NYSE Backtesting

NYA -- USA Index  

 13,089  114.56  0.88%

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

NYSE 'What if' Analysis

July 24, 2019
0.00
No Change 0.00  0.0 
In 2 months and 31 days
October 22, 2019
0.00
If you would invest  0.00  in NYSE on July 24, 2019 and sell it all today you would earn a total of 0.00 from holding NYSE or generate 0.0% return on investment in NYSE over 90 days.

NYSE Upside/Downside Indicators

Downside Deviation1.3
Information Ratio0.0153
Maximum Drawdown4.97
Value At Risk(2.51)
Potential Upside1.38

NYSE Market Premium Indicators

Risk Adjusted Performance0.0042
Total Risk Alpha0.0202
Sortino Ratio0.013

NYSE Backtested Returns

NYSE has Sharpe Ratio of -0.0099 which conveys that the entity had -0.0099% of return per unit of standard deviation over the last 3 months. Macroaxis philosophy towards estimating risk of any index is to look at both systematic and un-systematic factors of the business, including all available market data and technical indicators. NYSE exposes twenty-eight different technical indicators which can help you to evaluate volatility that cannot be diversified away. The index secures Beta (Market Risk) of 0.0 which conveys that the returns on MARKET and NYSE are completely uncorrelated. Even though it is essential to pay attention to NYSE price patterns, it is always good to be careful when utilizing equity historical price patterns. Macroaxis philosophy towards estimating future performance of any index is to check both, its past performance charts as well as the business as a whole, including all available technical indicators. NYSE exposes twenty-eight different technical indicators which can help you to evaluate its performance.
Advice Volatility Trend Exposure Correlations
15 days auto-correlation 0.43 
correlation synergy

Average predictability

NYSE has average predictability. Overlapping area represents the amount of predictability between NYSE time series from July 24, 2019 to September 7, 2019 and September 7, 2019 to October 22, 2019. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of NYSE price movement. The serial correlation of 0.43 indicates that just about 43.0% of current NYSE price fluctuation can be explain by its past prices.
Correlation Coefficient0.43
Spearman Rank Test0.27
Residual Average0.0
Price Variance38785.31

NYSE lagged returns against current returns

 Current and Lagged Values 
      Timeline 

NYSE regressed lagged prices vs. current prices

 Current vs Lagged Prices 
      Timeline 

NYSE Lagged Returns

 Regressed Prices 
      Timeline 

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See also NYSE Hype Analysis, NYSE Correlation, Portfolio Optimization, NYSE Volatility as well as analyze NYSE Alpha and Beta and NYSE Performance. Please also try Content Syndication module to quickly integrate customizable finance content to your own investment portal.
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