UTI MIS (India) Probability of Target Price Finishing Over Current Price

    F00000WOH2 -- India Fund  

    INR 40.38  0.26  0.64%

    UTI MIS probability of target price tool provides mechanism to make assumptions about upside and downside potential of UTI MIS Advantage Dir Mn Pay performance during a given time horizon utilizing its historical volatility. Please specify UTI MIS time horizon, a valid symbol (red box) and a target price (blue box) you would like UTI MIS odds to be computed. Additionally see Investing Opportunities.
    Horizon     30 Days    Login   to change
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    UTI MIS Target Price Odds to finish over

    Current PriceHorizonTarget PriceOdds to move above current price in 30 days
     40.38 30 days 40.38  ABOUT 75.62%
    Based on normal probability distribution, the odds of UTI MIS to move above current price in 30 days from now is about 75.62% (This UTI MIS Advantage Dir Mn Pay probability density function shows the probability of UTI MIS Fund to fall within a particular range of prices over 30 days) .
    Assuming 30 trading days horizon, UTI MIS has beta of 0.3632 suggesting as returns on market go up, UTI MIS average returns are expected to increase less than the benchmark. However during bear market, the loss on holding UTI MIS Advantage Dir Mn Pay will be expected to be much smaller as well. Additionally UTI MIS Advantage Dir Mn Pay has an alpha of 0.0606 implying that it can potentially generate 0.0606% excess return over DOW after adjusting for the inherited market risk (beta).
     UTI MIS Price Density 
          Price 
    α
    Alpha over DOW
    =0.06
    β
    Beta against DOW=0.36
    σ
    Overall volatility
    =0.51
    Ir
    Information ratio =0.12

    UTI MIS Alerts

    UTI MIS Alerts and Suggestions

    UTI MIS Advantage is not yet fully synchronised with the market data
    The fund retains about 16.76% of its assets under management (AUM) in cash
    Additionally see Investing Opportunities. Please also try Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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