Correlation Between GM and Guangzhou Fangbang
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By analyzing existing cross correlation between General Motors and Guangzhou Fangbang Electronics, you can compare the effects of market volatilities on GM and Guangzhou Fangbang 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 Guangzhou Fangbang. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and Guangzhou Fangbang.
Diversification Opportunities for GM and Guangzhou Fangbang
0.59 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between GM and Guangzhou is 0.59. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and Guangzhou Fangbang Electronics in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Guangzhou Fangbang 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 Guangzhou Fangbang. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Guangzhou Fangbang has no effect on the direction of GM i.e., GM and Guangzhou Fangbang go up and down completely randomly.
Pair Corralation between GM and Guangzhou Fangbang
Allowing for the 90-day total investment horizon General Motors is expected to under-perform the Guangzhou Fangbang. But the stock apears to be less risky and, when comparing its historical volatility, General Motors is 1.54 times less risky than Guangzhou Fangbang. The stock trades about -0.07 of its potential returns per unit of risk. The Guangzhou Fangbang Electronics is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest 3,642 in Guangzhou Fangbang Electronics on September 29, 2024 and sell it today you would earn a total of 125.00 from holding Guangzhou Fangbang Electronics or generate 3.43% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 90.91% |
Values | Daily Returns |
General Motors vs. Guangzhou Fangbang Electronics
Performance |
Timeline |
General Motors |
Guangzhou Fangbang |
GM and Guangzhou Fangbang Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with GM and Guangzhou Fangbang
The main advantage of trading using opposite GM and Guangzhou Fangbang positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, Guangzhou Fangbang 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 Guangzhou Fangbang will offset losses from the drop in Guangzhou Fangbang's long position.The idea behind General Motors and Guangzhou Fangbang Electronics 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.Guangzhou Fangbang vs. Guangxi Wuzhou Communications | Guangzhou Fangbang vs. Chenzhou Jingui Silver | Guangzhou Fangbang vs. JCHX Mining Management | Guangzhou Fangbang vs. Railway Signal Communication |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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