Correlation Between GM and CN DATANG
Can any of the company-specific risk be diversified away by investing in both GM and CN DATANG 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 CN DATANG into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and CN DATANG C, you can compare the effects of market volatilities on GM and CN DATANG 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 CN DATANG. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and CN DATANG.
Diversification Opportunities for GM and CN DATANG
Very good diversification
The 3 months correlation between GM and DT7 is -0.49. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and CN DATANG C in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CN DATANG C 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 CN DATANG. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CN DATANG C has no effect on the direction of GM i.e., GM and CN DATANG go up and down completely randomly.
Pair Corralation between GM and CN DATANG
Allowing for the 90-day total investment horizon General Motors is expected to under-perform the CN DATANG. But the stock apears to be less risky and, when comparing its historical volatility, General Motors is 1.39 times less risky than CN DATANG. The stock trades about -0.01 of its potential returns per unit of risk. The CN DATANG C is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 25.00 in CN DATANG C on December 17, 2024 and sell it today you would earn a total of 1.00 from holding CN DATANG C or generate 4.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
General Motors vs. CN DATANG C
Performance |
Timeline |
General Motors |
CN DATANG C |
GM and CN DATANG Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with GM and CN DATANG
The main advantage of trading using opposite GM and CN DATANG positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, CN DATANG 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 CN DATANG will offset losses from the drop in CN DATANG's long position.The idea behind General Motors and CN DATANG C 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.CN DATANG vs. Data3 Limited | CN DATANG vs. SCANDMEDICAL SOLDK 040 | CN DATANG vs. China Datang | CN DATANG vs. DICKER DATA LTD |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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