Correlation Between Pyung Hwa and Korea Information
Can any of the company-specific risk be diversified away by investing in both Pyung Hwa and Korea Information 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 Pyung Hwa and Korea Information into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Pyung Hwa Industrial and Korea Information Engineering, you can compare the effects of market volatilities on Pyung Hwa and Korea Information 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 Pyung Hwa with a short position of Korea Information. Check out your portfolio center. Please also check ongoing floating volatility patterns of Pyung Hwa and Korea Information.
Diversification Opportunities for Pyung Hwa and Korea Information
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Pyung and Korea is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding Pyung Hwa Industrial and Korea Information Engineering in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Korea Information and Pyung Hwa 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 Pyung Hwa Industrial are associated (or correlated) with Korea Information. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Korea Information has no effect on the direction of Pyung Hwa i.e., Pyung Hwa and Korea Information go up and down completely randomly.
Pair Corralation between Pyung Hwa and Korea Information
Assuming the 90 days trading horizon Pyung Hwa Industrial is expected to generate 0.81 times more return on investment than Korea Information. However, Pyung Hwa Industrial is 1.23 times less risky than Korea Information. It trades about -0.15 of its potential returns per unit of risk. Korea Information Engineering is currently generating about -0.13 per unit of risk. If you would invest 100,600 in Pyung Hwa Industrial on September 2, 2024 and sell it today you would lose (10,300) from holding Pyung Hwa Industrial or give up 10.24% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Pyung Hwa Industrial vs. Korea Information Engineering
Performance |
| Timeline |
| Pyung Hwa Industrial |
| Korea Information |
Pyung Hwa and Korea Information Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Pyung Hwa and Korea Information
The main advantage of trading using opposite Pyung Hwa and Korea Information positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Pyung Hwa position performs unexpectedly, Korea Information 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 Korea Information will offset losses from the drop in Korea Information's long position.| Pyung Hwa vs. AptaBio Therapeutics | Pyung Hwa vs. Daewoo SBI SPAC | Pyung Hwa vs. Dream Security co | Pyung Hwa vs. Microfriend |
| Korea Information vs. Dongsin Engineering Construction | Korea Information vs. Doosan Fuel Cell | Korea Information vs. Daishin Balance 1 | Korea Information vs. Total Soft Bank |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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