Correlation Between Tex Ray and Asia Plastic
Can any of the company-specific risk be diversified away by investing in both Tex Ray and Asia Plastic 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 Tex Ray and Asia Plastic into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Tex Ray Industrial Co and Asia Plastic Recycling, you can compare the effects of market volatilities on Tex Ray and Asia Plastic 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 Tex Ray with a short position of Asia Plastic. Check out your portfolio center. Please also check ongoing floating volatility patterns of Tex Ray and Asia Plastic.
Diversification Opportunities for Tex Ray and Asia Plastic
0.64 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Tex and Asia is 0.64. Overlapping area represents the amount of risk that can be diversified away by holding Tex Ray Industrial Co and Asia Plastic Recycling in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Asia Plastic Recycling and Tex Ray 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 Tex Ray Industrial Co are associated (or correlated) with Asia Plastic. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Asia Plastic Recycling has no effect on the direction of Tex Ray i.e., Tex Ray and Asia Plastic go up and down completely randomly.
Pair Corralation between Tex Ray and Asia Plastic
Assuming the 90 days trading horizon Tex Ray Industrial Co is expected to generate 1.25 times more return on investment than Asia Plastic. However, Tex Ray is 1.25 times more volatile than Asia Plastic Recycling. It trades about -0.07 of its potential returns per unit of risk. Asia Plastic Recycling is currently generating about -0.29 per unit of risk. If you would invest 1,080 in Tex Ray Industrial Co on October 25, 2024 and sell it today you would lose (50.00) from holding Tex Ray Industrial Co or give up 4.63% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Tex Ray Industrial Co vs. Asia Plastic Recycling
Performance |
Timeline |
Tex Ray Industrial |
Asia Plastic Recycling |
Tex Ray and Asia Plastic Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Tex Ray and Asia Plastic
The main advantage of trading using opposite Tex Ray and Asia Plastic positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Tex Ray position performs unexpectedly, Asia Plastic 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 Asia Plastic will offset losses from the drop in Asia Plastic's long position.Tex Ray vs. Tainan Enterprises Co | Tex Ray vs. De Licacy Industrial | Tex Ray vs. Nien Hsing Textile | Tex Ray vs. Wisher Industrial Co |
Asia Plastic vs. Victory New Materials | Asia Plastic vs. Hunya Foods Co | Asia Plastic vs. YCC Parts MFG | Asia Plastic vs. Kwong Fong Industries |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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