NYSE Backtesting

NYSE -- USA Index  

 13,474  3.74  0.0278%

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
 Time Horizon     30 Days    Login   to change

NYSE 'What if' Analysis

December 24, 2017
No Change 0.00  0.0%
In 31 days
January 23, 2018
If you would invest  0.00  in NYSE on December 24, 2017 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 30 days. NYSE is entity of United States. It is traded as Index on Index exchange.

NYSE Upside/Downside Indicators


NYSE Market Premium Indicators

NYSE lagged returns against current returns

 Current and Lagged Values 

NYSE regressed lagged prices vs. current prices

 Current vs Lagged Prices 

NYSE Backtested Returns

NYSE has Sharpe Ratio of 0.68 which conveys that NYSE had 0.68% of return per unit of standard deviation over the last 1 month. Our philosophy towards estimating volatility of a index 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 NYSE which you can use to evaluate future volatility of the organization. The index secures Beta (Market Risk) of 0.0 which conveys that the returns on MARKET and NYSE are completely uncorrelated. Although it is vital to follow to NYSE price patterns, it is good to be conservative about what you can actually do with the information regarding equity historical price patterns. The philosophy towards estimating future performance of any index is to evaluate the business as a whole together with its past performance including all available fundamental and technical indicators. By reviewing NYSE technical indicators you can currently evaluate if the expected return of 0.2661% will be sustainable into the future.
Advice Volatility Trend Exposure Correlations
15 days auto-correlation 0.87 

Very good predictability

NYSE has very good predictability. Overlapping area represents the amount of predictability between NYSE time series from December 24, 2017 to January 8, 2018 and January 8, 2018 to January 23, 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 NYSE price movement. The serial correlation of 0.87 indicates that approximately 87.0% of current NYSE price fluctuation can be explain by its past prices.
Correlation Coefficient 0.87
Spearman Rank Test 0.95
Price Variance 10098.5
Lagged Price Variance 13554.55

NYSE Lagged Returns

 Regressed Prices 

NYSE Performance vs DOW

The median price of NYSE for the period between Sun, Dec 24, 2017 and Tue, Jan 23, 2018 is 13106.6 with a coefficient of variation of 1.83. The daily time series for the period is distributed with a sample standard deviation of 239.84, arithmetic mean of 13078.21, and mean deviation of 205.06. The Index received some media coverage during the period.
Price Growth (%)  
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