Etf Backtesting

GAZ -- USA iPath Bloomberg Natural Gas Subindex Total Return ETN  

USD 2,990  2,990  1,285,369%

With this equity back-testing module your can estimate the performance of a buy and hold strategy of Etf and determine expected loss or profit from investing in Etf over given investment horizon. Please also check Etf Hype Analysis, Etf Correlation, Portfolio Optimization, Etf Volatility as well as analyze Etf Alpha and Beta and Etf Performance.
 Time Horizon     30 Days    Login   to change
SymbolX
Backtest

Etf 'What if' Analysis

May 22, 2018
0.00
No Change 0.00  0.0%
In 31 days
June 21, 2018
0.00
If you would invest  0.00  in Etf on May 22, 2018 and sell it all today you would earn a total of 0.00 from holding Etf or generate 0.0% return on investment in Etf over 30 days. Etf is related to or competes with Walmart, Volkswagen Aktiengesellscha, Volkswagen Aktiengesellscha, Volkswagen Aktiengesellscha, Volkswagen Aktiengesellscha, G4S plc, and AMAZON INC. The investment seeks to reflect the returns that are potentially available through an unleveraged investment in the futu...

Etf Upside/Downside Indicators

  

Etf Market Premium Indicators

Etf Backtested Returns

Etf is abnormally risky given 1 month investment horizon. Etf secures Sharpe Ratio (or Efficiency) of 0.5159 which denotes Etf had 0.5159% of return per unit of risk over the last 1 month. Our philosophy towards predicting volatility of a ipath bloomberg natural gas subindex total return etn is to use Etf market data together with company specific technical indicators. We found twenty-one different technical indicators which can help you to evaluate if expected returns of 247.938% are justified by taking the suggested risk. Use Etf to evaluate company specific risk that cannot be diversified away. The organization shows Beta (market volatility) of 0.0 which denotes to the fact that the returns on MARKET and Etf are completely uncorrelated. Although it is essential to pay attention to Etf historical returns, it is also good to be reasonable about what you can actually do with equity current trending patterns. Macroaxis philosophy towards predicting future performance of any ipath bloomberg natural gas subindex total return etn is to look not only at its past charts but also at the business as a whole, including all available fundamental and technical indicators. To evaluate if Etf expected return of 247.938 will be sustainable into the future, we have found twenty-one different technical indicators which can help you to check if the expected returns are sustainable.
Advice Volatility Trend Exposure Correlations
15 days auto-correlation(0.59) 

Good reverse predictability

Etf has good reverse predictability. Overlapping area represents the amount of predictability between Etf time series from May 22, 2018 to June 6, 2018 and June 6, 2018 to June 21, 2018. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Etf price movement. The serial correlation of -0.59 indicates that roughly 59.0% of current Etf price fluctuation can be explain by its past prices. Given that Etf has negative autocorrelation for selected time horizon, investors may consider taking a contrarian position regarding future price movement of Etf for similar time interval.
Correlation Coefficient -0.59
Spearman Rank Test 0.52
Price Variance 2174283.25
Lagged Price Variance 2067740.27

Etf lagged returns against current returns

 Current and Lagged Values 
      Timeline 

Etf regressed lagged prices vs. current prices

 Current vs Lagged Prices 
      Timeline 

Etf Lagged Returns

 Regressed Prices 
      Timeline 

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Analyst Recommendations

Analyst recommendations and target price estimates broken down by several categories
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Please also check Etf Hype Analysis, Etf Correlation, Portfolio Optimization, Etf Volatility as well as analyze Etf Alpha and Beta and Etf Performance. Please also try Coins and Tokens Correlation module to utilize digital token correlation table to build portfolio of cryptocurrencies across multiple exchanges.