Correlation Between Aluminumof China and HANOVER INSURANCE
Can any of the company-specific risk be diversified away by investing in both Aluminumof China and HANOVER 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 Aluminumof China and HANOVER INSURANCE into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Aluminum of and HANOVER INSURANCE, you can compare the effects of market volatilities on Aluminumof China and HANOVER 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 Aluminumof China with a short position of HANOVER INSURANCE. Check out your portfolio center. Please also check ongoing floating volatility patterns of Aluminumof China and HANOVER INSURANCE.
Diversification Opportunities for Aluminumof China and HANOVER INSURANCE
-0.15 | Correlation Coefficient |
Good diversification
The 3 months correlation between Aluminumof and HANOVER is -0.15. Overlapping area represents the amount of risk that can be diversified away by holding Aluminum of and HANOVER INSURANCE in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on HANOVER INSURANCE and Aluminumof China 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 Aluminum of are associated (or correlated) with HANOVER INSURANCE. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of HANOVER INSURANCE has no effect on the direction of Aluminumof China i.e., Aluminumof China and HANOVER INSURANCE go up and down completely randomly.
Pair Corralation between Aluminumof China and HANOVER INSURANCE
Assuming the 90 days horizon Aluminum of is expected to under-perform the HANOVER INSURANCE. In addition to that, Aluminumof China is 1.72 times more volatile than HANOVER INSURANCE. It trades about -0.19 of its total potential returns per unit of risk. HANOVER INSURANCE is currently generating about -0.2 per unit of volatility. If you would invest 15,405 in HANOVER INSURANCE on September 24, 2024 and sell it today you would lose (805.00) from holding HANOVER INSURANCE or give up 5.23% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Aluminum of vs. HANOVER INSURANCE
Performance |
Timeline |
Aluminumof China |
HANOVER INSURANCE |
Aluminumof China and HANOVER INSURANCE Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Aluminumof China and HANOVER INSURANCE
The main advantage of trading using opposite Aluminumof China and HANOVER INSURANCE positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Aluminumof China position performs unexpectedly, HANOVER 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 HANOVER INSURANCE will offset losses from the drop in HANOVER INSURANCE's long position.Aluminumof China vs. Norsk Hydro ASA | Aluminumof China vs. Norsk Hydro ASA | Aluminumof China vs. Alcoa Corp | Aluminumof China vs. AMAG Austria Metall |
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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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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