4.1 ANALYSIS OF MUTUAL FUND PERFORMANCE MEASURES Many mutual funds operate in public sector as well as private sector as a investment companies. Mutual fund performance can be evaluated through performance measurement ratios which are use in portfolio analysis. I here used Trey nor, Sharpe, and Jensen ratio to evaluate mutual funds and rank accordingly. Structural portfolio performance measures have the flexibility of gathering risk and return performance into a single value. The most commonly used composite measures are: Trey nor, Sharpe and Jensen measures. While Treynor measures
Risk can be measured in terms of Beta and standard deviations.
BETA:
 Beta is calculated by two returns factors relating to security return and market return.
 Beta is a measure of the volatility of a particular fund in comparison to the market as a whole, that is, the extent to which the fund's return is affected by market factors. Beta is calculated using a statistical tool called regression analysis.
 By definition, the market benchmark index of Sensex and Nifty has a beta of 1.0. Conservative investors should concentrate on mutual funds schemes with beta having low value. Aggressive investors can select to invest in mutual fund schemes which have higher beta value for higher returns where investors need to bear more
Rm is the market return or index. Variance is the square of standard deviation.

STANDARD DEVIATION:
 In mutual funds, the standard deviation tells about understanding how much the return on a fund is variation takes place from the expected returns based upon period of time.
 Standard deviation helps to analyze the volatility of the fund. The standard deviation of a fund measures this risk by measuring the degree to which the fund changes in relation to its average return of a fund for a period of time.
 Standard deviation is a calculation of returns of consistency based on mutual fund.
 Standard deviation of higher value should mention that the mutual fund of Net Asset Value is more risk and volatile compared to that of standard deviation of lower value.

Σ (Rx-Rx¯) ² σx = _____________ N Where, σ² is the Variance of Return is the Standard Deviation of