Correlation Between GM and Voya Us
Can any of the company-specific risk be diversified away by investing in both GM and Voya Us 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 Voya Us into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and Voya Stock Index, you can compare the effects of market volatilities on GM and Voya Us 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 Voya Us. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and Voya Us.
Diversification Opportunities for GM and Voya Us
Poor diversification
The 3 months correlation between GM and Voya is 0.76. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and Voya Stock Index in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Voya Stock Index 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 Voya Us. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Voya Stock Index has no effect on the direction of GM i.e., GM and Voya Us go up and down completely randomly.
Pair Corralation between GM and Voya Us
Allowing for the 90-day total investment horizon General Motors is expected to generate 3.88 times more return on investment than Voya Us. However, GM is 3.88 times more volatile than Voya Stock Index. It trades about 0.17 of its potential returns per unit of risk. Voya Stock Index is currently generating about 0.36 per unit of risk. If you would invest 5,076 in General Motors on September 1, 2024 and sell it today you would earn a total of 483.00 from holding General Motors or generate 9.52% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 95.45% |
| Values | Daily Returns |
General Motors vs. Voya Stock Index
Performance |
| Timeline |
| General Motors |
| Voya Stock Index |
GM and Voya Us Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with GM and Voya Us
The main advantage of trading using opposite GM and Voya Us positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, Voya Us 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 Voya Us will offset losses from the drop in Voya Us' long position.The idea behind General Motors and Voya Stock Index 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.| Voya Us vs. Voya Bond Index | Voya Us vs. Voya Bond Index | Voya Us vs. Voya Limited Maturity | Voya Us vs. Voya Limited Maturity |
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 Correlation Analysis module to reduce portfolio risk simply by holding instruments which are not perfectly correlated.
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