Correlation Between GM and Datasea
Can any of the company-specific risk be diversified away by investing in both GM and Datasea 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 Datasea into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and Datasea, you can compare the effects of market volatilities on GM and Datasea 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 Datasea. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and Datasea.
Diversification Opportunities for GM and Datasea
Very weak diversification
The 3 months correlation between GM and Datasea is 0.58. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and Datasea in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Datasea 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 Datasea. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Datasea has no effect on the direction of GM i.e., GM and Datasea go up and down completely randomly.
Pair Corralation between GM and Datasea
Allowing for the 90-day total investment horizon General Motors is expected to generate 0.84 times more return on investment than Datasea. However, General Motors is 1.19 times less risky than Datasea. It trades about 0.01 of its potential returns per unit of risk. Datasea is currently generating about -0.11 per unit of risk. If you would invest 5,418 in General Motors on October 26, 2024 and sell it today you would earn a total of 4.00 from holding General Motors or generate 0.07% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 94.74% |
Values | Daily Returns |
General Motors vs. Datasea
Performance |
Timeline |
General Motors |
Datasea |
GM and Datasea Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with GM and Datasea
The main advantage of trading using opposite GM and Datasea positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, Datasea 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 Datasea will offset losses from the drop in Datasea's long position.The idea behind General Motors and Datasea 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.Datasea vs. authID Inc | Datasea vs. Priority Technology Holdings | Datasea vs. Fuse Science | Datasea vs. Taoping |
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 Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.
Other Complementary Tools
Idea Optimizer Use advanced portfolio builder with pre-computed micro ideas to build optimal portfolio | |
Watchlist Optimization Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm | |
Headlines Timeline Stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity | |
Portfolio Center All portfolio management and optimization tools to improve performance of your portfolios | |
Money Flow Index Determine momentum by analyzing Money Flow Index and other technical indicators |