Correlation Between Horace Mann and CNA Financial
Can any of the company-specific risk be diversified away by investing in both Horace Mann and CNA Financial 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 Horace Mann and CNA Financial into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Horace Mann Educators and CNA Financial, you can compare the effects of market volatilities on Horace Mann and CNA Financial 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 Horace Mann with a short position of CNA Financial. Check out your portfolio center. Please also check ongoing floating volatility patterns of Horace Mann and CNA Financial.
Diversification Opportunities for Horace Mann and CNA Financial
0.52 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Horace and CNA is 0.52. Overlapping area represents the amount of risk that can be diversified away by holding Horace Mann Educators and CNA Financial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CNA Financial and Horace Mann 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 Horace Mann Educators are associated (or correlated) with CNA Financial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CNA Financial has no effect on the direction of Horace Mann i.e., Horace Mann and CNA Financial go up and down completely randomly.
Pair Corralation between Horace Mann and CNA Financial
Considering the 90-day investment horizon Horace Mann is expected to generate 1.54 times less return on investment than CNA Financial. In addition to that, Horace Mann is 1.13 times more volatile than CNA Financial. It trades about 0.01 of its total potential returns per unit of risk. CNA Financial is currently generating about 0.01 per unit of volatility. If you would invest 4,215 in CNA Financial on January 25, 2024 and sell it today you would earn a total of 204.00 from holding CNA Financial or generate 4.84% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Horace Mann Educators vs. CNA Financial
Performance |
Timeline |
Horace Mann Educators |
CNA Financial |
Horace Mann and CNA Financial Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Horace Mann and CNA Financial
The main advantage of trading using opposite Horace Mann and CNA Financial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Horace Mann position performs unexpectedly, CNA Financial 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 CNA Financial will offset losses from the drop in CNA Financial's long position.Horace Mann vs. Kemper | Horace Mann vs. RLI Corp | Horace Mann vs. Global Indemnity PLC | Horace Mann vs. Argo Group International |
CNA Financial vs. Selective Insurance Group | CNA Financial vs. Kemper | CNA Financial vs. Donegal Group B | CNA Financial vs. Argo Group International |
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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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