Axis Income (India) Probability of Target Price Finishing Over Current Price

    F00000PFLR -- India Fund  

     10.90  0.01  0.09%

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

    Current PriceHorizonTarget PriceOdds to move above current price in 30 days
     10.90 30 days 10.90  ABOUT 78.52%
    Based on normal probability distribution, the odds of Axis Income to move above current price in 30 days from now is about 78.52% (This Axis Income Dir Qt Div probability density function shows the probability of Axis Income Fund to fall within a particular range of prices over 30 days) .
    Assuming 30 trading days horizon, Axis Income has beta of 0.3013 suggesting as returns on market go up, Axis Income average returns are expected to increase less than the benchmark. However during bear market, the loss on holding Axis Income Dir Qt Div will be expected to be much smaller as well. Additionally Axis Income Dir Qt Div has a negative alpha implying that the risk taken by holding this equity is not justified. The company is significantly underperforming DOW
     Axis Income Price Density 
     
          
    Current Price   Target Price   
    α
    Alpha over DOW
    =0.18
    β
    Beta against DOW=0.30
    σ
    Overall volatility
    =0.07
    Ir
    Information ratio =0.57

    Axis Income Alerts

    Axis Income Alerts and Suggestions

    Axis Income Dir generates negative expected return over the last 30 days
    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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