Correlation Between W R and White Mountains
Can any of the company-specific risk be diversified away by investing in both W R and White Mountains 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 W R and White Mountains into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between W R Berkley and White Mountains Insurance, you can compare the effects of market volatilities on W R and White Mountains 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 W R with a short position of White Mountains. Check out your portfolio center. Please also check ongoing floating volatility patterns of W R and White Mountains.
Diversification Opportunities for W R and White Mountains
-0.03 | Correlation Coefficient |
Good diversification
The 3 months correlation between WRB-PE and White is -0.03. Overlapping area represents the amount of risk that can be diversified away by holding W R Berkley and White Mountains Insurance in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on White Mountains Insurance and W R 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 W R Berkley are associated (or correlated) with White Mountains. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of White Mountains Insurance has no effect on the direction of W R i.e., W R and White Mountains go up and down completely randomly.
Pair Corralation between W R and White Mountains
Assuming the 90 days trading horizon W R Berkley is expected to under-perform the White Mountains. But the preferred stock apears to be less risky and, when comparing its historical volatility, W R Berkley is 1.41 times less risky than White Mountains. The preferred stock trades about -0.36 of its potential returns per unit of risk. The White Mountains Insurance is currently generating about 0.02 of returns per unit of risk over similar time horizon. If you would invest 177,011 in White Mountains Insurance on February 1, 2024 and sell it today you would earn a total of 803.00 from holding White Mountains Insurance or generate 0.45% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
W R Berkley vs. White Mountains Insurance
Performance |
Timeline |
W R Berkley |
White Mountains Insurance |
W R and White Mountains Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with W R and White Mountains
The main advantage of trading using opposite W R and White Mountains positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if W R position performs unexpectedly, White Mountains 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 White Mountains will offset losses from the drop in White Mountains' long position.W R vs. Aspen Insurance Holdings | W R vs. Aspen Insurance Holdings | W R vs. Argo Group International | W R vs. AmTrust Financial Services |
White Mountains vs. Donegal Group B | White Mountains vs. Horace Mann Educators | White Mountains 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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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