Correlation Between Berkshire Hathaway and Tesla
Can any of the company-specific risk be diversified away by investing in both Berkshire Hathaway and Tesla 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 Berkshire Hathaway and Tesla into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Berkshire Hathaway CDR and Tesla Inc CDR, you can compare the effects of market volatilities on Berkshire Hathaway and Tesla 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 Berkshire Hathaway with a short position of Tesla. Check out your portfolio center. Please also check ongoing floating volatility patterns of Berkshire Hathaway and Tesla.
Diversification Opportunities for Berkshire Hathaway and Tesla
0.33 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Berkshire and Tesla is 0.33. Overlapping area represents the amount of risk that can be diversified away by holding Berkshire Hathaway CDR and Tesla Inc CDR in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Tesla Inc CDR and Berkshire Hathaway 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 Berkshire Hathaway CDR are associated (or correlated) with Tesla. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Tesla Inc CDR has no effect on the direction of Berkshire Hathaway i.e., Berkshire Hathaway and Tesla go up and down completely randomly.
Pair Corralation between Berkshire Hathaway and Tesla
Assuming the 90 days trading horizon Berkshire Hathaway is expected to generate 6.76 times less return on investment than Tesla. But when comparing it to its historical volatility, Berkshire Hathaway CDR is 3.45 times less risky than Tesla. It trades about 0.14 of its potential returns per unit of risk. Tesla Inc CDR is currently generating about 0.26 of returns per unit of risk over similar time horizon. If you would invest 2,394 in Tesla Inc CDR on August 28, 2024 and sell it today you would earn a total of 693.00 from holding Tesla Inc CDR or generate 28.95% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Berkshire Hathaway CDR vs. Tesla Inc CDR
Performance |
| Timeline |
| Berkshire Hathaway CDR |
| Tesla Inc CDR |
Berkshire Hathaway and Tesla Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Berkshire Hathaway and Tesla
The main advantage of trading using opposite Berkshire Hathaway and Tesla positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Berkshire Hathaway position performs unexpectedly, Tesla 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 Tesla will offset losses from the drop in Tesla's long position.| Berkshire Hathaway vs. NVIDIA CDR | Berkshire Hathaway vs. Apple Inc CDR | Berkshire Hathaway vs. Microsoft Corp CDR | Berkshire Hathaway vs. Amazon CDR |
| Tesla vs. Canlan Ice Sports | Tesla vs. Comprehensive Healthcare Systems | Tesla vs. Chemtrade Logistics Income | Tesla vs. DRI Healthcare Trust |
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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