Correlation Between Cars and Selective Insurance
Can any of the company-specific risk be diversified away by investing in both Cars and Selective 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 Cars and Selective Insurance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cars Inc and Selective Insurance Group, you can compare the effects of market volatilities on Cars and Selective 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 Cars with a short position of Selective Insurance. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cars and Selective Insurance.
Diversification Opportunities for Cars and Selective Insurance
0.68 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Cars and Selective is 0.68. Overlapping area represents the amount of risk that can be diversified away by holding Cars Inc and Selective Insurance Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Selective Insurance and Cars 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 Cars Inc are associated (or correlated) with Selective Insurance. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Selective Insurance has no effect on the direction of Cars i.e., Cars and Selective Insurance go up and down completely randomly.
Pair Corralation between Cars and Selective Insurance
Assuming the 90 days horizon Cars Inc is expected to generate 1.43 times more return on investment than Selective Insurance. However, Cars is 1.43 times more volatile than Selective Insurance Group. It trades about 0.1 of its potential returns per unit of risk. Selective Insurance Group is currently generating about 0.08 per unit of risk. If you would invest 1,570 in Cars Inc on September 15, 2024 and sell it today you would earn a total of 250.00 from holding Cars Inc or generate 15.92% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Cars Inc vs. Selective Insurance Group
Performance |
Timeline |
Cars Inc |
Selective Insurance |
Cars and Selective Insurance Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Cars and Selective Insurance
The main advantage of trading using opposite Cars and Selective Insurance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cars position performs unexpectedly, Selective 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 Selective Insurance will offset losses from the drop in Selective Insurance's long position.Cars vs. Superior Plus Corp | Cars vs. SIVERS SEMICONDUCTORS AB | Cars vs. Norsk Hydro ASA | Cars vs. Reliance Steel Aluminum |
Selective Insurance vs. Insurance Australia Group | Selective Insurance vs. Superior Plus Corp | Selective Insurance vs. SIVERS SEMICONDUCTORS AB | Selective Insurance vs. CHINA HUARONG ENERHD 50 |
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 Analyst Advice module to analyst recommendations and target price estimates broken down by several categories.
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