Correlation Between GM and FVCBankcorp
Can any of the company-specific risk be diversified away by investing in both GM and FVCBankcorp 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 FVCBankcorp into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and FVCBankcorp, you can compare the effects of market volatilities on GM and FVCBankcorp 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 FVCBankcorp. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and FVCBankcorp.
Diversification Opportunities for GM and FVCBankcorp
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between GM and FVCBankcorp is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and FVCBankcorp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on FVCBankcorp 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 FVCBankcorp. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of FVCBankcorp has no effect on the direction of GM i.e., GM and FVCBankcorp go up and down completely randomly.
Pair Corralation between GM and FVCBankcorp
Allowing for the 90-day total investment horizon GM is expected to generate 1.69 times less return on investment than FVCBankcorp. In addition to that, GM is 1.1 times more volatile than FVCBankcorp. It trades about 0.07 of its total potential returns per unit of risk. FVCBankcorp is currently generating about 0.13 per unit of volatility. If you would invest 1,290 in FVCBankcorp on September 5, 2024 and sell it today you would earn a total of 90.00 from holding FVCBankcorp or generate 6.98% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
General Motors vs. FVCBankcorp
Performance |
Timeline |
General Motors |
FVCBankcorp |
GM and FVCBankcorp Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with GM and FVCBankcorp
The main advantage of trading using opposite GM and FVCBankcorp positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, FVCBankcorp 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 FVCBankcorp will offset losses from the drop in FVCBankcorp's long position.The idea behind General Motors and FVCBankcorp 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.FVCBankcorp vs. Home Federal Bancorp | FVCBankcorp vs. First Financial Northwest | FVCBankcorp vs. First Northwest Bancorp | FVCBankcorp vs. First Capital |
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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