Correlation Between GS Engineering and Cytogen
Can any of the company-specific risk be diversified away by investing in both GS Engineering and Cytogen 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 GS Engineering and Cytogen into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between GS Engineering Construction and Cytogen, you can compare the effects of market volatilities on GS Engineering and Cytogen 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 GS Engineering with a short position of Cytogen. Check out your portfolio center. Please also check ongoing floating volatility patterns of GS Engineering and Cytogen.
Diversification Opportunities for GS Engineering and Cytogen
0.27 | Correlation Coefficient |
Modest diversification
The 3 months correlation between 006360 and Cytogen is 0.27. Overlapping area represents the amount of risk that can be diversified away by holding GS Engineering Construction and Cytogen in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cytogen and GS 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 GS Engineering Construction are associated (or correlated) with Cytogen. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cytogen has no effect on the direction of GS Engineering i.e., GS Engineering and Cytogen go up and down completely randomly.
Pair Corralation between GS Engineering and Cytogen
Assuming the 90 days trading horizon GS Engineering Construction is expected to under-perform the Cytogen. But the stock apears to be less risky and, when comparing its historical volatility, GS Engineering Construction is 1.19 times less risky than Cytogen. The stock trades about -0.1 of its potential returns per unit of risk. The Cytogen is currently generating about -0.07 of returns per unit of risk over similar time horizon. If you would invest 465,500 in Cytogen on November 7, 2024 and sell it today you would lose (16,000) from holding Cytogen or give up 3.44% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 94.44% |
Values | Daily Returns |
GS Engineering Construction vs. Cytogen
Performance |
Timeline |
GS Engineering Const |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Cytogen |
GS Engineering and Cytogen Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with GS Engineering and Cytogen
The main advantage of trading using opposite GS Engineering and Cytogen positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GS Engineering position performs unexpectedly, Cytogen 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 Cytogen will offset losses from the drop in Cytogen's long position.GS Engineering vs. People Technology | GS Engineering vs. Vina Technology Co | GS Engineering vs. Hotel Shilla Co | GS Engineering vs. Samsung Publishing Co |
Cytogen vs. Vitzro Tech Co | Cytogen vs. Samsung Life Insurance | Cytogen vs. ADTechnology CoLtd | Cytogen vs. Narae Nanotech Corp |
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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