Correlation Between ESS Tech and Solid Power
Can any of the company-specific risk be diversified away by investing in both ESS Tech and Solid Power 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 ESS Tech and Solid Power into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between ESS Tech and Solid Power, you can compare the effects of market volatilities on ESS Tech and Solid Power 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 ESS Tech with a short position of Solid Power. Check out your portfolio center. Please also check ongoing floating volatility patterns of ESS Tech and Solid Power.
Diversification Opportunities for ESS Tech and Solid Power
-0.79 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between ESS and Solid is -0.79. Overlapping area represents the amount of risk that can be diversified away by holding ESS Tech and Solid Power in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Solid Power and ESS Tech 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 ESS Tech are associated (or correlated) with Solid Power. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Solid Power has no effect on the direction of ESS Tech i.e., ESS Tech and Solid Power go up and down completely randomly.
Pair Corralation between ESS Tech and Solid Power
Considering the 90-day investment horizon ESS Tech is expected to under-perform the Solid Power. In addition to that, ESS Tech is 3.08 times more volatile than Solid Power. It trades about -0.05 of its total potential returns per unit of risk. Solid Power is currently generating about 0.18 per unit of volatility. If you would invest 111.00 in Solid Power on March 27, 2025 and sell it today you would earn a total of 76.00 from holding Solid Power or generate 68.47% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
ESS Tech vs. Solid Power
Performance |
| Timeline |
| ESS Tech |
| Solid Power |
ESS Tech and Solid Power Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with ESS Tech and Solid Power
The main advantage of trading using opposite ESS Tech and Solid Power positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if ESS Tech position performs unexpectedly, Solid Power 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 Solid Power will offset losses from the drop in Solid Power's long position.The idea behind ESS Tech and Solid Power 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.| Solid Power vs. Plug Power | Solid Power vs. FuelCell Energy | Solid Power vs. Enovix Corp | Solid Power vs. Microvast Holdings |
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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