CFPA HM (Germany) Performance

The organization shows Beta (market volatility) of 0.0 which signifies that the returns on MARKET and CFPA HM are completely uncorrelated. Although it is extremely important to respect CFPA HM historical returns, it is better to be realistic regarding the information on equity current trending patterns. The philosophy towards foreseeing future performance of any etf is to evaluate the business as a whole together with its past performance including all available fundamental and technical indicators. By reviewing CFPA HM technical indicators you can today evaluate if the expected return of 0.0% will be sustainable into the future.
Horizon     30 Days    Login   to change

CFPA HM Relative Risk vs. Return Landscape

If you would invest  0.00  in CFPA HM on November 15, 2018 and sell it today you would earn a total of  0.00  from holding CFPA HM or generate 0.0% return on investment over 30 days. CFPA HM is generating negative expected returns and assumes 0.0% volatility on return distribution over the 30 days horizon. Simply put, 0% of equities are less volatile than CFPA HM and 99% of equity instruments are likely to generate higher returns than the company over the next 30 trading days.
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CFPA HM Market Risk Analysis

Sharpe Ratio = 0.0
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Based on monthly moving average CFPA HM is performing at about 0% of its full potential. If added to a well diversified portfolio the total return can be enhanced and market risk can be reduced. You can increase risk-adjusted return of CFPA HM by adding it to a well-diversified portfolio.

CFPA HM Performance Rating

CFPA HM Risk Adjusted Performance Analysis

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Risk-Adjusted Performance

Over the last 30 days CFPA HM has generated negative risk-adjusted returns adding no value to investors with long positions.

CFPA HM Alerts

Equity Alerts and Improvement Suggestions

CFPA HM is not yet fully synchronised with the market data
CFPA HM has some characteristics of a very speculative penny stock
Check also Trending Equities. Please also try Pattern Recognition module to use different pattern recognition models to time the market across multiple global exchanges.
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