Correlation Between Hyundai Heavy and KBSTAR 200TR
Can any of the company-specific risk be diversified away by investing in both Hyundai Heavy and KBSTAR 200TR 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 Hyundai Heavy and KBSTAR 200TR into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hyundai Heavy Industries and KBSTAR 200TR, you can compare the effects of market volatilities on Hyundai Heavy and KBSTAR 200TR 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 Hyundai Heavy with a short position of KBSTAR 200TR. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hyundai Heavy and KBSTAR 200TR.
Diversification Opportunities for Hyundai Heavy and KBSTAR 200TR
0.53 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Hyundai and KBSTAR is 0.53. Overlapping area represents the amount of risk that can be diversified away by holding Hyundai Heavy Industries and KBSTAR 200TR in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on KBSTAR 200TR and Hyundai Heavy 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 Hyundai Heavy Industries are associated (or correlated) with KBSTAR 200TR. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of KBSTAR 200TR has no effect on the direction of Hyundai Heavy i.e., Hyundai Heavy and KBSTAR 200TR go up and down completely randomly.
Pair Corralation between Hyundai Heavy and KBSTAR 200TR
Assuming the 90 days trading horizon Hyundai Heavy Industries is expected to generate 1.57 times more return on investment than KBSTAR 200TR. However, Hyundai Heavy is 1.57 times more volatile than KBSTAR 200TR. It trades about 0.06 of its potential returns per unit of risk. KBSTAR 200TR is currently generating about 0.03 per unit of risk. If you would invest 5,093,120 in Hyundai Heavy Industries on August 28, 2024 and sell it today you would earn a total of 2,966,880 from holding Hyundai Heavy Industries or generate 58.25% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Hyundai Heavy Industries vs. KBSTAR 200TR
Performance |
| Timeline |
| Hyundai Heavy Industries |
| KBSTAR 200TR |
Hyundai Heavy and KBSTAR 200TR Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Hyundai Heavy and KBSTAR 200TR
The main advantage of trading using opposite Hyundai Heavy and KBSTAR 200TR positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hyundai Heavy position performs unexpectedly, KBSTAR 200TR 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 KBSTAR 200TR will offset losses from the drop in KBSTAR 200TR's long position.| Hyundai Heavy vs. Samsung Electronics Co | Hyundai Heavy vs. Samsung Electronics Co | Hyundai Heavy vs. Hyundai Motor Co | Hyundai Heavy vs. Hyundai Motor |
| KBSTAR 200TR vs. Busan Industrial Co | KBSTAR 200TR vs. Busan Ind | KBSTAR 200TR vs. Mirae Asset Daewoo | KBSTAR 200TR vs. Shinhan WTI Futures |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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