Correlation Between GM and RBC Quant
Can any of the company-specific risk be diversified away by investing in both GM and RBC Quant 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 RBC Quant into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and RBC Quant European, you can compare the effects of market volatilities on GM and RBC Quant 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 RBC Quant. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and RBC Quant.
Diversification Opportunities for GM and RBC Quant
Excellent diversification
The 3 months correlation between GM and RBC is -0.7. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and RBC Quant European in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on RBC Quant European 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 RBC Quant. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of RBC Quant European has no effect on the direction of GM i.e., GM and RBC Quant go up and down completely randomly.
Pair Corralation between GM and RBC Quant
Allowing for the 90-day total investment horizon General Motors is expected to generate 4.37 times more return on investment than RBC Quant. However, GM is 4.37 times more volatile than RBC Quant European. It trades about 0.17 of its potential returns per unit of risk. RBC Quant European is currently generating about -0.07 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 Against |
| Strength | Weak |
| Accuracy | 95.45% |
| Values | Daily Returns |
General Motors vs. RBC Quant European
Performance |
| Timeline |
| General Motors |
| RBC Quant European |
GM and RBC Quant Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with GM and RBC Quant
The main advantage of trading using opposite GM and RBC Quant positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, RBC Quant 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 RBC Quant will offset losses from the drop in RBC Quant's long position.The idea behind General Motors and RBC Quant European 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.| RBC Quant vs. BMO Europe High | RBC Quant vs. BMO High Dividend | RBC Quant vs. BMO Covered Call | RBC Quant vs. BMO Global High |
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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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