Correlation Between Gunkul Engineering and CK Power
Can any of the company-specific risk be diversified away by investing in both Gunkul Engineering and CK 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 Gunkul Engineering and CK Power into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Gunkul Engineering Public and CK Power Public, you can compare the effects of market volatilities on Gunkul Engineering and CK 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 Gunkul Engineering with a short position of CK Power. Check out your portfolio center. Please also check ongoing floating volatility patterns of Gunkul Engineering and CK Power.
Diversification Opportunities for Gunkul Engineering and CK Power
0.87 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Gunkul and CKP is 0.87. Overlapping area represents the amount of risk that can be diversified away by holding Gunkul Engineering Public and CK Power Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CK Power Public and Gunkul Engineering 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 Gunkul Engineering Public are associated (or correlated) with CK Power. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CK Power Public has no effect on the direction of Gunkul Engineering i.e., Gunkul Engineering and CK Power go up and down completely randomly.
Pair Corralation between Gunkul Engineering and CK Power
Assuming the 90 days trading horizon Gunkul Engineering Public is expected to under-perform the CK Power. In addition to that, Gunkul Engineering is 1.11 times more volatile than CK Power Public. It trades about -0.19 of its total potential returns per unit of risk. CK Power Public is currently generating about -0.12 per unit of volatility. If you would invest 368.00 in CK Power Public on September 14, 2024 and sell it today you would lose (46.00) from holding CK Power Public or give up 12.5% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Gunkul Engineering Public vs. CK Power Public
Performance |
Timeline |
Gunkul Engineering Public |
CK Power Public |
Gunkul Engineering and CK Power Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Gunkul Engineering and CK Power
The main advantage of trading using opposite Gunkul Engineering and CK Power positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Gunkul Engineering position performs unexpectedly, CK 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 CK Power will offset losses from the drop in CK Power's long position.Gunkul Engineering vs. Gulf Energy Development | Gunkul Engineering vs. Energy Absolute Public | Gunkul Engineering vs. Banpu Public | Gunkul Engineering vs. WHA Public |
CK Power vs. Energy Absolute Public | CK Power vs. BCPG Public | CK Power vs. Bangkok Expressway and | CK Power vs. Gulf Energy Development |
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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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