JM Gov (India) Manager Performance Evaluation

JMGOVSECMNDI -- India Fund  

 24.97  0.0006  0.0024%

The fund owns Beta (Systematic Risk) of 0.0 which attests that the returns on MARKET and JM Gov are completely uncorrelated. Although it is extremely important to respect JM Gov Sec existing price patterns, it is better to be realistic regarding the information on equity price patterns. The way in which we are determining future performance of any fund is to evaluate the business as a whole together with its past performance including all available fundamental and technical indicators. By inspecting JM Gov Sec technical indicators you can at this moment evaluate if the expected return of 0.0% will be sustainable into the future.
Horizon     30 Days    Login   to change

JM Gov Sec Relative Risk vs. Return Landscape

If you would invest  2,497  in JM Gov Sec Mn Div on August 20, 2018 and sell it today you would earn a total of  0.00  from holding JM Gov Sec Mn Div or generate 0.0% return on investment over 30 days. JM Gov Sec Mn Div is generating negative expected returns and assumes 0.0% volatility on return distribution over the 30 days horizon. Simply put, 0% of equities are less volatile than JM Gov Sec Mn Div and 99% of equity instruments are likely to generate higher returns than the company over the next 30 trading days.
 Daily Expected Return (%) 
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JM Gov Market Risk Analysis

Sharpe Ratio = 0.0
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Based on monthly moving average JM Gov is performing at about 0% of its full potential. If added to a well diversified portfolio the total return can be enhanced and market risk can be reduced. You can increase risk-adjusted return of JM Gov by adding it to a well-diversified portfolio.

JM Gov Performance Rating

JM Gov Sec Mn Div Risk Adjusted Performance Analysis


Risk-Adjusted Fund Performance

Over the last 30 days JM Gov Sec Mn Div has generated negative risk-adjusted returns adding no value to fund investors.
Please also check Risk vs Return Analysis. Please also try Pattern Recognition module to use different pattern recognition models to time the market across multiple global exchanges.