Correlation Between GM and Check Cap
Can any of the company-specific risk be diversified away by investing in both GM and Check Cap 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 Check Cap into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and Check Cap, you can compare the effects of market volatilities on GM and Check Cap 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 Check Cap. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and Check Cap.
Diversification Opportunities for GM and Check Cap
Pay attention - limited upside
The 3 months correlation between GM and Check is -0.75. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and Check Cap in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Check Cap 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 Check Cap. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Check Cap has no effect on the direction of GM i.e., GM and Check Cap go up and down completely randomly.
Pair Corralation between GM and Check Cap
Allowing for the 90-day total investment horizon General Motors is expected to generate 0.6 times more return on investment than Check Cap. However, General Motors is 1.66 times less risky than Check Cap. It trades about 0.07 of its potential returns per unit of risk. Check Cap is currently generating about -0.33 per unit of risk. If you would invest 5,273 in General Motors on August 29, 2024 and sell it today you would earn a total of 206.00 from holding General Motors or generate 3.91% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
General Motors vs. Check Cap
Performance |
| Timeline |
| General Motors |
| Check Cap |
GM and Check Cap Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with GM and Check Cap
The main advantage of trading using opposite GM and Check Cap positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, Check Cap 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 Check Cap will offset losses from the drop in Check Cap's long position.The idea behind General Motors and Check Cap 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.| Check Cap vs. Fonar | Check Cap vs. Burning Rock Biotech | Check Cap vs. Sera Prognostics | Check Cap vs. Psychemedics |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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