Correlation Between CHINA HUARONG and Hartford Financial
Can any of the company-specific risk be diversified away by investing in both CHINA HUARONG and Hartford Financial 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 CHINA HUARONG and Hartford Financial into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CHINA HUARONG ENERHD 50 and The Hartford Financial, you can compare the effects of market volatilities on CHINA HUARONG and Hartford Financial 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 CHINA HUARONG with a short position of Hartford Financial. Check out your portfolio center. Please also check ongoing floating volatility patterns of CHINA HUARONG and Hartford Financial.
Diversification Opportunities for CHINA HUARONG and Hartford Financial
0.19 | Correlation Coefficient |
Average diversification
The 3 months correlation between CHINA and Hartford is 0.19. Overlapping area represents the amount of risk that can be diversified away by holding CHINA HUARONG ENERHD 50 and The Hartford Financial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on The Hartford Financial and CHINA HUARONG 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 CHINA HUARONG ENERHD 50 are associated (or correlated) with Hartford Financial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of The Hartford Financial has no effect on the direction of CHINA HUARONG i.e., CHINA HUARONG and Hartford Financial go up and down completely randomly.
Pair Corralation between CHINA HUARONG and Hartford Financial
Assuming the 90 days trading horizon CHINA HUARONG ENERHD 50 is expected to generate 18.85 times more return on investment than Hartford Financial. However, CHINA HUARONG is 18.85 times more volatile than The Hartford Financial. It trades about 0.14 of its potential returns per unit of risk. The Hartford Financial is currently generating about 0.05 per unit of risk. If you would invest 0.05 in CHINA HUARONG ENERHD 50 on September 13, 2024 and sell it today you would earn a total of 0.10 from holding CHINA HUARONG ENERHD 50 or generate 200.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
CHINA HUARONG ENERHD 50 vs. The Hartford Financial
Performance |
Timeline |
CHINA HUARONG ENERHD |
The Hartford Financial |
CHINA HUARONG and Hartford Financial Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with CHINA HUARONG and Hartford Financial
The main advantage of trading using opposite CHINA HUARONG and Hartford Financial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CHINA HUARONG position performs unexpectedly, Hartford Financial 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 Hartford Financial will offset losses from the drop in Hartford Financial's long position.CHINA HUARONG vs. WILLIS LEASE FIN | CHINA HUARONG vs. SAFETY MEDICAL PROD | CHINA HUARONG vs. AVITA Medical | CHINA HUARONG vs. CarsalesCom |
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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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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