Correlation Between Tetragon Financial and CNH Industrial
Can any of the company-specific risk be diversified away by investing in both Tetragon Financial and CNH Industrial 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 Tetragon Financial and CNH Industrial into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Tetragon Financial Group and CNH Industrial NV, you can compare the effects of market volatilities on Tetragon Financial and CNH Industrial 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 Tetragon Financial with a short position of CNH Industrial. Check out your portfolio center. Please also check ongoing floating volatility patterns of Tetragon Financial and CNH Industrial.
Diversification Opportunities for Tetragon Financial and CNH Industrial
0.32 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Tetragon and CNH is 0.32. Overlapping area represents the amount of risk that can be diversified away by holding Tetragon Financial Group and CNH Industrial NV in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CNH Industrial NV and Tetragon Financial 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 Tetragon Financial Group are associated (or correlated) with CNH Industrial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CNH Industrial NV has no effect on the direction of Tetragon Financial i.e., Tetragon Financial and CNH Industrial go up and down completely randomly.
Pair Corralation between Tetragon Financial and CNH Industrial
Assuming the 90 days trading horizon Tetragon Financial Group is expected to generate 0.39 times more return on investment than CNH Industrial. However, Tetragon Financial Group is 2.57 times less risky than CNH Industrial. It trades about 0.37 of its potential returns per unit of risk. CNH Industrial NV is currently generating about 0.02 per unit of risk. If you would invest 1,410 in Tetragon Financial Group on October 15, 2024 and sell it today you would earn a total of 185.00 from holding Tetragon Financial Group or generate 13.12% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Tetragon Financial Group vs. CNH Industrial NV
Performance |
Timeline |
Tetragon Financial |
CNH Industrial NV |
Tetragon Financial and CNH Industrial Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Tetragon Financial and CNH Industrial
The main advantage of trading using opposite Tetragon Financial and CNH Industrial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Tetragon Financial position performs unexpectedly, CNH Industrial 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 CNH Industrial will offset losses from the drop in CNH Industrial's long position.Tetragon Financial vs. SupplyMe Capital PLC | Tetragon Financial vs. SM Energy Co | Tetragon Financial vs. FuelCell Energy | Tetragon Financial vs. Grand Vision Media |
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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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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