Correlation Between Westone Information and Hefei Metalforming
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By analyzing existing cross correlation between Westone Information Industry and Hefei Metalforming Mach, you can compare the effects of market volatilities on Westone Information and Hefei Metalforming 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 Westone Information with a short position of Hefei Metalforming. Check out your portfolio center. Please also check ongoing floating volatility patterns of Westone Information and Hefei Metalforming.
Diversification Opportunities for Westone Information and Hefei Metalforming
0.9 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Westone and Hefei is 0.9. Overlapping area represents the amount of risk that can be diversified away by holding Westone Information Industry and Hefei Metalforming Mach in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hefei Metalforming Mach and Westone Information 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 Westone Information Industry are associated (or correlated) with Hefei Metalforming. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hefei Metalforming Mach has no effect on the direction of Westone Information i.e., Westone Information and Hefei Metalforming go up and down completely randomly.
Pair Corralation between Westone Information and Hefei Metalforming
Assuming the 90 days trading horizon Westone Information is expected to generate 11.87 times less return on investment than Hefei Metalforming. But when comparing it to its historical volatility, Westone Information Industry is 1.46 times less risky than Hefei Metalforming. It trades about 0.01 of its potential returns per unit of risk. Hefei Metalforming Mach is currently generating about 0.1 of returns per unit of risk over similar time horizon. If you would invest 730.00 in Hefei Metalforming Mach on September 3, 2024 and sell it today you would earn a total of 49.00 from holding Hefei Metalforming Mach or generate 6.71% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Westone Information Industry vs. Hefei Metalforming Mach
Performance |
| Timeline |
| Westone Information |
| Hefei Metalforming Mach |
Westone Information and Hefei Metalforming Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Westone Information and Hefei Metalforming
The main advantage of trading using opposite Westone Information and Hefei Metalforming positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Westone Information position performs unexpectedly, Hefei Metalforming 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 Hefei Metalforming will offset losses from the drop in Hefei Metalforming's long position.| Westone Information vs. Agricultural Bank of | Westone Information vs. China Construction Bank | Westone Information vs. Postal Savings Bank | Westone Information vs. Bank of Communications |
| Hefei Metalforming vs. Cultural Investment Holdings | Hefei Metalforming vs. Gome Telecom Equipment | Hefei Metalforming vs. Bus Online Co | Hefei Metalforming vs. Holitech Technology Co |
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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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