0333 0.0000

1 yr Rp-Rf

Foreign AMC



Sharpe -0.0272 0.0000 0.0199 0.0000 0.1106 0.0000

IR Ratio -0.0215 0.0000 0.0175 0.0000 0.0608 0.0000

Treynor -0.0003 0.2115 0.0140 0.0000 0.0007 0.2115

Coeff_Var 0.0202 0.0002 0.0129 0.0000 0.0161 0.0002

2 yr Rp-Rf

Foreign AMC



Sharpe 0.0143 0.0000 0.0186 0.0000 0.1053 0.0000

IR Ratio 0.0147 0.0000 0.0192 0.0000 0.0888 0.0000

Treynor 0.0000 0.6730 0.0222 0.0000 -0.0013 0.6730

Coeff_Var 0.0502 0.0000 0.0188 0.0000 0.3863 0.0000

3 yr Rp-Rf

Foreign AMC



Sharpe -0.012 0.000 0.011 0.000 0.018 0.0000

IR Ratio -0.004 0.158 0.009 0.000 0.001 0.1581

Treynor 0.000 0.154 0.009 0.000 0.001 0.1536

Coeff_Var 0.025 0.000 0.008 0.000 0.022 0.0000

1 yr Rp-Rm

Foreign AMC



Sharpe -0.014 0.000 0.013 0.000 0.053 0.0000

IR Ratio -0.011 0.000 0.012 0.000 0.030 0.0000

Treynor 0.000 0.474 0.010 0.000 -0.001 0.4742

Coeff_Var 0.008 0.039 0.009 0.000 0.004 0.0391

2 yr Rp-Rm

Foreign AMC



Sharpe -0.016 0.000 0.014 0.000 0.100 0.0000

IR Ratio -0.016 0.000 0.013 0.000 0.083 0.0000

Treynor 0.000 0.086 0.010 0.000 0.003 0.0858

Coeff_Var 0.008 0.021 0.009 0.000 0.007 0.0214

3 yr Rp-Rm

Foreign AMC



Sharpe -0.2359 0.0000 0.1126 0.0000 0.0624 0.0000

IR Ratio -0.1662 0.0000 0.0896 0.0000 0.0324 0.0000

Treynor 0.0025 0.2694 0.0701 0.0000 0.0002 0.2694

Coeff_Var 0.2276 0.0001 0.0610 0.0000 0.0150 0.0001

1 yr BAHR

Foreign AMC



Sharpe -0.2896 0.0000 0.1299 0.0000 0.1794 0.0000

IR Ratio -0.2506 0.0000 0.1077 0.0000 0.1197 0.0000

Treynor 0.0014 0.3964 0.0671 0.0000 -0.0004 0.3964

Coeff_Var 0.0521 0.2560 0.0643 0.0000 0.0004 0.2560

2 yr BAHR

Foreign AMC



Sharpe -0.2654 0.0000 0.1330 0.0000 0.2506 0.0000

IR Ratio -0.2611 0.0000 0.1185 0.0000 0.1921 0.0000

Treynor 0.0008 0.5493 0.0659 0.0000 -0.0010 0.5493

Coeff_Var 0.0719 0.0631 0.0610 0.0000 0.0038 0.0631

3 yr BAHR

Conclusion

Sharpe’s Ratio

Sharpe's Ratio Private Indian Indian JV Foreign

Public Sector Indian

Rp-Rf

Fut_1Y -ve -ve -ve -ve


Fut_3Y +ve +ve +ve +ve

Rp-Rm




BAHR




Information Ratio

Information RatioPrivate Indian Indian JV Foreign


Rp-Rf




Rp-Rm

Fut_1Y -ve -ve F_NS -ve



BAHR

Fut_1Y -ve -ve -ve F_NS



Treynor’s Ratio

Treynor's Ratio Private Indian Indian JV Foreign


Rp-Rf

Fut_1Y F_NS F_NS F_NS F_NS

Fut_2Y F_NS F_NS F_NS +ve


Rp-Rm




BAHR




Coefficient of Variation

Coefficient of VariationPrivate Indian Indian JV Foreign


Rp-Rf

Fut_1Y +ve F_NS +ve -ve



Rp-Rm


Fut_2Y +ve F_NS +ve F_NS


BAHR


Fut_2Y +ve F_NS F_NS F_NS


• Sharpe Ratio• The future performance of all kind of –vely correlated.• Information Ratio• The predicament is almost similar across all types of

AMC’s• Treynor’s Ratio• Insignificant• Coefficient of Variation• Private Indian & Foreign AMC imitated by its past.• While it is trivial for Indian Joint Ventures.• Unclear for Public AMC.

Further ResearchLeaping Data Limitations

• The analysis can be extended for each AMC’s seperately.

• The analysis can be done by grouping the schemes on the basis of capital.

• The past performance measure can be calculated over 1 year, 2 years & 3 years period for that purpose weekly data is to be made available.

• The analysis can be done for a particular market scenario say during sub prime crisis or other phases of boom and bust.

Aman KesarwaniJunior Undergraduate

Mathematics and Computing Indian Institute of Technology Guwahati

Email : [email protected] : +91 7896 17 2432

Thanks !

mailto:[email protected]

Risk Adjusted Return

• In 1996 Elton, Gruber and Blake made a significant contribution to the field by addressing the issue of survivorship bias of the testing sample of funds.

• They refined the technique to calculate the risk adjusted return using the historical return data.

• Concluded that the past carries the information about the future performance of the fund and they highlighted that both the 1 year and 3 year alphas convey the future information.

M3 measure

• Muralidhar (2000) proposed a new measure called M3 for the construction of optimal portfolio of fund, benchmark and risk free assets.

• This new measure accounts for the difference in the standard deviation of the benchmark and portfolio and the correlations of mutual fund portfolios and their benchmark for an investor’s relative risk target.

Rating Firms

• Michael Stutzer analyzed the ratings given by different rating firms who partition the funds into different categories based on their style, size, asset class & sectors.

• He also reported that the fund managers who can beat the benchmark for the long run surprisingly still have significant probability of underperforming which extends over a long period of time.

Benchmark

• Stutzer also identified that the Sharpe Ratio which is part of the basis for rating produced by S&P and Charles Schwab is not appropriate for rating purpose because it uses a T-Bill benchmark instead of benchmark that user wants to beat.

• So in our study we also took the corresponding benchmark for each fund that the fund managers want to beat and calculated the excess return over the market

In Indian Context

PCM

• A sample of 50 Indian mutual fund was analyzed over 26 months by Roy and Bhattacharjee.

• Calculating the Performance Change Measure (PCM) developed by Grinblatt and Titman (1993) at the lag of one month, one quarter and one year and

• Found that though in short term the mutual funds were able to generate above normal return but on average the combined PCM of all mutual funds is significantly different from zero.

Return Based Style Analysis

• Deb, Banerjee and Chakrabarti did a return based style analysis of Indian mutual fund

• Analyzed their relative performance with respect to the style benchmark obtained by doing quadratic optimization of asset class factor model using historical monthly return

• Found out that on an average fund managers have not been able to beat their style benchmark.

Open Ended Equity Mutual Fund

• The result of analysis of risk & return relationship of open ended equity mutual fund schemes of both the public and private sector mutual funds in India indicate that the performance of majority of sample was not significantly related to their market movements during the study period.

Managerial Ability

• The investigation of underperformance of mutual fund portfolios by Dey, Yi Wang and Yexiao Xu (2001) highlighted that the fund managers may possess superior stock selection skills

• But the substantial gains could be achieved by improving the efficiency of allocation of mutual fund assets.

• They also suggested the when the mutual fund turnover is excessive then fund manager may rely on the stock price momentum for profitable returns.

Market Timing & Stock Selection

• A similar study based on the market timing and stock selection ability was done by Deb, Banerjee and Chakrabarti (2007)

• Using conditional and unconditional model over Indian fund market

• Found very little evidence of market timing skill of fund managers though their stock selection ability was decent enough to produce good returns from the market.

Bear Market

• Dr. S Narayan Rao evaluated the performance of Indian mutual funds in bear market through return performance index, risk-return analysis, Treynor’s ratio, Sharpe ratio, Sharpe measure, Jensen measure and Fama measure.

• He witnessed that the Medium term debt funds performed extremely well during that period while InfoTech equity funds suffered the most.

• Some fund managers were able to diversify the risk and maximize the return and even few managed to give returns greater that risk free return during bear market but the debt fund were the ultimate winners.

Sub Prime Crisis

• Bose (2012) tried to throw the light on the mutual funds’ performance during the recent financial crisis which tested the resilience of Indian mutual fund industry.

• Huge outflow of investment from the equity fund markets a huge surge of investment in the debt and gilt fund markets driven by the low policy rates and the risk averse attitude of the investors during that period.

Food

Persistence of Mutual Fund Performance in India