PIMCO GIS (Ireland) Probability of Target Price Finishing Over Current Price

    FOGBR05KHR -- Ireland Fund  

     6.53  0.01  0.15%

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

    Current PriceHorizonTarget PriceOdds to move above current price in 30 days
     6.53 30 days 6.53  ABOUT 27.4%
    Based on normal probability distribution, the odds of PIMCO GIS to move above current price in 30 days from now is about 27.4% (This PIMCO GIS Commodity Real Ret Int USD Acc probability density function shows the probability of PIMCO GIS Fund to fall within a particular range of prices over 30 days) .
    Assuming 30 trading days horizon, PIMCO GIS has beta of 0.0912 suggesting as returns on market go up, PIMCO GIS average returns are expected to increase less than the benchmark. However during bear market, the loss on holding PIMCO GIS Commodity Real Ret Int USD Acc will be expected to be much smaller as well. Additionally PIMCO GIS Commodity Real Ret Int USD Acc has a negative alpha implying that the risk taken by holding this equity is not justified. The company is significantly underperforming DOW
     PIMCO GIS Price Density 
          Price 
    α
    Alpha over DOW
    =0.07
    β
    Beta against DOW=0.09
    σ
    Overall volatility
    =2.87
    Ir
    Information ratio =0.0000373

    PIMCO GIS Alerts

    PIMCO GIS Alerts and Suggestions

    PIMCO GIS Commodity is not yet fully synchronised with the market data
    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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