Correlation Between Wan Hai and Kung Sing
Can any of the company-specific risk be diversified away by investing in both Wan Hai and Kung Sing 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 Wan Hai and Kung Sing into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Wan Hai Lines and Kung Sing Engineering, you can compare the effects of market volatilities on Wan Hai and Kung Sing 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 Wan Hai with a short position of Kung Sing. Check out your portfolio center. Please also check ongoing floating volatility patterns of Wan Hai and Kung Sing.
Diversification Opportunities for Wan Hai and Kung Sing
Significant diversification
The 3 months correlation between Wan and Kung is 0.07. Overlapping area represents the amount of risk that can be diversified away by holding Wan Hai Lines and Kung Sing Engineering in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kung Sing Engineering and Wan Hai 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 Wan Hai Lines are associated (or correlated) with Kung Sing. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kung Sing Engineering has no effect on the direction of Wan Hai i.e., Wan Hai and Kung Sing go up and down completely randomly.
Pair Corralation between Wan Hai and Kung Sing
Assuming the 90 days trading horizon Wan Hai Lines is expected to under-perform the Kung Sing. In addition to that, Wan Hai is 1.44 times more volatile than Kung Sing Engineering. It trades about -0.2 of its total potential returns per unit of risk. Kung Sing Engineering is currently generating about -0.12 per unit of volatility. If you would invest 1,110 in Kung Sing Engineering on September 16, 2024 and sell it today you would lose (45.00) from holding Kung Sing Engineering or give up 4.05% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Wan Hai Lines vs. Kung Sing Engineering
Performance |
Timeline |
Wan Hai Lines |
Kung Sing Engineering |
Wan Hai and Kung Sing Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Wan Hai and Kung Sing
The main advantage of trading using opposite Wan Hai and Kung Sing positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Wan Hai position performs unexpectedly, Kung Sing 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 Kung Sing will offset losses from the drop in Kung Sing's long position.The idea behind Wan Hai Lines and Kung Sing Engineering pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.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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