Correlation Between Chung Hwa and Tehmag Foods
Can any of the company-specific risk be diversified away by investing in both Chung Hwa and Tehmag Foods 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 Chung Hwa and Tehmag Foods into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Chung Hwa Food and Tehmag Foods, you can compare the effects of market volatilities on Chung Hwa and Tehmag Foods 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 Chung Hwa with a short position of Tehmag Foods. Check out your portfolio center. Please also check ongoing floating volatility patterns of Chung Hwa and Tehmag Foods.
Diversification Opportunities for Chung Hwa and Tehmag Foods
0.32 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Chung and Tehmag is 0.32. Overlapping area represents the amount of risk that can be diversified away by holding Chung Hwa Food and Tehmag Foods in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Tehmag Foods and Chung Hwa 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 Chung Hwa Food are associated (or correlated) with Tehmag Foods. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Tehmag Foods has no effect on the direction of Chung Hwa i.e., Chung Hwa and Tehmag Foods go up and down completely randomly.
Pair Corralation between Chung Hwa and Tehmag Foods
Assuming the 90 days trading horizon Chung Hwa Food is expected to under-perform the Tehmag Foods. But the stock apears to be less risky and, when comparing its historical volatility, Chung Hwa Food is 1.31 times less risky than Tehmag Foods. The stock trades about -0.03 of its potential returns per unit of risk. The Tehmag Foods is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest 23,863 in Tehmag Foods on October 7, 2024 and sell it today you would earn a total of 7,187 from holding Tehmag Foods or generate 30.12% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Chung Hwa Food vs. Tehmag Foods
Performance |
Timeline |
Chung Hwa Food |
Tehmag Foods |
Chung Hwa and Tehmag Foods Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Chung Hwa and Tehmag Foods
The main advantage of trading using opposite Chung Hwa and Tehmag Foods positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Chung Hwa position performs unexpectedly, Tehmag Foods 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 Tehmag Foods will offset losses from the drop in Tehmag Foods' long position.Chung Hwa vs. Uni President Enterprises Corp | Chung Hwa vs. Tingyi Holding Corp | Chung Hwa vs. Lien Hwa Industrial | Chung Hwa vs. Great Wall Enterprise |
Tehmag Foods vs. Uni President Enterprises Corp | Tehmag Foods vs. Tingyi Holding Corp | Tehmag Foods vs. Lien Hwa Industrial | Tehmag Foods vs. Great Wall Enterprise |
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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