Correlation Between Jasmine International and Hwa Fong
Can any of the company-specific risk be diversified away by investing in both Jasmine International and Hwa Fong 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 Jasmine International and Hwa Fong into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Jasmine International Public and Hwa Fong Rubber, you can compare the effects of market volatilities on Jasmine International and Hwa Fong 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 Jasmine International with a short position of Hwa Fong. Check out your portfolio center. Please also check ongoing floating volatility patterns of Jasmine International and Hwa Fong.
Diversification Opportunities for Jasmine International and Hwa Fong
0.13 | Correlation Coefficient |
Average diversification
The 3 months correlation between Jasmine and Hwa is 0.13. Overlapping area represents the amount of risk that can be diversified away by holding Jasmine International Public and Hwa Fong Rubber in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hwa Fong Rubber and Jasmine International 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 Jasmine International Public are associated (or correlated) with Hwa Fong. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hwa Fong Rubber has no effect on the direction of Jasmine International i.e., Jasmine International and Hwa Fong go up and down completely randomly.
Pair Corralation between Jasmine International and Hwa Fong
Assuming the 90 days trading horizon Jasmine International Public is expected to generate 1.6 times more return on investment than Hwa Fong. However, Jasmine International is 1.6 times more volatile than Hwa Fong Rubber. It trades about 0.13 of its potential returns per unit of risk. Hwa Fong Rubber is currently generating about -0.33 per unit of risk. If you would invest 222.00 in Jasmine International Public on August 29, 2024 and sell it today you would earn a total of 12.00 from holding Jasmine International Public or generate 5.41% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Jasmine International Public vs. Hwa Fong Rubber
Performance |
Timeline |
Jasmine International |
Hwa Fong Rubber |
Jasmine International and Hwa Fong Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Jasmine International and Hwa Fong
The main advantage of trading using opposite Jasmine International and Hwa Fong positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Jasmine International position performs unexpectedly, Hwa Fong 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 Hwa Fong will offset losses from the drop in Hwa Fong's long position.Jasmine International vs. Indara Insurance Public | Jasmine International vs. Regional Container Lines | Jasmine International vs. Regional Container Lines | Jasmine International vs. Mahachai Hospital Public |
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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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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