Correlation Between Seaboard and White Mountains
Can any of the company-specific risk be diversified away by investing in both Seaboard 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 Seaboard and White Mountains into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Seaboard and White Mountains Insurance, you can compare the effects of market volatilities on Seaboard 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 Seaboard with a short position of White Mountains. Check out your portfolio center. Please also check ongoing floating volatility patterns of Seaboard and White Mountains.
Diversification Opportunities for Seaboard and White Mountains
-0.76 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Seaboard and White is -0.76. Overlapping area represents the amount of risk that can be diversified away by holding Seaboard 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 Seaboard 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 Seaboard 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 Seaboard i.e., Seaboard and White Mountains go up and down completely randomly.
Pair Corralation between Seaboard and White Mountains
Considering the 90-day investment horizon Seaboard is expected to under-perform the White Mountains. But the stock apears to be less risky and, when comparing its historical volatility, Seaboard is 1.12 times less risky than White Mountains. The stock trades about -0.05 of its potential returns per unit of risk. The White Mountains Insurance is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 146,089 in White Mountains Insurance on August 27, 2024 and sell it today you would earn a total of 52,745 from holding White Mountains Insurance or generate 36.1% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Seaboard vs. White Mountains Insurance
Performance |
| Timeline |
| Seaboard |
| White Mountains Insurance |
Seaboard and White Mountains Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Seaboard and White Mountains
The main advantage of trading using opposite Seaboard and White Mountains positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Seaboard 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.| Seaboard vs. White Mountains Insurance | Seaboard vs. Cable One | Seaboard vs. NVR Inc | Seaboard vs. Alexanders |
| White Mountains vs. NI Holdings | White Mountains vs. Donegal Group A | White Mountains vs. Donegal Group B | White Mountains vs. The Hanover Insurance |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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