Correlation Between Ihuman and Fidelis Insurance
Can any of the company-specific risk be diversified away by investing in both Ihuman 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 Ihuman and Fidelis Insurance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ihuman Inc and Fidelis Insurance Holdings, you can compare the effects of market volatilities on Ihuman 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 Ihuman with a short position of Fidelis Insurance. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ihuman and Fidelis Insurance.
Diversification Opportunities for Ihuman and Fidelis Insurance
-0.43 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Ihuman and Fidelis is -0.43. Overlapping area represents the amount of risk that can be diversified away by holding Ihuman Inc and Fidelis Insurance Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fidelis Insurance and Ihuman 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 Ihuman Inc 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 Ihuman i.e., Ihuman and Fidelis Insurance go up and down completely randomly.
Pair Corralation between Ihuman and Fidelis Insurance
Allowing for the 90-day total investment horizon Ihuman Inc is expected to under-perform the Fidelis Insurance. In addition to that, Ihuman is 1.59 times more volatile than Fidelis Insurance Holdings. It trades about -0.03 of its total potential returns per unit of risk. Fidelis Insurance Holdings is currently generating about 0.1 per unit of volatility. If you would invest 1,202 in Fidelis Insurance Holdings on September 12, 2024 and sell it today you would earn a total of 750.00 from holding Fidelis Insurance Holdings or generate 62.4% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Ihuman Inc vs. Fidelis Insurance Holdings
Performance |
| Timeline |
| Ihuman Inc |
| Fidelis Insurance |
Ihuman and Fidelis Insurance Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ihuman and Fidelis Insurance
The main advantage of trading using opposite Ihuman and Fidelis Insurance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ihuman 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.| Ihuman vs. Boqii Holding Limited | Ihuman vs. Lixiang Education Holding | Ihuman vs. Huize Holding | Ihuman vs. Kuke Music Holding |
| Fidelis Insurance vs. IPG Photonics | Fidelis Insurance vs. Consol Energy | Fidelis Insurance vs. Asbury Automotive Group | Fidelis Insurance vs. Summit Materials |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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