Correlation Between SentinelOne and OPAL Fuels
Can any of the company-specific risk be diversified away by investing in both SentinelOne and OPAL Fuels 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 SentinelOne and OPAL Fuels into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SentinelOne and OPAL Fuels, you can compare the effects of market volatilities on SentinelOne and OPAL Fuels 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 SentinelOne with a short position of OPAL Fuels. Check out your portfolio center. Please also check ongoing floating volatility patterns of SentinelOne and OPAL Fuels.
Diversification Opportunities for SentinelOne and OPAL Fuels
0.04 | Correlation Coefficient |
Significant diversification
The 3 months correlation between SentinelOne and OPAL is 0.04. Overlapping area represents the amount of risk that can be diversified away by holding SentinelOne and OPAL Fuels in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on OPAL Fuels and SentinelOne 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 SentinelOne are associated (or correlated) with OPAL Fuels. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of OPAL Fuels has no effect on the direction of SentinelOne i.e., SentinelOne and OPAL Fuels go up and down completely randomly.
Pair Corralation between SentinelOne and OPAL Fuels
Taking into account the 90-day investment horizon SentinelOne is expected to under-perform the OPAL Fuels. But the stock apears to be less risky and, when comparing its historical volatility, SentinelOne is 2.06 times less risky than OPAL Fuels. The stock trades about -0.02 of its potential returns per unit of risk. The OPAL Fuels is currently generating about 0.01 of returns per unit of risk over similar time horizon. If you would invest 237.00 in OPAL Fuels on August 26, 2025 and sell it today you would lose (13.00) from holding OPAL Fuels or give up 5.49% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
SentinelOne vs. OPAL Fuels
Performance |
| Timeline |
| SentinelOne |
| OPAL Fuels |
SentinelOne and OPAL Fuels Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with SentinelOne and OPAL Fuels
The main advantage of trading using opposite SentinelOne and OPAL Fuels positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SentinelOne position performs unexpectedly, OPAL Fuels 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 OPAL Fuels will offset losses from the drop in OPAL Fuels' long position.| SentinelOne vs. Knight Transportation | SentinelOne vs. Sportsmans | SentinelOne vs. Hyatt Hotels | SentinelOne vs. Wyndham Hotels Resorts |
| OPAL Fuels vs. SmarTone Telecommunications Holdings | OPAL Fuels vs. Spirent Communications plc | OPAL Fuels vs. Mitsui Chemicals ADR | OPAL Fuels vs. Hutchison Telecommunications Hong |
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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