Correlation Between Driven Brands and Consumer Discretionary
Can any of the company-specific risk be diversified away by investing in both Driven Brands and Consumer Discretionary 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 Driven Brands and Consumer Discretionary into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Driven Brands Holdings and Consumer Discretionary Portfolio, you can compare the effects of market volatilities on Driven Brands and Consumer Discretionary 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 Driven Brands with a short position of Consumer Discretionary. Check out your portfolio center. Please also check ongoing floating volatility patterns of Driven Brands and Consumer Discretionary.
Diversification Opportunities for Driven Brands and Consumer Discretionary
0.9 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Driven and CONSUMER is 0.9. Overlapping area represents the amount of risk that can be diversified away by holding Driven Brands Holdings and Consumer Discretionary Portfol in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Consumer Discretionary and Driven Brands 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 Driven Brands Holdings are associated (or correlated) with Consumer Discretionary. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Consumer Discretionary has no effect on the direction of Driven Brands i.e., Driven Brands and Consumer Discretionary go up and down completely randomly.
Pair Corralation between Driven Brands and Consumer Discretionary
Given the investment horizon of 90 days Driven Brands Holdings is expected to generate 1.94 times more return on investment than Consumer Discretionary. However, Driven Brands is 1.94 times more volatile than Consumer Discretionary Portfolio. It trades about 0.15 of its potential returns per unit of risk. Consumer Discretionary Portfolio is currently generating about 0.24 per unit of risk. If you would invest 1,407 in Driven Brands Holdings on September 3, 2024 and sell it today you would earn a total of 278.00 from holding Driven Brands Holdings or generate 19.76% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Driven Brands Holdings vs. Consumer Discretionary Portfol
Performance |
Timeline |
Driven Brands Holdings |
Consumer Discretionary |
Driven Brands and Consumer Discretionary Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Driven Brands and Consumer Discretionary
The main advantage of trading using opposite Driven Brands and Consumer Discretionary positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Driven Brands position performs unexpectedly, Consumer Discretionary 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 Consumer Discretionary will offset losses from the drop in Consumer Discretionary's long position.Driven Brands vs. CarGurus | Driven Brands vs. KAR Auction Services | Driven Brands vs. Kingsway Financial Services | Driven Brands vs. Group 1 Automotive |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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