Correlation Between Softstar Entertainment and Kura Sushi
Can any of the company-specific risk be diversified away by investing in both Softstar Entertainment and Kura Sushi 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 Softstar Entertainment and Kura Sushi into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Softstar Entertainment and Kura Sushi Asia, you can compare the effects of market volatilities on Softstar Entertainment and Kura Sushi 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 Softstar Entertainment with a short position of Kura Sushi. Check out your portfolio center. Please also check ongoing floating volatility patterns of Softstar Entertainment and Kura Sushi.
Diversification Opportunities for Softstar Entertainment and Kura Sushi
0.45 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Softstar and Kura is 0.45. Overlapping area represents the amount of risk that can be diversified away by holding Softstar Entertainment and Kura Sushi Asia in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kura Sushi Asia and Softstar Entertainment 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 Softstar Entertainment are associated (or correlated) with Kura Sushi. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kura Sushi Asia has no effect on the direction of Softstar Entertainment i.e., Softstar Entertainment and Kura Sushi go up and down completely randomly.
Pair Corralation between Softstar Entertainment and Kura Sushi
Assuming the 90 days trading horizon Softstar Entertainment is expected to generate 2.74 times more return on investment than Kura Sushi. However, Softstar Entertainment is 2.74 times more volatile than Kura Sushi Asia. It trades about 0.03 of its potential returns per unit of risk. Kura Sushi Asia is currently generating about -0.02 per unit of risk. If you would invest 6,100 in Softstar Entertainment on December 5, 2024 and sell it today you would earn a total of 120.00 from holding Softstar Entertainment or generate 1.97% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Softstar Entertainment vs. Kura Sushi Asia
Performance |
Timeline |
Softstar Entertainment |
Kura Sushi Asia |
Softstar Entertainment and Kura Sushi Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Softstar Entertainment and Kura Sushi
The main advantage of trading using opposite Softstar Entertainment and Kura Sushi positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Softstar Entertainment position performs unexpectedly, Kura Sushi 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 Kura Sushi will offset losses from the drop in Kura Sushi's long position.Softstar Entertainment vs. Logah Technology Corp | Softstar Entertainment vs. CTBC Financial Holding | Softstar Entertainment vs. ESUN Financial Holding | Softstar Entertainment vs. Chicony Power Technology |
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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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