Pax High Backtesting

PXHIX -- USA Fund  

USD 6.61  0.01  0.15%

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

Pax High 'What if' Analysis

August 20, 2018
0.00
No Change 0.00  0.0%
In 31 days
September 19, 2018
0.00
If you would invest  0.00  in Pax High on August 20, 2018 and sell it all today you would earn a total of 0.00 from holding Pax High Yield Bond Institutional or generate 0.0% return on investment in Pax High over 30 days. Pax High is related to or competes with BlackRock High, BlackRock High, BlackRock High, BlackRock High, Fidelity Capital, JPMorgan High, and JPMorgan High. The investment seeks high current income as a secondary investment objective, it seeks capital appreciation

Pax High Upside/Downside Indicators

Information Ratio0.96
Maximum Drawdown0.3037
Value At Risk0.15
Potential Upside0.152
  

Pax High Market Premium Indicators

Risk Adjusted Performance0.0583
Jensen Alpha0.0052
Total Risk Alpha0.009653
Treynor Ratio0.1798

Pax High Yield Backtested Returns

We consider Pax High not too risky. Pax High Yield maintains Sharpe Ratio (i.e. Efficiency) of 0.2495 which implies Pax High Yield had 0.2495% of return per unit of risk over the last 1 month. Our philosophy towards forecasting volatility of a fund is to use all available market data together with fund specific technical indicators that cannot be diversified away. We have found twenty-one technical indicators for Pax High Yield which you can use to evaluate future volatility of the fund. Please check Pax High Yield Coefficient Of Variation of 410.39 and Risk Adjusted Performance of 0.0583 to confirm if risk estimate we provide are consistent with the epected return of 0.0217%. The fund holds Beta of 0.0596 which implies as returns on market increase, Pax High returns are expected to increase less than the market. However during bear market, the loss on holding Pax High will be expected to be smaller as well.. Although it is extremely important to respect Pax High Yield current trending patterns, it is better to be realistic regarding the information on equity existing price patterns. The philosophy towards forecasting future performance of any fund is to evaluate the business as a whole together with its past performance including all available fundamental and technical indicators. By analyzing Pax High Yield technical indicators you can presently evaluate if the expected return of 0.0217% will be sustainable into the future.
Advice Volatility Trend Exposure Correlations
15 days auto-correlation 0.44 

Average predictability

Pax High Yield Bond Institutional has average predictability. Overlapping area represents the amount of predictability between Pax High time series from August 20, 2018 to September 4, 2018 and September 4, 2018 to September 19, 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 Pax High Yield price movement. The serial correlation of 0.44 indicates that just about 44.0% of current Pax High price fluctuation can be explain by its past prices.
Correlation Coefficient0.44
Spearman Rank Test0.75
Residual Average0.0
Price Variance0.0

Pax High Yield lagged returns against current returns

 Current and Lagged Values 
      Timeline 

Pax High regressed lagged prices vs. current prices

 Current vs Lagged Prices 
      Timeline 

Pax High Lagged Returns

 Regressed Prices 
      Timeline 

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Additionally take a look at Pax High Hype Analysis, Pax High Correlation, Portfolio Optimization, Pax High Volatility as well as analyze Pax High Alpha and Beta and Pax High Performance. Please also try Fundamentals Matrix module to view fundamentals matrix and analyze how accounts are interrelated and interconnected with each other.
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