Correlation Between Tex Cycle and Oriental Food
Can any of the company-specific risk be diversified away by investing in both Tex Cycle and Oriental Food 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 Cycle and Oriental Food into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Tex Cycle Technology and Oriental Food Industries, you can compare the effects of market volatilities on Tex Cycle and Oriental Food 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 Cycle with a short position of Oriental Food. Check out your portfolio center. Please also check ongoing floating volatility patterns of Tex Cycle and Oriental Food.
Diversification Opportunities for Tex Cycle and Oriental Food
0.75 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Tex and Oriental is 0.75. Overlapping area represents the amount of risk that can be diversified away by holding Tex Cycle Technology and Oriental Food Industries in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Oriental Food Industries and Tex Cycle 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 Cycle Technology are associated (or correlated) with Oriental Food. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Oriental Food Industries has no effect on the direction of Tex Cycle i.e., Tex Cycle and Oriental Food go up and down completely randomly.
Pair Corralation between Tex Cycle and Oriental Food
Assuming the 90 days trading horizon Tex Cycle Technology is expected to under-perform the Oriental Food. But the stock apears to be less risky and, when comparing its historical volatility, Tex Cycle Technology is 1.48 times less risky than Oriental Food. The stock trades about -0.09 of its potential returns per unit of risk. The Oriental Food Industries is currently generating about -0.04 of returns per unit of risk over similar time horizon. If you would invest 159.00 in Oriental Food Industries on December 23, 2024 and sell it today you would lose (9.00) from holding Oriental Food Industries or give up 5.66% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Tex Cycle Technology vs. Oriental Food Industries
Performance |
Timeline |
Tex Cycle Technology |
Oriental Food Industries |
Tex Cycle and Oriental Food Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Tex Cycle and Oriental Food
The main advantage of trading using opposite Tex Cycle and Oriental Food positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Tex Cycle position performs unexpectedly, Oriental Food 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 Oriental Food will offset losses from the drop in Oriental Food's long position.Tex Cycle vs. Coraza Integrated Technology | Tex Cycle vs. Greatech Technology Bhd | Tex Cycle vs. Genetec Technology Bhd | Tex Cycle vs. Cloudpoint Technology Berhad |
Oriental Food vs. Eonmetall Group Bhd | Oriental Food vs. TAS Offshore Bhd | Oriental Food vs. Impiana Hotels Bhd | Oriental Food vs. Choo Bee Metal |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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