Correlation Between PIE Industrial and Tex Cycle
Can any of the company-specific risk be diversified away by investing in both PIE Industrial and Tex Cycle 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 PIE Industrial and Tex Cycle into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between PIE Industrial Bhd and Tex Cycle Technology, you can compare the effects of market volatilities on PIE Industrial and Tex Cycle 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 PIE Industrial with a short position of Tex Cycle. Check out your portfolio center. Please also check ongoing floating volatility patterns of PIE Industrial and Tex Cycle.
Diversification Opportunities for PIE Industrial and Tex Cycle
-0.5 | Correlation Coefficient |
Very good diversification
The 3 months correlation between PIE and Tex is -0.5. Overlapping area represents the amount of risk that can be diversified away by holding PIE Industrial Bhd and Tex Cycle Technology in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Tex Cycle Technology and PIE Industrial 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 PIE Industrial Bhd are associated (or correlated) with Tex Cycle. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Tex Cycle Technology has no effect on the direction of PIE Industrial i.e., PIE Industrial and Tex Cycle go up and down completely randomly.
Pair Corralation between PIE Industrial and Tex Cycle
Assuming the 90 days trading horizon PIE Industrial Bhd is expected to generate 3.91 times more return on investment than Tex Cycle. However, PIE Industrial is 3.91 times more volatile than Tex Cycle Technology. It trades about 0.2 of its potential returns per unit of risk. Tex Cycle Technology is currently generating about -0.28 per unit of risk. If you would invest 519.00 in PIE Industrial Bhd on August 30, 2024 and sell it today you would earn a total of 56.00 from holding PIE Industrial Bhd or generate 10.79% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 95.45% |
| Values | Daily Returns |
PIE Industrial Bhd vs. Tex Cycle Technology
Performance |
| Timeline |
| PIE Industrial Bhd |
| Tex Cycle Technology |
PIE Industrial and Tex Cycle Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with PIE Industrial and Tex Cycle
The main advantage of trading using opposite PIE Industrial and Tex Cycle positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if PIE Industrial position performs unexpectedly, Tex Cycle 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 Tex Cycle will offset losses from the drop in Tex Cycle's long position.| PIE Industrial vs. Choo Bee Metal | PIE Industrial vs. Shangri La Hotels | PIE Industrial vs. British American Tobacco | PIE Industrial vs. Sungei Bagan Rubber |
| Tex Cycle vs. Computer Forms Bhd | Tex Cycle vs. Minetech Resources Bhd | Tex Cycle vs. Sunzen Biotech Bhd | Tex Cycle vs. Hengyuan Refining |
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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