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

    F00000MQVQ -- Ireland Fund  

    USD 16.00  0.12  0.74%

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

    Current PriceHorizonTarget PriceOdds to move above current price in 30 days
     16.00 30 days 16.00  ABOUT 34.08%
    Based on normal probability distribution, the odds of Wellington to move above current price in 30 days from now is about 34.08% (This Wellington US Core HY Bd USD S Acc probability density function shows the probability of Wellington Fund to fall within a particular range of prices over 30 days) .
    Assuming 30 trading days horizon, Wellington has beta of 0.0505 suggesting as returns on market go up, Wellington average returns are expected to increase less than the benchmark. However during bear market, the loss on holding Wellington US Core HY Bd USD S Acc will be expected to be much smaller as well. Additionally Wellington US Core HY Bd USD S Acc has an alpha of 0.1247 implying that it can potentially generate 0.1247% excess return over DOW after adjusting for the inherited market risk (beta).
     Wellington Price Density 
    Alpha over DOW
    Beta against DOW=0.05
    Overall volatility
    Information ratio =0.62

    Wellington Alerts

    Wellington Alerts and Suggestions

    Wellington US Core is not yet fully synchronised with the market data
    The fund retains about 6.34% of its assets under management (AUM) in cash
    Additionally see Investing Opportunities. Please also try Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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