LIC MF (India) Probability of Target Price Finishing Over Current Price

    F00000VYUT -- India Fund  

    INR 17.12  0.64  3.60%

    LIC MF probability of target price tool provides mechanism to make assumptions about upside and downside potential of LIC MF ULIS 10Y RP UC Dir Mn Div performance during a given time horizon utilizing its historical volatility. Please specify LIC MF time horizon, a valid symbol (red box) and a target price (blue box) you would like LIC MF odds to be computed. Additionally see Investing Opportunities.
    Horizon     30 Days    Login   to change
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    LIC MF Target Price Odds to finish over

    Current PriceHorizonTarget PriceOdds to move above current price in 30 days
     17.12 30 days 17.12  ABOUT 39.63%
    Based on normal probability distribution, the odds of LIC MF to move above current price in 30 days from now is about 39.63% (This LIC MF ULIS 10Y RP UC Dir Mn Div probability density function shows the probability of LIC MF Fund to fall within a particular range of prices over 30 days) .
    Assuming 30 trading days horizon, LIC MF has beta of 0.0229 suggesting as returns on market go up, LIC MF average returns are expected to increase less than the benchmark. However during bear market, the loss on holding LIC MF ULIS 10Y RP UC Dir Mn Div will be expected to be much smaller as well. Additionally The company has an alpha of 0.1122 implying that it can potentially generate 0.1122% excess return over DOW after adjusting for the inherited market risk (beta).
     LIC MF Price Density 
          Price 
    α
    Alpha over DOW
    =0.11
    β
    Beta against DOW=0.0229
    σ
    Overall volatility
    =7.26
    Ir
    Information ratio =0.08

    LIC MF Alerts

    LIC MF Alerts and Suggestions

    LIC MF ULIS is not yet fully synchronised with the market data
    The fund retains about 12.4% of its assets under management (AUM) in cash

    Price Density Drivers

    LIC MF Health Indicators

    Additionally see Investing Opportunities. Please also try Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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