Correlation Between GM and Cheng Uei
Can any of the company-specific risk be diversified away by investing in both GM and Cheng Uei 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 Cheng Uei into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and Cheng Uei Precision, you can compare the effects of market volatilities on GM and Cheng Uei 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 Cheng Uei. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and Cheng Uei.
Diversification Opportunities for GM and Cheng Uei
Average diversification
The 3 months correlation between GM and Cheng is 0.19. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and Cheng Uei Precision in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cheng Uei Precision 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 Cheng Uei. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cheng Uei Precision has no effect on the direction of GM i.e., GM and Cheng Uei go up and down completely randomly.
Pair Corralation between GM and Cheng Uei
Allowing for the 90-day total investment horizon General Motors is expected to generate 1.45 times more return on investment than Cheng Uei. However, GM is 1.45 times more volatile than Cheng Uei Precision. It trades about -0.03 of its potential returns per unit of risk. Cheng Uei Precision is currently generating about -0.18 per unit of risk. If you would invest 5,404 in General Motors on December 26, 2024 and sell it today you would lose (309.00) from holding General Motors or give up 5.72% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 91.8% |
Values | Daily Returns |
General Motors vs. Cheng Uei Precision
Performance |
Timeline |
General Motors |
Cheng Uei Precision |
GM and Cheng Uei Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with GM and Cheng Uei
The main advantage of trading using opposite GM and Cheng Uei positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, Cheng Uei 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 Cheng Uei will offset losses from the drop in Cheng Uei's long position.The idea behind General Motors and Cheng Uei Precision 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.Cheng Uei vs. Inventec Corp | Cheng Uei vs. Compal Electronics | Cheng Uei vs. Ichia Technologies | Cheng Uei vs. Pan International Industrial 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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