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Performance evaluation of balanced mutual fund schemes in Indian Scenario.


Mutual fund is an investment vehicle preferred by small investors as it offers an opportunity to invest in a diversified, professionally managed portfolio at a relatively low cost. These investors buy units of a particular mutual fund scheme that has a defined investment objective and strategy. The money thus collected is then invested by the fund manager in different types of securities. These could range from shares to debentures to money market instruments, depending upon the scheme's stated objectives. The income earned through these investments and the capital appreciation realized by the scheme is shared by its units in proportion to the number of units owned by them. Mutual Fund as an instrument has become an important aspect in the Indian Financial System. The value of mutual fund is depicted by NAV. The net asset value is the current market value of a fund's holdings, minus the fund's liabilities, that is usually expressed as a per-share amount. The Mutual Fund Industry in India started in 1963 with the formation of Unit Trust of India, at the initiative of the Government of India and Reserve Bank of India. The total asset under management popularly known as AUM has increased from Rs.1, 01, 565 crores in January 2000 to Rs.5, 67, 601.98 crores in April 2008. As at the end of March 2008, there were 33 mutual funds, which managed assets of Rs. 5,05,152 crores (US $ 126 Billion) under 956 schemes. This fast growing industry is regulated by the Securities and Exchange Board of India (SEBI). Association of Mutual Funds in India (AMFI) is the umbrella body of all the mutual funds registered with SEBI. It is a nonprofit organization committed to develop the Indian Mutual Fund Industry on professional, healthy and ethical lines and to enhance and maintain standards in all areas with a view to protect and promote the interests of mutual funds and their unit holders. With the increase in domestic savings and improvement in deployment of investment through markets, the need and scope for mutual fund operation has increased tremendously. Mutual funds are involved in the transformation of Indian capital market as they are playing a significant role in spreading equity culture. This industry is growing at a phenomenal rate. The impressive growth can be attributed to the entry of commercial banks and the private players in the mutual fund industry coupled with the rapid growth of the Indian capital markets during the last few years.

In this context, it becomes pertinent to study the performance of this industry. Close monitoring and evaluation of mutual funds on regular basis would be beneficial for the investors. The main objective of investing in a mutual fund scheme is to diversify risk. Though the mutual funds invest in diversified portfolio, the fund managers take different levels of risk in order to achieve the scheme's objectives. Therefore, while evaluating and comparing the performance of the schemes, the returns should be measured taking into account the risks involved in achieving the returns.

Review of Literature

Treynor (1965), Sharpe (1966), and Jensen (1968) have developed the standard indices to measure risk adjusted mutual fund returns. They came out with the models to evaluate the portfolio's performance. Their models have been used in detail later in the study to evaluate the performance.

John and Donald (1974) examined the relationship between the stated fund objectives and their risks-return attributes. They conclude that on an average, the fund manager appears to offer superior aggregate returns but they are offset by expenses and load charges.

Lehmann and Modest (1987) came out with one of the cornerstone study of mutual fund performance evaluation. They, for the first time used multifactor models for performance measurement. Although evidence of persistence is found, the authors note that results are highly dependent on performance metrics employed; the results show considerable differences between rankings based on the Capital Asset Pricing Model (CAPM) and those based on various applications of the Arbitrage Pricing Theory (APT) Model. Moreover, substantial ranking differences occur also within alternative Arbitrage Pricing Theory implementations.

Ippolito (1989) examined the relationship between mutual fund investment performance and other variables such as asset size, expenses, turnover, and load status. It was stated that domestic mutual fund risk-adjusted returns, net of fees and expenses, were comparable to returns of index funds. However, portfolio turnover was unrelated to fund performance.

Barua, Raghunathan and Varma (1991) evaluated the performance of Master Share during the period 1987 to 1991 using Sharpe, Jensen and Treynor measures. They conclude that the fund performed better that the market, but not so well as compared to the Capital Market Line.

Goetzmann and Ibbotson (1994) analyzed monthly total returns of 728 mutual funds over 13-year period (1976-1988). Using total returns and the Jensen alphas as performance measures they examined the power of various lengths of selection periods to predict the performance measured from holding periods of the same length. The time horizons tested in this study are one year, two year, three year and one month. Generally, the results are significant, i.e., past performance has some predictive power on future performance for all time horizons tested. To test robustness of the results over the conjecture whether the performance persistence is related more to investment style than skill, they performed the same tests on a sub-sample that consists only of the relatively homogenous growth funds. The tests indicate that the performance persistence is not likely to be due to style differences.

Jayadev (1996) evaluated the performance of two growth oriented mutual funds (Mastergain and Magnum Express) on the basis of monthly returns compared to benchmark returns. For this purpose, risk adjusted performance measures suggested by Jenson, Treynor and Sharpe were employed. It was found that, Mastergain has performed better according to Jenson and Treynor measures and on the basis of Sharpe ratio its performance is not up to the benchmark. The performance of Magnum Express was poor on the basis of all those three measures. However, Magnum Express is well diversified and has reduced its unique risk where as Mastergain did not. These two funds were found to be poor in earning better returns either adopting marketing or in selecting under priced securities.

Gupta & Sehgal (1998) found out the investment performance of 80 schemes managed by 25 mutual funds, 15 in private sector and 10 in public sector for the time period of June 1992-1996. The study has examined the performance in terms of fund diversification and consistency of performance. The paper concludes that mutual fund industry's portfolio diversification has performed well and it supported the consistency of performance.

Gupta (2000) has examined the investment performance of Indian mutual funds using weekly NAV data and found that the schemes showed mixed performance during 1994-1999.

Redman, Gullett and Manakyan (2000) examined the risk-adjusted returns using Sharpe's Index, Treynor's Index, and Jensen's Alpha for five portfolios of international mutual funds and for three time periods: 1985-1994, 1985-1989, and 1990-1994. The benchmarks for comparison were the U. S. market proxied by the Vanguard Index 500 mutual fund and a portfolio of funds that invest solely in U. S. stocks. The result shows that for 1985 through 1994 the portfolios of international mutual funds outperformed the U. S. market and the portfolio of U. S. mutual funds under Sharpe's and Treynor's indices. During 1985-1989, the international fund portfolio outperformed both the U. S. market and the domestic fund portfolio. Returns declined below the stock market and domestic mutual funds during 1990-1994.

Kothari and Warner (2001) argued that standard performance measures depend on the benchmarks' ability to mimic the fund style, and therefore benchmarks must be selected carefully.

Korkeamaki and Smythe (2004) analyzed the Finnish mutual fund industry from 1993 to 2000, and focused on market segmentation and mutual fund expenses. As per their study, Finnish mutual funds have performed neutrally with the exception of equity funds underperforming.

Aggarwal (2007) provided an overview of mutual fund activity in emerging markets and described their size and asset allocation. His paper analyzed the Indian mutual fund industry's pricing mechanism with empirical studies on its valuation. He also analyzed data at both the fund-manager and fund-investor levels.

Gupta and Aggarwal (2007) examined the performance of mutual funds operation in India. In this regard, quarterly return of all the equity-diversified mutual funds during the period from January 2002 to December 2006 was tested. Analysis was carried out with the help of Capital Asset Pricing Model (CAPM) and Fama-French Model. Amidst contrasting findings from the application of the two models, the study calls for further research and insights into the interplay between the performance determinant factor portfolios and their effect on mutual fund returns.

Anand and Murugaiah (2008) examined the components and sources of investment performance in order to attribute it to specific activities of Indian fund managers. They also attempted to identify a part of observed return which was due to the ability to pick up the best securities at given level of risk. For this purpose, Fama's methodology is adopted here. The study covers the period between April 1999 and March 2003 and evaluates the performance of mutual funds based on 113 selected schemes having exposure more than 90percent of corpus to equity stocks of 25 fund houses. The empirical results reported reveals the fact that the mutual funds were not able to compensate the investors for the additional risk that they have taken by investing in the mutual funds. The study concludes that the influence of market factor was more severe during negative performance of the funds while the impact selectivity skills of fund managers was more than the other factors on the fund performance in times of generating positive return by the funds.

Thanou (2008) in his paper examined the risk adjusted overall performance of 17 Greek Equity Mutual Funds between the years 1997 and 2005. The performance evaluation of each fund based on the CAPM performance, Treynor and Sharp indexes for the nine year period as well as for three sub-periods displaying different market characteristics was done. Then, he compared the rankings obtained by the two indexes and found significant differences in rankings between up and down market conditions. Lastly, paper proceed to analyze the fund managers' performance, distinguishing superior security selection ability and market timing, using the standard and quadratic Jensen's performance measures. Results indicate that the majority of the funds under examination followed closely the market, achieved overall satisfactory diversification and some consistently outperformed the market, while the results in market timing are mixed, with most funds displaying negative market timing capabilities.

Sehgal and Janwar (2008) in his paper evaluated the performance of selected equity-based mutual funds in India. Argument was made that multi-factor benchmarks provide better selectivity and timing measures compared to one-factor CAPM as they control for style characteristics such as size, value and momentum. The results timing ability, and to some extent stock selectivity improve when daily data was used instead of monthly data. It was concluded that higher observation frequency captures the trading skills of more active fund managers in a better fashion. They showed that timing should be examined in a multi-dimensional framework with additional measures for timing of style characteristics.

Guha (2008) focused on return-based style analysis of equity mutual funds in India using quadratic optimization of an asset class factor model proposed by William Sharpe. The study found the "Style Benchmarks" of each of its sample of equity funds as optimum exposure to 11 passive asset class indexes. The study also analyzed the relative performance of the funds with respect to their style benchmarks. The results of the study showed that the funds have not been able to beat their style benchmarks on the average.

Huang, Sialm and Zhang (2009) studied that mutual funds change their risk levels significantly over time. Their paper investigates whether risk shifting has an impact on fund performance? The result is consistent with risk shifters having inferior ability or acting opportunistically due to agency conflicts and inconsistent with skilled fund managers taking advantage of changing investment opportunities.

Afza and Rauf (2009) evaluated mutual fund performance by using Sharpe ratio with the help of pooled time-series and cross-sectional data and focused on different fund attributes such as fund size, expenses, age, turnover, loads and liquidity. The quarterly sample data were collected for all the open-ended mutual funds listed on Mutual Fund Association of Pakistan (MUFAP), for the years 1999-2006. The results indicate that among various funds attributes lagged return, liquidity and 12B-1 had significant impact on fund performance.

Debasish (2009) studied the performance of selected schemes of mutual funds based on risk-return relationship models and measures. A total of 23 schemes offered by six private sector mutual funds and three public sector mutual funds have been studied over the time period April 1996 to March 2009 (13 years). The analysis has been made on the basis of mean return, beta risk, co-efficient of determination, Sharpe ratio, Treynor ratio and Jensen Alpha. The overall analysis finds Franklin Templeton and UTI being the best performers and Birla SunLife, HDFC and LIC mutual funds showing poor below-average performance.

Objectives of the Study

Indian Mutual Fund Industry has grown enormously. Now it has plethora of schemes, having different investment objective, available for small investor to choose from. This present study has the objective of finding out the necessary facts regarding performance of selected balanced schemes (Both growth and dividend), which can benefit the investors and fund managers.

The specific objectives of the study are:

* To evaluate the performance of Indian Mutual Fund Selected Balanced Schemes using Return-Risk Analysis, Sharpe Measure, Treynors Measure and Jensen Alpha.

* To compare all the measures against the market to distinguish the performers from the laggards.

* To analyze the excess return per unit of risk evidenced by mutual fund schemes, and to draw comparisons.

Data and Sources of Study

The period of study is from 1st September 2007 to 31st August 2010 (3 years). The study aims at analyzing the performance of open-ended balanced mutual funds schemes. This study takes those mutual funds which are having a minimum of 10 years of operation i.e. their date of set up is before 1st September 2000 and funds whose schemes are not transferred to any other fund. Therefore, this study will show the last 3 years' performances of the mutual funds with are the old and stable players. Out of these, those which have balance open-ended schemes with continuous availability of NAV data were selected. Finally, 15 Mutual Funds were short listed. Two schemes balance-growth and balance-dividend were selected for all short listed mutual funds. Thus, total 30 schemes came under the purview of this study. The study has used secondary data because this study pertains to historical analysis of reported financial data. Daily Net Asset Values (NAV) data have been used for the schemes and the daily closing values for the benchmark market index (NSE Nifty) have also been used. The main sources of data have been the official website of National Stock Exchange ( and Association of Mutual Funds in India (

Research Methodology

After collecting the data of NAV of the schemes selected and nifty values, various measures of return / risk and portfolio performance were applied:


The daily log returns are computed on the basis of the NAV of the different schemes and returns in the market index are calculated on basis of NSE Nifty on the respective date for the 3 years.

The log return from a mutual fund scheme (Rst) at time t, given in Equation-1, is as follows:

[] = Ln ([NAV.sub.t]/[NAV.sub.t-1]) (1)

Where, [NAV.sub.t] and [NAV.sub.t-1] are net assets value for time period t and t-1, respectively.

The mean return of the mutual fund scheme ([]) over a period of time, given in Equation-2, is as follows:

[] = [summation] []/n (2)

Where, [] is the return from a mutual fund scheme at time t and n is the total number of time period studied.

The log return on the market (representative by a stock index) at time t, given in Equation-3, is as follows:

[] = Ln ([I.sub.t]/[I.sub.t-1]) (3)

Where, [I.sub.t] and [I.sub.t-1] are value of a benchmark stock market index at period t and t-1, respectively. In our case, we have taken the NSE Nifty as the benchmark stock index representing the broad market.

The mean return of the market portfolio ([]) over a period of time, given in Equation-4, is as follows:

[] = [summation] []/n (4)

Where, [] is the return from a stock market index (for our case, NSE Nifty) at time t and n is the total number of time periods studied.

Risk Free Rate

By definition, a risk less asset has zero variability of returns. If an investor buys an asset at the beginning of the holding period with the known terminal value, such type of asset can be called as risk-less or risk free asset. Government securities and nationalized bank deposits fall under this category. In this study, average daily yield on 91-days Treasury bill have been used as a proxy for risk free rate of return.


The risk is calculated on the basis of daily NAV. The following measures of risks associated with mutual funds have been calculated for the study:

Beta ([beta]): i.e., fund's volatility as regard market index measuring the extent of co-movement of fund with that of the benchmark index. Higher values of [beta] indicate a high sensitivity of fund returns against market returns; the lower value indicates low sensitivity. Higher [beta] values are desired for the mutual funds during bull phase of the market and lower [beta] values are desired during the bear phase to out perform the market.

Standard Deviation (SD): i.e., fund's volatility or variation from the average expected return over a certain period. Standard deviation is computed from logarithmic daily returns.

For further evaluation, the risk-return relation models given by Sharpe (1966), Treynor (1965) and Jensen (1968) have been applied.

Sharpe Ratio

William F. Sharpe (1966) devised an index of portfolio performance measure, referred to as reward to variability ratio. The Sharpe measure provides the reward to volatility tradeoff. It is the ratio of the fund portfolio's average excess return divided by the standard deviation of returns and is given by Equation-5.

Sharpe Ratio = ([] - [])/sd (5)

Where, []= average return on mutual fund portfolio over the sample period, [] = average risk free return over the sample period, and sd = standard deviation of excess returns over the sample period.

By dividing the average return of the portfolio in excess of the risk-free return by the standard deviation of the portfolio, we get the Sharpe ratio (given by Equation-5) which measures the risk premium earned per unit of risk exposure. In other words, it measures the change in the portfolio's return with respect to a one unit change in the portfolio's risk. The higher this "Reward-to-Variability-Ratio" the more attractive is the evaluated portfolio because the investor receives more compensation for the same increase in risk.

Treynor Ratio

Jack Treynor (1965) conceived an index of portfolio performance measure called as reward to volatility ratio, based on systematic risk The Treynor measure is similar to the Sharpe ratio, except that it defines reward (average excess return) as a ratio of the CAPM beta risk. Treynor's performance measure is defined as the risk premium earned per unit of risk taken. Thus, it is computed as the average return of the portfolio in excess of the risk-free return divided by the portfolio's beta. Treynor's ratio is given by Equation-6 as shown below:

Treynor's Ratio = ([] - [])/[Beta.sub.p] (6)

Where, [] = average return on mutual fund portfolio over the sample period, [] = average risk free return over the sample period, and [Beta.sub.p] = beta risk value for the mutual fund portfolio. The higher this ratio the more attractive is the evaluated portfolio.

Jensen alpha

Michael C. Jensen (1968) has given different dimension and confined his attention to the problem of evaluating a fund manager's ability of providing higher returns to the investors. He defines his measure of portfolio performance as the difference between the actual returns on a portfolio in any particular holding period and the expected returns on that portfolio conditional on the risk-free rate, its level of "systematic risk", and the actual returns on the market portfolio. Jensen's Alpha measure is given by the Equation-7 as shown below.

Jensen Alpha = [] - ([] + [Beta.sub.p] ([] - [])) (7)

Where, [] is the average mutual fund portfolio return over the time period, [] is the average risk free return over the time period; [] is the return on the market portfolio.

Results, Findings and Discussion

Table 1 depicts the mean return, systematic risk and total risk of schemes selected and the market for the period of study, i.e. 1st September 2007 to 31st august 2010.


Using equation 1, 2, 3 and 4, mean return for the scheme and index has been calculated. It can be seen that 21 mutual fund schemes has positive average daily returns and rest 9 are giving negative returns. If we look at those 9 negative return providing schemes, it can be found out that out of those, 8 are the balanced-dividend schemes. It means the balanced-growth schemes have performed better than the balanced-dividend schemes. By further analyzing, it can be seen that 13 balanced schemes have outperformed the market by proving better returns. The top performers as per average daily mean return are HDFC MF (Growth) with .0638%, DSP BlackRock MF (Growth) with .0545% and Canara Robeco MF (Growth) with .0509% mean return. The worst performers are JM Financial MF (Dividend), Escorts MF (Dividend) and Principal MF (Dividend) with negative returns of -.0353%, -.0348% and -.0292% respectively.


Third Column of Table 1 shows beta of every scheme. It can be seen that the variation is not much with regard to beta of all the schemes. The value of beta is varying between 0.437-0.718 and on an average it is hovering around 0.6. It represents that all the mutual funds returns are less volatile and thus less risky. Escorts MF (Growth) have least beta value of .437 and Sundaram BNP Paribas MF (Dividend) has the highest systematic risk of .718. Similar is the story with total risk also where Standard deviation for all the schemes lies between 1.254%-1.812%.

Table 2 depicts the Sharpe Ratio, Treynors Ratio and Jensen Alpha for the selected schemes and the market for the period of study, i.e. 1st September 2007 to 31st august 2010.

Sharpe Measure

Sharpe Measure is one of the most common tools of evaluating the portfolio which has been used extensively in many of such papers. Sharpe Ratio for the individual scheme and the market has been calculated using equation 5. It is the ratio of the fund portfolio's average excess return divided by the standard deviation of returns. Positive value shows better performance. Higher positive value is found in HDFC MF (Growth), DSP BlackRock MF (Growth) and Canara Robeco MF (Growth) with Sharpe ratio 0.038, 0.031 and 0.023 respectively. 14 schemes have negative Sharpe measure which shows their bad performance during the period of study. 13 out of total schemes outperformed the market as per this measure which is an adequate performance indicator of whole mutual fund industry. The laggard performers are JM Financial MF (Dividend), Escorts MF (Dividend) and ICICI Prudential MF (Dividend) with negative ratio of -0.029, 0.027 and -0.025 respectively. Both of the schemes of JM financials MF performed badly giving negative Sharpe ratio. And both the schemes of ING MF performed decently, giving positive values of Sharpe ratio and the measure is also slightly above the market ratio.

Treynor Measure

Treynor ratio measures the excess return earned over risk free return per unit of systematic risk. The third column of table 2 presents the Treynor ratio value for all the schemes and the market portfolio for which Equation 6 has been used to calculate. Here, the major observation mirrors the similar finding as in Sharpe ratio and mean return with some minute differences. The top performers are the same, i.e, HDFC MF (Growth), DSP BlackRock MF (Growth) and Canara Robeco MF (Growth) with Treynor ratio 0.099, 0.073 and 0.053 respectively. Tata MF (Growth) has also performed well with the measure 0.045. The laggard performers are again the same but their ranking in terms of worseness as per this measure differs. Escorts MF (Dividend) being the worst performer with ratio of -0.114, followed by Principal MF (Dividend) with ratio -0.077 and then JM Financial MF (Dividend) with ratio -0.074. ICICI Prudential MF (Dividend) has also been one of the slacker with ratio measure of -0.062.

Jensen Alpha Measure

Using equation 7, the values in column 4 of table 2 have been calculated that shows the Jensen alpha for the schemes. It is the excess return provided by the portfolio over the expected (CAPM) returns. Higher value indicated better performance. 17 schemes have shown negative alpha which indicates the failure on part of their fund managers to forecast security prices on time for taking better investment decision. Rest 13 schemes have given the return over the expected return which means 43% of the schemes have been successful as per this measure. The results are more or less the same with the same top performers and lazybones. HDFC MF (Growth), DSP BlackRock MF (Growth) and Canara Robeco MF (Growth) with alpha value 0.043, 0.033 and 0.028 respectively are top performers. 12 schemes out of those 17 showing negative alpha value and 3 schemes out of those 13 showing positive alpha value are the balanced-dividend schemes which clearly portrays that the Balanced-Growth schemes have outperformed the Balanced-Dividend schemes.


In India, today a common investor is generally confused regarding his (or her) choice of investment in mutual funds due to innumerable schemes available in the market. Which mutual fund is to be selected for investment becomes an important decision? This study was trying to resolve this same problem along with analyzing the whole industry's performance. However, the use of a systematic performance evaluation technique helps the investors to take wise decisions so that they are able to achieve their investment objectives. Balanced schemes are preferred the most because of reasonable risk and decent returns as both equity and debt forms part of it. In the conclusion, we can say that HDFC MF (Growth) is having the maximum return, maximum Sharpe and maximum Treynors. The study clearly brings out the fact that HDFC MF (Growth), DSP BlackRock MF (Growth), Tata MF (Growth) and Canara Robeco MF (Growth) are the top performers and JM Financial MF (Dividend), Escorts MF (Dividend), ICICI Prudential MF (Dividend) and Principal MF (Dividend) are few bad performers of the industry based on the performance of last three years. Mutual Funds like Canara Robeco MF (Dividend), Franklin Templeton MF (Growth), ING MF (Growth and Dividend), Principal MF (Growth), SBI MF (Growth), Sundaram BNP Paribas MF (Growth), Tata MF (Dividend) and UTI MF (Growth) have been the above market average performers.

More or less results shown by applying any of the performance measure were same. 13 out of all the 30 schemes have performed well and above the market which shows that 43 % of the balanced schemes have proved to provide better returns than the market. It has been a reasonable performance shown by the industry as a whole. The study also gives one more important outcome that the balanced-growth schemes have given better results as compared to Balanced-dividend schemes. 14 out of 15 (approximately 93%) balanced-growth schemes have given positive returns and 7 out of 15 (approximately 47%) balanced-dividend schemes have given positive returns. This is explicitly showing the balanced-growth investment style performing better. Even the Sharpe measure of Balanced-Growth plans and the corresponding Balanced-Dividend plans stands testimony to the relatively better performance of Balanced-Growth plans as 13 Growth plans out of 15 (approximately 87%) had better risk adjusted excess returns highlighting the fact that the Balanced-Growth plans are more likely to reward the investors for the extra risk they are assuming. The analysis points to the fact that the investment style does matter as performances are driven by investment styles.

The small investors are well-advised to analyze the return and risk parameters of the mutual funds, over longer period of time, before their investment decisions. Although mutual finds are instruments of diversified investments, a prudent choice between the many available mutual fund schemes will go a long way in generating wealth for the investors. Further, in times of high stock market volatility, mutual funds are the best source of investments with assured and adequate returns provided the selection of the mutual funds is in the right direction.


Afza, T., and A. Rauf, (2009), 'Performance Evaluation of Pakistani Mutual Funds', Pakistan Economic and Social Review, Vol. 47, No. 2, pp. 199-214.

Aggrawal, D., (2007), 'Measuring Performance of Indian Mutual Funds', Prabhandan Tanikniqui, Vol. 1, No. 1, pp. 43-52.

Anand, S., and V. Murugaiah, (2008), 'Analysis of Components of Investment Performance--An Empirical Study of Mutual Funds in India', 10th Indian Institute of Capital Markets Conference, ICFAI: Hyderabad.

Barua, S. K., V. Raghunathan, and J. R. Verma, (1991), 'Master Share: A Bonanza for Large Investors', Vikalpa, Vol. 17, No. 1, pp. 29-34.

Debasish, S.S., (2009),'Investigating Performance of Equity-based Mutual Fund Schemes in Indian Scenario', KCA Journal of Business Management, Vol. 2, Issue 2, pp. 1-15. Available at:

Thanou, E., (2008), 'Mutual Fund Evaluation During Up and Down Market Conditions: The Case of Greek Equity Mutual Funds', International Research Journal of Finance and Economics, Euro Journals Publishing, Issue 13, pp. 84-93.

Goetzmann, W. N., and R.G. Ibbotson, (1994), 'Do Winners Repeat? Pattern in Mutual Fund Performance', Journal of Portfolio Management, 20, pp. 9-17.

Guha, S., (2008), 'Performance of Indian Equity Mutual Funds vis-a-vis their Style Benchmarks', The ICFAI Journal of Applied Finance, Vol.14, No. 1, pp. 49-81.

Gupta, A., (2000), 'Market Timing Abilities of Indian Mutual Fund Managers: An Empirical Study', The ICFAI Journal of Applied Finance, Vol. 6, No. 2, pp. 47-60.

Gupta, M., and N. Aggarwal, (2007), 'Performance of Mutual Funds in India: An Empirical Study', The ICFAI Journal of Applied Finance, Vol.13, No. 9, pp. 5-16.

Gupta, O.P., and Sehgal, S., (1998), "Investment Performance of Mutual Funds: The Indian Experience", ICFAI Journal of Applied Finance, Vol. No 2, April, pp.25-36.

Huang, J., Sialm, C., and Zhang, H., (2009), 'Risk Shifting and Mutual Fund Performance' , National Bureau of Economic Research, NBER Working Paper No. 14903, Available at:

Ippolito, R.A., (1989), 'Efficiency with Costly Information: A Study of Mutual Fund Performance', Quarterly Journal of Economics, 104, pp. 1-23.

Jayadev, M., (1996), 'Mutual Fund Performance: An Analysis of Monthly Returns', Finance India, Vol. X, No.1, pp.73-84.

Jensen, M.C., (1968), 'The Performance of Mutual Funds in the period 1945-1964', Journal of Finance, Vol. 23, No.2, pp. 389-416.

John, G., and M. Donald, (1974), 'Objectives and Performance of Mutual Funds: 1960-1967', Journal of Financial and Quantitative Analysis, Vol. 27, No. 2, pp. 311-333.

Korkeamaki, T., and T.I. Smythe, (2004), 'An Empirical Analysis of Finnish Mutual Fund Expenses and Returns', European Financial Management, Vol. 10, No. 3, pp. 413438.

Kothari, S.P., and J.B. Warner, (2001), 'Evaluating Mutual Fund Performance, The Journal of Finance', 56, pp.1985-2010.

Lehman, B.N., and D.M. Modest, (1987), 'Mutual fund performance evaluation: A comparison of benchmarks and benchmark comparisons', Journal of Finance, 42, pp. 233-265.

Pastor, L., and R.F. Stambaugh, (2002), 'Mutual fund performance and seemingly unrelated assets', Journal of Financial Economics, 63, pp. 315-349.

Redman, A.L., N.S. Gullett, and H. Manakyan, (2000), 'The Performance of Global and International Mutual Funds', Journal of Financial and Strategic Decision, Vol. 13, No. 1, pp. 75-85.

Sehgal, S., and Janwar, M., (2008), "On Stock Selection Skills and Market Timing Abilities of Mutual Fund Managers in India", International Research Journal of Finance and Economics, Euro Journals Publishing, Issue 15, pp. 307-317.

Sharpe, W.F., (1966), 'Mutual Fund Performance', Journal of Business, Vol. 39, No.1, pp. 119-138.

Treynor, J.L., (1965), 'How to Rate Management of Investment Funds', Harvard Business Review, 43, pp. 63-73.

Himanshu Puri


Department of Management

Delhi Institute of Advanced Studies

Plot-6, Sector 25, Rohini


Mobile: 09990103061
Table 1: Mean return, Systematic risk and
Total risk of Schemes Selected

Scheme Avg. Daily Beta

Baroda pioneer MF-Balanced(growth) 0.00894564 0.63544402
Baroda pioneer MF-Balance(dividend) 0.009703933 0.63433337
Canara Robeco MF-Balance(growth) 0.050900244 0.65903726
Canara Robeco MF-Balance(dividend) 0.031486263 0.66131942
DSP BlackRock MF-Balance(growth) 0.054540678 0.52888461
DSP BlackRock MF-Balance(dividend) -0.01050627 0.50746491
Escorts MF-Balance(growth) 0.016639671 0.43740559
Escorts MF-Balance(dividend) -0.03487073 0.44011764
Franklin Templeton MF-Balance(growth) 0.033339079 0.59895781
Franklin Templeton MF-Balance(dividend) -0.0182203 0.59955618
HDFC MF-Balance(growth) 0.063819363 0.48544538
HDFC MF-Balance(dividend) 0.014533928 0.48813292
ICICI Prudential MF-Balance(growth) 0.021464842 0.60914813
ICICI Prudential MF-Balance(dividend) -0.02144255 0.59370647
ING MF-Balance(growth) 0.029033247 0.65359439
ING MF-Balance(dividend) 0.028970131 0.65354415
JM Financial MF-Balance(growth) -0.0266863 0.68614543
JM Financial MF-Balance(dividend) -0.03533932 0.68564608
LIC MF-Balance(growth) 0.02038932 0.62428986
LIC MF-Balance(dividend) 0.004484957 0.62267628
PRINCIPAL MF-Balance(growth) 0.034348074 0.59981549
PRINCIPAL MF-Balance(dividend) -0.0292798 0.58068755
SBI MF-Balance(growth) 0.033839818 0.64601481
SBI MF-Balance(dividend) -0.00844366 0.65388207
Sundaram BNP Paribas MF-Balance(growth) 0.036707715 0.69117036
Sundaram BNP Paribas MF-Balan.(dividend) -0.00992533 0.71806609
Tata MF-Balance(growth) 0.044655641 0.63390748
Tata MF-Balance(dividend) 0.029405517 0.63766054
UTI MF-Balance(growth) 0.034057389 0.61929191
UTI MF-Balance(dividend) 0.011362173 0.63211006
Market 0.025791448 1

Scheme Standard

Baroda pioneer MF-Balanced(growth) 1.55538437
Baroda pioneer MF-Balance(dividend) 1.5539068
Canara Robeco MF-Balance(growth) 1.52372117
Canara Robeco MF-Balance(dividend) 1.61991894
DSP BlackRock MF-Balance(growth) 1.25525741
DSP BlackRock MF-Balance(dividend) 1.63183473
Escorts MF-Balance(growth) 1.50372741
Escorts MF-Balance(dividend) 1.81233381
Franklin Templeton MF-Balance(growth) 1.36326333
Franklin Templeton MF-Balance(dividend) 1.59318167
HDFC MF-Balance(growth) 1.25499411
HDFC MF-Balance(dividend) 1.46364106
ICICI Prudential MF-Balance(growth) 1.42515303
ICICI Prudential MF-Balance(dividend) 1.46999416
ING MF-Balance(growth) 1.47215564
ING MF-Balance(dividend) 1.47244381
JM Financial MF-Balance(growth) 1.68486558
JM Financial MF-Balance(dividend) 1.70069493
LIC MF-Balance(growth) 1.58709182
LIC MF-Balance(dividend) 1.62916553
PRINCIPAL MF-Balance(growth) 1.38206646
PRINCIPAL MF-Balance(dividend) 1.82325047
SBI MF-Balance(growth) 1.47238367
SBI MF-Balance(dividend) 1.70471354
Sundaram BNP Paribas MF-Balance(growth) 1.57885343
Sundaram BNP Paribas MF-Balan.(dividend) 1.79808331
Tata MF-Balance(growth) 1.47397125
Tata MF-Balance(dividend) 1.50059385
UTI MF-Balance(growth) 1.41507481
UTI MF-Balance(dividend) 1.50646533
Market 2.20055193

Table 2: Sharpe Ratio, Trynors Ratio and Jensen Alpha for Schemes

Scheme Sharpe Trynors
 Ratio Ratio

Baroda pioneer MF-Balanced(growth) -0.0042398 -0.0103777
Baroda Pioneer MF-Balance(dividend) -0.0037558 -0.0092005
Canara Robeco MF-Balance(growth) 0.02320644 0.0536542
Canara Robeco MF-Balance(dividend) 0.0098438 0.0241126
DSP BlackRock MF-Balance(growth) 0.03106978 0.0737412
DSP BlackRock MF-Balance(dividend) -0.0159614 -0.0513265
Escorts MF-Balance(growth) 0.00073123 0.0025138
Escorts MF-Balance(dividend) -0.0278154 -0.1145395
Franklin Templeton MF-Balance(growth) 0.01305616 0.0297166
Franklin Templeton MF-Balance(dividend) -0.0211906 -0.056309
HDFC MF-Balance(growth) 0.03846971 0.0994535
HDFC MF-Balance(dividend) -0.0006874 -0.0020613
ICICI Prudential MF-Balance(growth) 0.00415727 0.0097263
ICICI Prudential MF-Balance(dividend) -0.0251584 -0.0622911
ING MF-Balance(growth) 0.00916557 0.0206445
ING MF-Balance(dividend) 0.00912091 0.0205495
JM Financial MF-Balance(growth) -0.0250622 -0.0615415
JM Financial MF-Balance(dividend) -0.0299168 -0.0742065
LIC MF-Balance(growth) 0.00305541 0.0077676
LIC MF-Balance(dividend) -0.0067858 -0.0177542
PRINCIPAL MF-Balance(growth) 0.01360859 0.0313563
PRINCIPAL MF-Balance(dividend) -0.0245824 -0.0771842
SBI MF-Balance(growth) 0.01242863 0.0283271
SBI MF-Balance(dividend) -0.0140691 -0.036679
Sundaram BNP Paribas MF-Balance(growth) 0.01340695 0.0306258
Sundaram BNP Paribas MF-Balance(dividend) -0.0141625 -0.0354639
Tata MF-Balance(growth) 0.01975313 0.0459303
Tata MF-Balance(dividend) 0.00923995 0.0217442
UTI MF-Balance(growth) 0.01308573 0.0299007
UTI MF-Balance(dividend) -0.0027733 -0.0066095
Market 0.00465837 0.0102513

Scheme Jensen

Baroda pioneer MF-Balanced(growth) -0.0130962
Baroda Pioneer MF-Balance(dividend) -0.0123266
Canara Robeco MF-Balance(growth) 0.0285937
Canara Robeco MF-Balance(dividend) 0.0091563
DSP BlackRock MF-Balance(growth) 0.0336263
DSP BlackRock MF-Balance(dividend) -0.031203
Escorts MF-Balance(growth) -0.0033913
Escorts MF-Balance(dividend) -0.0549296
Franklin Templeton MF-Balance(growth) 0.0116705
Franklin Templeton MF-Balance(dividend) -0.039895
HDFC MF-Balance(growth) 0.0433634
HDFC MF-Balance(dividend) -0.0059492
ICICI Prudential MF-Balance(growth) -0.0002651
ICICI Prudential MF-Balance(dividend) -0.0430156
ING MF-Balance(growth) 0.0068516
ING MF-Balance(dividend) 0.006789
JM Financial MF-Balance(growth) -0.0491987
JM Financial MF-Balance(dividend) -0.0578466
LIC MF-Balance(growth) -0.0019678
LIC MF-Balance(dividend) -0.0178545
PRINCIPAL MF-Balance(growth) 0.0127129
PRINCIPAL MF-Balance(dividend) -0.0507206
SBI MF-Balance(growth) 0.0116212
SBI MF-Balance(dividend) -0.0307436
Sundaram BNP Paribas MF-Balance(growth) 0.0141443
Sundaram BNP Paribas MF-Balance(dividend) -0.0327621
Tata MF-Balance(growth) 0.0226741
Tata MF-Balance(dividend) 0.0073858
UTI MF-Balance(growth) 0.012137
UTI MF-Balance(dividend) -0.0106903
Market 0
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Author:Puri, Himanshu
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Geographic Code:9INDI
Date:Jul 1, 2010
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