F00000PHA0 (Ireland) Probability of Target Price Finishing Over Current Price

    F00000PHA0 -- Ireland Fund  

    GBp 11,513  17.00  0.15%

    F00000PHA0 probability of target price tool provides mechanism to make assumptions about upside and downside potential of F00000PHA0 IR performance during a given time horizon utilizing its historical volatility. Please specify F00000PHA0 time horizon, a valid symbol (red box) and a target price (blue box) you would like F00000PHA0 odds to be computed. Additionally see Investing Opportunities.
    Horizon     30 Days    Login   to change
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    F00000PHA0 Target Price Odds to finish over

    Current PriceHorizonTarget PriceOdds to move above current price in 30 days
     11,513 30 days 11,513  NEARLY 4.48%
    Based on normal probability distribution, the odds of F00000PHA0 to move above current price in 30 days from now is nearly 4.48% (This F00000PHA0 IR probability density function shows the probability of F00000PHA0 Fund to fall within a particular range of prices over 30 days) .
    Assuming 30 trading days horizon, F00000PHA0 IR has beta of -0.0226 suggesting as returns on benchmark increase, returns on holding F00000PHA0 are expected to decrease at a much smaller rate. During bear market, however, F00000PHA0 IR is likely to outperform the market. Additionally F00000PHA0 IR has a negative alpha implying that the risk taken by holding this equity is not justified. The company is significantly underperforming DOW
     F00000PHA0 Price Density 
          Price 
    α
    Alpha over DOW
    =0.02
    β
    Beta against DOW=0.02
    σ
    Overall volatility
    =5,075
    Ir
    Information ratio =0.82

    F00000PHA0 Alerts

    F00000PHA0 Alerts and Suggestions

    F00000PHA0 IR is not yet fully synchronised with the market data
    F00000PHA0 IR generates negative expected return over the last 30 days
    Additionally see Investing Opportunities. Please also try Watchlist Optimization module to optimize watchlists to build efficient portfolio or rebalance existing positions based on mean-variance optimization algorithm.
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