ANIMA Star (Ireland) Probability of Target Price Finishing Over Current Price

    F00000W4CU -- Ireland Fund  

    EUR 4.68  0.02  0.43%

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

    Current PriceHorizonTarget PriceOdds to move above current price in 30 days
     4.68 30 days 4.68  ABOUT 12.66%
    Based on normal probability distribution, the odds of ANIMA Star to move above current price in 30 days from now is about 12.66% (This ANIMA Star Bond B Acc probability density function shows the probability of ANIMA Star Fund to fall within a particular range of prices over 30 days) .
    Assuming 30 trading days horizon, ANIMA Star has beta of 0.0048 suggesting as returns on market go up, ANIMA Star average returns are expected to increase less than the benchmark. However during bear market, the loss on holding ANIMA Star Bond B Acc will be expected to be much smaller as well. Additionally ANIMA Star Bond B Acc has a negative alpha implying that the risk taken by holding this equity is not justified. The company is significantly underperforming DOW
     ANIMA Star Price Density 
          Price 
    α
    Alpha over DOW
    =0.01
    β
    Beta against DOW=0.0048
    σ
    Overall volatility
    =2.39
    Ir
    Information ratio =1.01

    ANIMA Star Alerts

    ANIMA Star Alerts and Suggestions

    ANIMA Star Bond is not yet fully synchronised with the market data
    The fund retains about 61.38% of its assets under management (AUM) in cash
    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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