Correlation Between SentinelOne and Kansai Electric
Can any of the company-specific risk be diversified away by investing in both SentinelOne and Kansai Electric 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 Kansai Electric into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SentinelOne and Kansai Electric Power, you can compare the effects of market volatilities on SentinelOne and Kansai Electric 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 Kansai Electric. Check out your portfolio center. Please also check ongoing floating volatility patterns of SentinelOne and Kansai Electric.
Diversification Opportunities for SentinelOne and Kansai Electric
-0.64 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between SentinelOne and Kansai is -0.64. Overlapping area represents the amount of risk that can be diversified away by holding SentinelOne and Kansai Electric Power in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kansai Electric Power 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 Kansai Electric. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kansai Electric Power has no effect on the direction of SentinelOne i.e., SentinelOne and Kansai Electric go up and down completely randomly.
Pair Corralation between SentinelOne and Kansai Electric
Taking into account the 90-day investment horizon SentinelOne is expected to generate 0.51 times more return on investment than Kansai Electric. However, SentinelOne is 1.96 times less risky than Kansai Electric. It trades about 0.12 of its potential returns per unit of risk. Kansai Electric Power is currently generating about -0.26 per unit of risk. If you would invest 2,647 in SentinelOne on August 31, 2024 and sell it today you would earn a total of 161.00 from holding SentinelOne or generate 6.08% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
SentinelOne vs. Kansai Electric Power
Performance |
| Timeline |
| SentinelOne |
| Kansai Electric Power |
SentinelOne and Kansai Electric Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with SentinelOne and Kansai Electric
The main advantage of trading using opposite SentinelOne and Kansai Electric positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SentinelOne position performs unexpectedly, Kansai Electric 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 Kansai Electric will offset losses from the drop in Kansai Electric's long position.| SentinelOne vs. Crowdstrike Holdings | SentinelOne vs. Okta Inc | SentinelOne vs. Cloudflare | SentinelOne vs. MongoDB |
| Kansai Electric vs. Constellation Energy Corp | Kansai Electric vs. Orsted AS ADR | Kansai Electric vs. Orsted AS | Kansai Electric vs. HUMANA INC |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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