Correlation Between GM and Hang Seng
Can any of the company-specific risk be diversified away by investing in both GM and Hang Seng 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 GM and Hang Seng into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and Hang Seng Bank, you can compare the effects of market volatilities on GM and Hang Seng 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 GM with a short position of Hang Seng. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and Hang Seng.
Diversification Opportunities for GM and Hang Seng
Poor diversification
The 3 months correlation between GM and Hang is 0.68. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and Hang Seng Bank in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hang Seng Bank and GM 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 General Motors are associated (or correlated) with Hang Seng. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hang Seng Bank has no effect on the direction of GM i.e., GM and Hang Seng go up and down completely randomly.
Pair Corralation between GM and Hang Seng
Allowing for the 90-day total investment horizon GM is expected to generate 1.81 times less return on investment than Hang Seng. In addition to that, GM is 1.24 times more volatile than Hang Seng Bank. It trades about 0.06 of its total potential returns per unit of risk. Hang Seng Bank is currently generating about 0.14 per unit of volatility. If you would invest 958.00 in Hang Seng Bank on September 23, 2024 and sell it today you would earn a total of 172.00 from holding Hang Seng Bank or generate 17.95% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 98.48% |
Values | Daily Returns |
General Motors vs. Hang Seng Bank
Performance |
Timeline |
General Motors |
Hang Seng Bank |
GM and Hang Seng Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with GM and Hang Seng
The main advantage of trading using opposite GM and Hang Seng positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, Hang Seng 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 Hang Seng will offset losses from the drop in Hang Seng's long position.The idea behind General Motors and Hang Seng Bank 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.Hang Seng vs. China Merchants Bank | Hang Seng vs. HDFC Bank Limited | Hang Seng vs. ICICI Bank Limited | Hang Seng vs. PT Bank Central |
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 Commodity Directory module to find actively traded commodities issued by global exchanges.
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