Correlation Between Duksan Hi and Wireless Power
Can any of the company-specific risk be diversified away by investing in both Duksan Hi and Wireless Power 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 Duksan Hi and Wireless Power into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Duksan Hi Metal and Wireless Power Amplifier, you can compare the effects of market volatilities on Duksan Hi and Wireless Power 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 Duksan Hi with a short position of Wireless Power. Check out your portfolio center. Please also check ongoing floating volatility patterns of Duksan Hi and Wireless Power.
Diversification Opportunities for Duksan Hi and Wireless Power
0.64 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Duksan and Wireless is 0.64. Overlapping area represents the amount of risk that can be diversified away by holding Duksan Hi Metal and Wireless Power Amplifier in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Wireless Power Amplifier and Duksan Hi 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 Duksan Hi Metal are associated (or correlated) with Wireless Power. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Wireless Power Amplifier has no effect on the direction of Duksan Hi i.e., Duksan Hi and Wireless Power go up and down completely randomly.
Pair Corralation between Duksan Hi and Wireless Power
Assuming the 90 days trading horizon Duksan Hi Metal is expected to under-perform the Wireless Power. In addition to that, Duksan Hi is 1.2 times more volatile than Wireless Power Amplifier. It trades about -0.07 of its total potential returns per unit of risk. Wireless Power Amplifier is currently generating about 0.0 per unit of volatility. If you would invest 302,000 in Wireless Power Amplifier on October 9, 2024 and sell it today you would lose (17,000) from holding Wireless Power Amplifier or give up 5.63% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Duksan Hi Metal vs. Wireless Power Amplifier
Performance |
Timeline |
Duksan Hi Metal |
Wireless Power Amplifier |
Duksan Hi and Wireless Power Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Duksan Hi and Wireless Power
The main advantage of trading using opposite Duksan Hi and Wireless Power positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Duksan Hi position performs unexpectedly, Wireless Power 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 Wireless Power will offset losses from the drop in Wireless Power's long position.Duksan Hi vs. Korea Electronic Certification | Duksan Hi vs. PJ Electronics Co | Duksan Hi vs. KyungIn Electronics Co | Duksan Hi vs. SungMoon Electronics Co |
Wireless Power vs. PJ Metal Co | Wireless Power vs. Choil Aluminum | Wireless Power vs. DRB Industrial Co | Wireless Power vs. Korea Air Svc |
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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