Correlation Between Pax High and Parametric Commodity
Can any of the company-specific risk be diversified away by investing in both Pax High and Parametric Commodity at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Pax High and Parametric Commodity into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Pax High Yield and Parametric Modity Strategy, you can compare the effects of market volatilities on Pax High and Parametric Commodity and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Pax High with a short position of Parametric Commodity. Check out your portfolio center. Please also check ongoing floating volatility patterns of Pax High and Parametric Commodity.
Diversification Opportunities for Pax High and Parametric Commodity
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Pax and Parametric is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding Pax High Yield and Parametric Modity Strategy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Parametric Commodity and Pax High is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Pax High Yield are associated (or correlated) with Parametric Commodity. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Parametric Commodity has no effect on the direction of Pax High i.e., Pax High and Parametric Commodity go up and down completely randomly.
Pair Corralation between Pax High and Parametric Commodity
Assuming the 90 days horizon Pax High is expected to generate 7.07 times less return on investment than Parametric Commodity. But when comparing it to its historical volatility, Pax High Yield is 2.71 times less risky than Parametric Commodity. It trades about 0.08 of its potential returns per unit of risk. Parametric Modity Strategy is currently generating about 0.21 of returns per unit of risk over similar time horizon. If you would invest 615.00 in Parametric Modity Strategy on December 29, 2024 and sell it today you would earn a total of 45.00 from holding Parametric Modity Strategy or generate 7.32% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Pax High Yield vs. Parametric Modity Strategy
Performance |
Timeline |
Pax High Yield |
Parametric Commodity |
Pax High and Parametric Commodity Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Pax High and Parametric Commodity
The main advantage of trading using opposite Pax High and Parametric Commodity positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Pax High position performs unexpectedly, Parametric Commodity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Parametric Commodity will offset losses from the drop in Parametric Commodity's long position.Pax High vs. Putnam Convertible Securities | Pax High vs. Rationalpier 88 Convertible | Pax High vs. Gabelli Convertible And | Pax High vs. Absolute Convertible Arbitrage |
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Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Idea Analyzer module to analyze all characteristics, volatility and risk-adjusted return of Macroaxis ideas.
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