Correlation Between China Steel and Chang Hwa
Can any of the company-specific risk be diversified away by investing in both China Steel and Chang Hwa 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 China Steel and Chang Hwa into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between China Steel Chemical and Chang Hwa Commercial, you can compare the effects of market volatilities on China Steel and Chang Hwa 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 China Steel with a short position of Chang Hwa. Check out your portfolio center. Please also check ongoing floating volatility patterns of China Steel and Chang Hwa.
Diversification Opportunities for China Steel and Chang Hwa
-0.11 | Correlation Coefficient |
Good diversification
The 3 months correlation between China and Chang is -0.11. Overlapping area represents the amount of risk that can be diversified away by holding China Steel Chemical and Chang Hwa Commercial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Chang Hwa Commercial and China Steel 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 China Steel Chemical are associated (or correlated) with Chang Hwa. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Chang Hwa Commercial has no effect on the direction of China Steel i.e., China Steel and Chang Hwa go up and down completely randomly.
Pair Corralation between China Steel and Chang Hwa
Assuming the 90 days trading horizon China Steel Chemical is expected to generate 1.52 times more return on investment than Chang Hwa. However, China Steel is 1.52 times more volatile than Chang Hwa Commercial. It trades about 0.76 of its potential returns per unit of risk. Chang Hwa Commercial is currently generating about -0.11 per unit of risk. If you would invest 9,210 in China Steel Chemical on November 27, 2024 and sell it today you would earn a total of 550.00 from holding China Steel Chemical or generate 5.97% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
China Steel Chemical vs. Chang Hwa Commercial
Performance |
| Timeline |
| China Steel Chemical |
| Chang Hwa Commercial |
China Steel and Chang Hwa Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with China Steel and Chang Hwa
The main advantage of trading using opposite China Steel and Chang Hwa positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if China Steel position performs unexpectedly, Chang Hwa 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 Chang Hwa will offset losses from the drop in Chang Hwa's long position.| China Steel vs. Formosa Chemicals Fibre | China Steel vs. Formosa Plastics Corp | China Steel vs. Cheng Shin Rubber | China Steel vs. President Chain Store |
| Chang Hwa vs. Hua Nan Financial | Chang Hwa vs. First Financial Holding | Chang Hwa vs. Sinopac Financial Holdings | Chang Hwa vs. Taishin Financial Holding |
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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