JM Balanced (India) Risk Analysis And Volatility

Our way in which we are determining volatility of a fund is to use all available market data together with fund specific technical indicators that cannot be diversified away. We have found twenty-one technical indicators for JM Balanced which you can use to evaluate future volatility of the entity. Please check out JM Balanced Dir HY Bns Princ to validate if risk estimate we provide are consistent with the epected return of 0.0%.
Horizon     30 Days    Login   to change

JM Balanced Dir Technical Analysis

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JM Balanced Projected Return Density Against Market

Assuming 30 trading days horizon, JM Balanced has beta of 0.0 suggesting the returns on DOW and JM Balanced do not appear to be correlated. Furthermore, It does not look like the company alpha can have any bearing on the equity current valuation.
Assuming 30 trading days horizon, the coefficient of variation of JM Balanced is 0.0. The daily returns are destributed with a variance of 0.0 and standard deviation of 0.0. The mean deviation of JM Balanced Dir HY Bns Princ is currently at 0.0. For similar time horizon, the selected benchmark (DOW) has volatility of 0.78
Alpha over DOW
Beta against DOW=0.00
Overall volatility
Information ratio =0.00

JM Balanced Return Volatility

the fund accepts 0.0% volatility on return distribution over the 30 days horizon. the entity inherits 0.7996% risk (volatility on return distribution) over the 30 days horizon.
 Performance (%) 

JM Balanced Investment Opportunity

DOW has a standard deviation of returns of 0.8 and is 9.223372036854776E16 times more volatile than JM Balanced Dir HY Bns Princ. 0% of all equities and portfolios are less risky than JM Balanced. Compared to the overall equity markets, volatility of historical daily returns of JM Balanced Dir HY Bns Princ is lower than 0 (%) of all global equities and portfolios over the last 30 days.

JM Balanced Current Risk Indicators

JM Balanced Suggested Diversification Pairs

See also Investing Opportunities. Please also try Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.