Correlation Between Bank of Kaohsiung and Chang Hwa
Can any of the company-specific risk be diversified away by investing in both Bank of Kaohsiung 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 Bank of Kaohsiung and Chang Hwa into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank of Kaohsiung and Chang Hwa Commercial, you can compare the effects of market volatilities on Bank of Kaohsiung 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 Bank of Kaohsiung with a short position of Chang Hwa. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of Kaohsiung and Chang Hwa.
Diversification Opportunities for Bank of Kaohsiung and Chang Hwa
0.56 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Bank and Chang is 0.56. Overlapping area represents the amount of risk that can be diversified away by holding Bank of Kaohsiung 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 Bank of Kaohsiung 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 Bank of Kaohsiung 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 Bank of Kaohsiung i.e., Bank of Kaohsiung and Chang Hwa go up and down completely randomly.
Pair Corralation between Bank of Kaohsiung and Chang Hwa
Assuming the 90 days trading horizon Bank of Kaohsiung is expected to generate 1.15 times more return on investment than Chang Hwa. However, Bank of Kaohsiung is 1.15 times more volatile than Chang Hwa Commercial. It trades about 0.02 of its potential returns per unit of risk. Chang Hwa Commercial is currently generating about -0.02 per unit of risk. If you would invest 1,155 in Bank of Kaohsiung on August 29, 2024 and sell it today you would earn a total of 15.00 from holding Bank of Kaohsiung or generate 1.3% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Bank of Kaohsiung vs. Chang Hwa Commercial
Performance |
| Timeline |
| Bank of Kaohsiung |
| Chang Hwa Commercial |
Bank of Kaohsiung and Chang Hwa Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of Kaohsiung and Chang Hwa
The main advantage of trading using opposite Bank of Kaohsiung and Chang Hwa positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of Kaohsiung 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.| Bank of Kaohsiung vs. Taiwan Secom Co | Bank of Kaohsiung vs. TTET Union Corp | Bank of Kaohsiung vs. China Steel Chemical | Bank of Kaohsiung vs. Taiwan Shin Kong |
| Chang Hwa vs. Taiwan Secom Co | Chang Hwa vs. TTET Union Corp | Chang Hwa vs. China Steel Chemical | Chang Hwa vs. Taiwan Shin Kong |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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