Correlation Between Gunkul Engineering and AP Public
Can any of the company-specific risk be diversified away by investing in both Gunkul Engineering and AP Public 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 AP Public 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 AP Public, you can compare the effects of market volatilities on Gunkul Engineering and AP Public 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 AP Public. Check out your portfolio center. Please also check ongoing floating volatility patterns of Gunkul Engineering and AP Public.
Diversification Opportunities for Gunkul Engineering and AP Public
0.64 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Gunkul and AP Public is 0.64. Overlapping area represents the amount of risk that can be diversified away by holding Gunkul Engineering Public and AP Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on AP 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 AP Public. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of AP Public has no effect on the direction of Gunkul Engineering i.e., Gunkul Engineering and AP Public go up and down completely randomly.
Pair Corralation between Gunkul Engineering and AP Public
Assuming the 90 days trading horizon Gunkul Engineering Public is expected to under-perform the AP Public. But the stock apears to be less risky and, when comparing its historical volatility, Gunkul Engineering Public is 1.15 times less risky than AP Public. The stock trades about -0.3 of its potential returns per unit of risk. The AP Public is currently generating about 0.23 of returns per unit of risk over similar time horizon. If you would invest 780.00 in AP Public on November 28, 2024 and sell it today you would earn a total of 110.00 from holding AP Public or generate 14.1% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Gunkul Engineering Public vs. AP Public
Performance |
| Timeline |
| Gunkul Engineering Public |
| AP Public |
Gunkul Engineering and AP Public Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Gunkul Engineering and AP Public
The main advantage of trading using opposite Gunkul Engineering and AP Public positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Gunkul Engineering position performs unexpectedly, AP Public 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 AP Public will offset losses from the drop in AP Public'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 |
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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 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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