Correlation Between Kenon Holdings and Fidelis Insurance
Can any of the company-specific risk be diversified away by investing in both Kenon Holdings and Fidelis Insurance 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 Kenon Holdings and Fidelis Insurance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kenon Holdings and Fidelis Insurance Holdings, you can compare the effects of market volatilities on Kenon Holdings and Fidelis Insurance 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 Kenon Holdings with a short position of Fidelis Insurance. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kenon Holdings and Fidelis Insurance.
Diversification Opportunities for Kenon Holdings and Fidelis Insurance
0.68 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Kenon and Fidelis is 0.68. Overlapping area represents the amount of risk that can be diversified away by holding Kenon Holdings and Fidelis Insurance Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fidelis Insurance and Kenon Holdings 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 Kenon Holdings are associated (or correlated) with Fidelis Insurance. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Fidelis Insurance has no effect on the direction of Kenon Holdings i.e., Kenon Holdings and Fidelis Insurance go up and down completely randomly.
Pair Corralation between Kenon Holdings and Fidelis Insurance
Considering the 90-day investment horizon Kenon Holdings is expected to generate 0.84 times more return on investment than Fidelis Insurance. However, Kenon Holdings is 1.19 times less risky than Fidelis Insurance. It trades about 0.17 of its potential returns per unit of risk. Fidelis Insurance Holdings is currently generating about 0.06 per unit of risk. If you would invest 2,560 in Kenon Holdings on September 15, 2024 and sell it today you would earn a total of 488.00 from holding Kenon Holdings or generate 19.06% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Kenon Holdings vs. Fidelis Insurance Holdings
Performance |
Timeline |
Kenon Holdings |
Fidelis Insurance |
Kenon Holdings and Fidelis Insurance Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kenon Holdings and Fidelis Insurance
The main advantage of trading using opposite Kenon Holdings and Fidelis Insurance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kenon Holdings position performs unexpectedly, Fidelis Insurance 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 Fidelis Insurance will offset losses from the drop in Fidelis Insurance's long position.Kenon Holdings vs. Vistra Energy Corp | Kenon Holdings vs. Pampa Energia SA | Kenon Holdings vs. NRG Energy | Kenon Holdings vs. TransAlta Corp |
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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 Global Correlations module to find global opportunities by holding instruments from different markets.
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