Correlation Between Great Computer and Skardin Industrial
Can any of the company-specific risk be diversified away by investing in both Great Computer and Skardin Industrial 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 Great Computer and Skardin Industrial into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Great Computer and Skardin Industrial, you can compare the effects of market volatilities on Great Computer and Skardin Industrial 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 Great Computer with a short position of Skardin Industrial. Check out your portfolio center. Please also check ongoing floating volatility patterns of Great Computer and Skardin Industrial.
Diversification Opportunities for Great Computer and Skardin Industrial
-0.42 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Great and Skardin is -0.42. Overlapping area represents the amount of risk that can be diversified away by holding Great Computer and Skardin Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Skardin Industrial and Great Computer 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 Great Computer are associated (or correlated) with Skardin Industrial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Skardin Industrial has no effect on the direction of Great Computer i.e., Great Computer and Skardin Industrial go up and down completely randomly.
Pair Corralation between Great Computer and Skardin Industrial
Assuming the 90 days trading horizon Great Computer is expected to generate 1.46 times more return on investment than Skardin Industrial. However, Great Computer is 1.46 times more volatile than Skardin Industrial. It trades about -0.07 of its potential returns per unit of risk. Skardin Industrial is currently generating about -0.22 per unit of risk. If you would invest 2,020 in Great Computer on October 22, 2024 and sell it today you would lose (165.00) from holding Great Computer or give up 8.17% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Great Computer vs. Skardin Industrial
Performance |
Timeline |
Great Computer |
Skardin Industrial |
Great Computer and Skardin Industrial Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Great Computer and Skardin Industrial
The main advantage of trading using opposite Great Computer and Skardin Industrial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Great Computer position performs unexpectedly, Skardin Industrial 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 Skardin Industrial will offset losses from the drop in Skardin Industrial's long position.Great Computer vs. Eagle Cold Storage | Great Computer vs. Gigastorage Corp | Great Computer vs. Da Cin Construction Co | Great Computer vs. Wistron Information 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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