Correlation Between Cheng Mei and Information Technology
Can any of the company-specific risk be diversified away by investing in both Cheng Mei and Information Technology 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 Cheng Mei and Information Technology into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cheng Mei Materials and Information Technology Total, you can compare the effects of market volatilities on Cheng Mei and Information Technology 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 Cheng Mei with a short position of Information Technology. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cheng Mei and Information Technology.
Diversification Opportunities for Cheng Mei and Information Technology
-0.42 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Cheng and Information is -0.42. Overlapping area represents the amount of risk that can be diversified away by holding Cheng Mei Materials and Information Technology Total in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Information Technology and Cheng Mei 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 Cheng Mei Materials are associated (or correlated) with Information Technology. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Information Technology has no effect on the direction of Cheng Mei i.e., Cheng Mei and Information Technology go up and down completely randomly.
Pair Corralation between Cheng Mei and Information Technology
Assuming the 90 days trading horizon Cheng Mei Materials is expected to generate 0.75 times more return on investment than Information Technology. However, Cheng Mei Materials is 1.34 times less risky than Information Technology. It trades about 0.13 of its potential returns per unit of risk. Information Technology Total is currently generating about 0.05 per unit of risk. If you would invest 1,270 in Cheng Mei Materials on September 13, 2024 and sell it today you would earn a total of 60.00 from holding Cheng Mei Materials or generate 4.72% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Cheng Mei Materials vs. Information Technology Total
Performance |
Timeline |
Cheng Mei Materials |
Information Technology |
Cheng Mei and Information Technology Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Cheng Mei and Information Technology
The main advantage of trading using opposite Cheng Mei and Information Technology positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cheng Mei position performs unexpectedly, Information Technology 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 Information Technology will offset losses from the drop in Information Technology's long position.Cheng Mei vs. AU Optronics | Cheng Mei vs. Innolux Corp | Cheng Mei vs. Ruentex Development Co | Cheng Mei vs. WiseChip Semiconductor |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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