GMFL Risk Analysis And Volatility Evaluation

GMFL -- USA Etf  

USD 27.82  0.00  0.00%

Our approach to determining volatility of a etf 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 GMFL which you can use to evaluate future volatility of the entity. Please check out GMFL Risk Adjusted Performance of 0.01 to validate if risk estimate we provide are consistent with the epected return of 0.0%.
 Time Horizon     30 Days    Login   to change

GMFL Technical Analysis

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

Given the investment horizon of 30 days, GMFL has beta of 0.0 . This indicates unless we do not have required data, the returns on DOW and GMFL are completely uncorrelated. Furthermore, GMFLIt does not look like GMFL alpha can have any bearing on the equity current valuation.
 Predicted Return Density 
Alpha over DOW
Beta against DOW=0.00
Overall volatility
Information ratio =0.14

Actual Return Volatility

GMFL inherits 0.0% risk (volatility on return distribution) over the 30 days horizon. DOW inherits 1.3896% risk (volatility on return distribution) over the 30 days horizon.
 Performance (%) 

Market Risk Breakdown

GMFL Volatility Factors

30 Days Market Risk

Unknown risk

Chance of Distress in 24 months

Unknown Distress

30 Days Economic Sensitivity


Investment Outlook

GMFL Investment Opportunity
DOW has a standard deviation of returns of 1.39 and is 9.223372036854776E16 times more volatile than GMFL. 0% of all equities and portfolios are less risky than GMFL. Compared to the overall equity markets, volatility of historical daily returns of GMFL is lower than 0 (%) of all global equities and portfolios over the last 30 days.
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.