Correlation Between Hanover Insurance and Pets At
Can any of the company-specific risk be diversified away by investing in both Hanover Insurance and Pets At 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 Hanover Insurance and Pets At into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between The Hanover Insurance and Pets at Home, you can compare the effects of market volatilities on Hanover Insurance and Pets At 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 Hanover Insurance with a short position of Pets At. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hanover Insurance and Pets At.
Diversification Opportunities for Hanover Insurance and Pets At
0.6 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Hanover and Pets is 0.6. Overlapping area represents the amount of risk that can be diversified away by holding The Hanover Insurance and Pets at Home in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Pets at Home and Hanover Insurance 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 The Hanover Insurance are associated (or correlated) with Pets At. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Pets at Home has no effect on the direction of Hanover Insurance i.e., Hanover Insurance and Pets At go up and down completely randomly.
Pair Corralation between Hanover Insurance and Pets At
Assuming the 90 days horizon Hanover Insurance is expected to generate 3.15 times less return on investment than Pets At. In addition to that, Hanover Insurance is 1.24 times more volatile than Pets at Home. It trades about 0.02 of its total potential returns per unit of risk. Pets at Home is currently generating about 0.08 per unit of volatility. If you would invest 261.00 in Pets at Home on April 21, 2025 and sell it today you would earn a total of 18.00 from holding Pets at Home or generate 6.9% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
The Hanover Insurance vs. Pets at Home
Performance |
Timeline |
Hanover Insurance |
Pets at Home |
Hanover Insurance and Pets At Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hanover Insurance and Pets At
The main advantage of trading using opposite Hanover Insurance and Pets At positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hanover Insurance position performs unexpectedly, Pets At 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 Pets At will offset losses from the drop in Pets At's long position.Hanover Insurance vs. Kingdee International Software | Hanover Insurance vs. Datadog | Hanover Insurance vs. Datang International Power | Hanover Insurance vs. NetSol Technologies |
Pets At vs. HANOVER INSURANCE | Pets At vs. Japan Post Insurance | Pets At vs. The Hanover Insurance | Pets At vs. GAMEON ENTERTAINM TECHS |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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