Correlation Between KPX Green and Korea Petro
Can any of the company-specific risk be diversified away by investing in both KPX Green and Korea Petro 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 KPX Green and Korea Petro into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between KPX Green Chemical and Korea Petro Chemical, you can compare the effects of market volatilities on KPX Green and Korea Petro 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 KPX Green with a short position of Korea Petro. Check out your portfolio center. Please also check ongoing floating volatility patterns of KPX Green and Korea Petro.
Diversification Opportunities for KPX Green and Korea Petro
0.06 | Correlation Coefficient |
Significant diversification
The 3 months correlation between KPX and Korea is 0.06. Overlapping area represents the amount of risk that can be diversified away by holding KPX Green Chemical and Korea Petro Chemical in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Korea Petro Chemical and KPX Green 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 KPX Green Chemical are associated (or correlated) with Korea Petro. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Korea Petro Chemical has no effect on the direction of KPX Green i.e., KPX Green and Korea Petro go up and down completely randomly.
Pair Corralation between KPX Green and Korea Petro
Assuming the 90 days trading horizon KPX Green Chemical is expected to generate 1.12 times more return on investment than Korea Petro. However, KPX Green is 1.12 times more volatile than Korea Petro Chemical. It trades about 0.01 of its potential returns per unit of risk. Korea Petro Chemical is currently generating about -0.04 per unit of risk. If you would invest 670,467 in KPX Green Chemical on November 4, 2024 and sell it today you would lose (30,467) from holding KPX Green Chemical or give up 4.54% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
KPX Green Chemical vs. Korea Petro Chemical
Performance |
| Timeline |
| KPX Green Chemical |
| Korea Petro Chemical |
KPX Green and Korea Petro Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with KPX Green and Korea Petro
The main advantage of trading using opposite KPX Green and Korea Petro positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if KPX Green position performs unexpectedly, Korea Petro 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 Petro will offset losses from the drop in Korea Petro's long position.| KPX Green vs. Asiana Airlines | KPX Green vs. Woori Technology Investment | KPX Green vs. Atinum Investment Co | KPX Green vs. Seoul Semiconductor Co |
| Korea Petro vs. Samyoung Electronics Co | Korea Petro vs. Daewoo Electronic Components | Korea Petro vs. Guyoung Technology Co | Korea Petro vs. Seers Technology |
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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