BNY Mellon (Ireland) Risk Analysis And Volatility Evaluation

Our approach towards foreseeing volatility of a fund is to use all available market data together with company specific technical indicators that cannot be diversified away. We have found twenty-one technical indicators for BNY Mellon Glbl Eq Higher Inc GBP M Acc which you can use to evaluate future volatility of the entity. Please confirm BNY Mellon Glbl to double-check if risk estimate we provide are consistent with the epected return of 0.0%.
 Time Horizon     30 Days    Login   to change

BNY Mellon Glbl Technical Analysis

Transformation
We are not able to run technical analysis function on this symbol. We either do not have that equity or its historical data is not available at this time. Please try again later.

Projected Return Density Against Market

Assuming 30 trading days horizon, BNY Mellon has beta of 0.0 . This indicates unless we do not have required data, the returns on DOW and BNY Mellon are completely uncorrelated. Furthermore, BNY Mellon Glbl Eq Higher Inc GBP M AccIt does not look like BNY Mellon alpha can have any bearing on the equity current valuation.
α
Alpha over DOW
=0.00
β
Beta against DOW=0.00
σ
Overall volatility
=0.00
Ir
Information ratio =0.00

Actual Return Volatility

BNY Mellon Glbl Eq Higher Inc GBP M Acc accepts 0.0% volatility on return distribution over the 30 days horizon. DOW inherits 0.63% risk (volatility on return distribution) over the 30 days horizon.
 Performance (%) 
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Investment Outlook

BNY Mellon Investment Opportunity
DOW has a standard deviation of returns of 0.63 and is 9.223372036854776E16 times more volatile than BNY Mellon Glbl Eq Higher Inc GBP M Acc. 0% of all equities and portfolios are less risky than BNY Mellon. Compared to the overall equity markets, volatility of historical daily returns of BNY Mellon Glbl Eq Higher Inc GBP M Acc is lower than 0 (%) of all global equities and portfolios over the last 30 days.

BNY Mellon Current Risk Indicators

Please also check Risk vs Return Analysis. Please also try Insider Screener module to find insiders across different sectors to evaluate their impact on performance.