CGWM GL (Ireland) Probability of Target Price Finishing Over Current Price

    4628047 -- Ireland Fund  

    USD 1.43  0.10  7.52%

    CGWM GL probability of target price tool provides mechanism to make assumptions about upside and downside potential of CGWM GL AF USD A performance during a given time horizon utilizing its historical volatility. Please specify CGWM GL time horizon, a valid symbol (red box) and a target price (blue box) you would like CGWM GL odds to be computed. Check also Trending Equities.
    Horizon     30 Days    Login   to change
    Symbol:
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    CGWM GL Target Price Odds to finish over

    Current PriceHorizonTarget PriceOdds to move above current price in 30 days
     1.43 30 days 1.43  ABOUT 28.35%
    Based on normal probability distribution, the odds of CGWM GL to move above current price in 30 days from now is about 28.35% (This CGWM GL AF USD A probability density function shows the probability of CGWM GL Fund to fall within a particular range of prices over 30 days) .
    Assuming 30 trading days horizon, CGWM GL AF USD A has beta of -0.019 . This suggests as returns on benchmark increase, returns on holding CGWM GL are expected to decrease at a much smaller rate. During bear market, however, CGWM GL AF USD A is likely to outperform the market. Additionally CGWM GL AF USD A has an alpha of 0.9394 implying that it can potentially generate 0.9394% excess return over DOW after adjusting for the inherited market risk (beta).
     CGWM GL Price Density 
     
          
    Current Price   Target Price   
    α
    Alpha over DOW
    =0.94
    β
    Beta against DOW=0.02
    σ
    Overall volatility
    =0.61
    Ir
    Information ratio =0.19

    CGWM GL Alerts

    CGWM GL Alerts and Suggestions

    CGWM GL AF is not yet fully synchronised with the market data
    CGWM GL AF generates negative expected return over the last 30 days
    CGWM GL AF may become a speculative penny stock
    Check also Trending Equities. Please also try Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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