Correlation Between Shinhan WTI and KCC Engineering
Can any of the company-specific risk be diversified away by investing in both Shinhan WTI and KCC Engineering 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 Shinhan WTI and KCC Engineering into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Shinhan WTI Futures and KCC Engineering Construction, you can compare the effects of market volatilities on Shinhan WTI and KCC Engineering 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 Shinhan WTI with a short position of KCC Engineering. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shinhan WTI and KCC Engineering.
Diversification Opportunities for Shinhan WTI and KCC Engineering
0.07 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Shinhan and KCC is 0.07. Overlapping area represents the amount of risk that can be diversified away by holding Shinhan WTI Futures and KCC Engineering Construction in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on KCC Engineering Cons and Shinhan WTI 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 Shinhan WTI Futures are associated (or correlated) with KCC Engineering. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of KCC Engineering Cons has no effect on the direction of Shinhan WTI i.e., Shinhan WTI and KCC Engineering go up and down completely randomly.
Pair Corralation between Shinhan WTI and KCC Engineering
Assuming the 90 days trading horizon Shinhan WTI Futures is expected to generate 1.39 times more return on investment than KCC Engineering. However, Shinhan WTI is 1.39 times more volatile than KCC Engineering Construction. It trades about 0.0 of its potential returns per unit of risk. KCC Engineering Construction is currently generating about -0.09 per unit of risk. If you would invest 732,000 in Shinhan WTI Futures on September 23, 2024 and sell it today you would lose (8,000) from holding Shinhan WTI Futures or give up 1.09% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 96.83% |
Values | Daily Returns |
Shinhan WTI Futures vs. KCC Engineering Construction
Performance |
Timeline |
Shinhan WTI Futures |
KCC Engineering Cons |
Shinhan WTI and KCC Engineering Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Shinhan WTI and KCC Engineering
The main advantage of trading using opposite Shinhan WTI and KCC Engineering positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shinhan WTI position performs unexpectedly, KCC Engineering 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 KCC Engineering will offset losses from the drop in KCC Engineering's long position.Shinhan WTI vs. Samsung Electronics Co | Shinhan WTI vs. Samsung Electronics Co | Shinhan WTI vs. LG Energy Solution | Shinhan WTI vs. SK Hynix |
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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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