Correlation Between Keyang Electric and Daewon Chemical
Can any of the company-specific risk be diversified away by investing in both Keyang Electric and Daewon Chemical 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 Keyang Electric and Daewon Chemical into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Keyang Electric Machinery and Daewon Chemical Co, you can compare the effects of market volatilities on Keyang Electric and Daewon Chemical 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 Keyang Electric with a short position of Daewon Chemical. Check out your portfolio center. Please also check ongoing floating volatility patterns of Keyang Electric and Daewon Chemical.
Diversification Opportunities for Keyang Electric and Daewon Chemical
-0.24 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Keyang and Daewon is -0.24. Overlapping area represents the amount of risk that can be diversified away by holding Keyang Electric Machinery and Daewon Chemical Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Daewon Chemical and Keyang Electric 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 Keyang Electric Machinery are associated (or correlated) with Daewon Chemical. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Daewon Chemical has no effect on the direction of Keyang Electric i.e., Keyang Electric and Daewon Chemical go up and down completely randomly.
Pair Corralation between Keyang Electric and Daewon Chemical
Assuming the 90 days trading horizon Keyang Electric Machinery is expected to generate 0.71 times more return on investment than Daewon Chemical. However, Keyang Electric Machinery is 1.41 times less risky than Daewon Chemical. It trades about -0.03 of its potential returns per unit of risk. Daewon Chemical Co is currently generating about -0.04 per unit of risk. If you would invest 596,000 in Keyang Electric Machinery on October 29, 2024 and sell it today you would lose (216,500) from holding Keyang Electric Machinery or give up 36.33% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Keyang Electric Machinery vs. Daewon Chemical Co
Performance |
Timeline |
Keyang Electric Machinery |
Daewon Chemical |
Keyang Electric and Daewon Chemical Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Keyang Electric and Daewon Chemical
The main advantage of trading using opposite Keyang Electric and Daewon Chemical positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Keyang Electric position performs unexpectedly, Daewon Chemical 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 Daewon Chemical will offset losses from the drop in Daewon Chemical's long position.Keyang Electric vs. Korea Petro Chemical | Keyang Electric vs. Youngchang Chemical Co | Keyang Electric vs. Namhae Chemical | Keyang Electric vs. Kyung In Synthetic Corp |
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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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