Correlation Between Hengyuan Refining and Tex Cycle
Can any of the company-specific risk be diversified away by investing in both Hengyuan Refining 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 Hengyuan Refining and Tex Cycle into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hengyuan Refining and Tex Cycle Technology, you can compare the effects of market volatilities on Hengyuan Refining 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 Hengyuan Refining with a short position of Tex Cycle. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hengyuan Refining and Tex Cycle.
Diversification Opportunities for Hengyuan Refining and Tex Cycle
0.48 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Hengyuan and Tex is 0.48. Overlapping area represents the amount of risk that can be diversified away by holding Hengyuan Refining 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 Hengyuan Refining 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 Hengyuan Refining 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 Hengyuan Refining i.e., Hengyuan Refining and Tex Cycle go up and down completely randomly.
Pair Corralation between Hengyuan Refining and Tex Cycle
Assuming the 90 days trading horizon Hengyuan Refining is expected to under-perform the Tex Cycle. In addition to that, Hengyuan Refining is 1.01 times more volatile than Tex Cycle Technology. It trades about -0.05 of its total potential returns per unit of risk. Tex Cycle Technology is currently generating about 0.03 per unit of volatility. If you would invest 82.00 in Tex Cycle Technology on November 28, 2024 and sell it today you would earn a total of 23.00 from holding Tex Cycle Technology or generate 28.05% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 99.79% |
Values | Daily Returns |
Hengyuan Refining vs. Tex Cycle Technology
Performance |
Timeline |
Hengyuan Refining |
Tex Cycle Technology |
Hengyuan Refining and Tex Cycle Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hengyuan Refining and Tex Cycle
The main advantage of trading using opposite Hengyuan Refining and Tex Cycle positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hengyuan Refining 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.Hengyuan Refining vs. Lyc Healthcare Bhd | Hengyuan Refining vs. Mercury Industries Bhd | Hengyuan Refining vs. RHB Bank Bhd | Hengyuan Refining vs. YX Precious Metals |
Tex Cycle vs. PMB Technology Bhd | Tex Cycle vs. Press Metal Bhd | Tex Cycle vs. Eonmetall Group Bhd | Tex Cycle vs. Sungei Bagan Rubber |
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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