Correlation Between Driven Brands and Tema ETF
Can any of the company-specific risk be diversified away by investing in both Driven Brands and Tema ETF 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 Tema ETF 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 Tema ETF Trust, you can compare the effects of market volatilities on Driven Brands and Tema ETF 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 Tema ETF. Check out your portfolio center. Please also check ongoing floating volatility patterns of Driven Brands and Tema ETF.
Diversification Opportunities for Driven Brands and Tema ETF
0.74 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Driven and Tema is 0.74. Overlapping area represents the amount of risk that can be diversified away by holding Driven Brands Holdings and Tema ETF Trust in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Tema ETF Trust 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 Tema ETF. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Tema ETF Trust has no effect on the direction of Driven Brands i.e., Driven Brands and Tema ETF go up and down completely randomly.
Pair Corralation between Driven Brands and Tema ETF
Given the investment horizon of 90 days Driven Brands is expected to generate 1.74 times less return on investment than Tema ETF. But when comparing it to its historical volatility, Driven Brands Holdings is 1.09 times less risky than Tema ETF. It trades about 0.11 of its potential returns per unit of risk. Tema ETF Trust is currently generating about 0.18 of returns per unit of risk over similar time horizon. If you would invest 3,702 in Tema ETF Trust on November 3, 2024 and sell it today you would earn a total of 193.00 from holding Tema ETF Trust or generate 5.21% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 95.24% |
| Values | Daily Returns |
Driven Brands Holdings vs. Tema ETF Trust
Performance |
| Timeline |
| Driven Brands Holdings |
| Tema ETF Trust |
Driven Brands and Tema ETF Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Driven Brands and Tema ETF
The main advantage of trading using opposite Driven Brands and Tema ETF positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Driven Brands position performs unexpectedly, Tema ETF 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 Tema ETF will offset losses from the drop in Tema ETF'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 |
| Tema ETF vs. iShares Dividend and | Tema ETF vs. Martin Currie Sustainable | Tema ETF vs. VictoryShares THB Mid | Tema ETF vs. Mast Global Battery |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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