Correlation Between Skardin Industrial and Macroblock
Can any of the company-specific risk be diversified away by investing in both Skardin Industrial and Macroblock 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 Skardin Industrial and Macroblock into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Skardin Industrial and Macroblock, you can compare the effects of market volatilities on Skardin Industrial and Macroblock 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 Skardin Industrial with a short position of Macroblock. Check out your portfolio center. Please also check ongoing floating volatility patterns of Skardin Industrial and Macroblock.
Diversification Opportunities for Skardin Industrial and Macroblock
0.23 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Skardin and Macroblock is 0.23. Overlapping area represents the amount of risk that can be diversified away by holding Skardin Industrial and Macroblock in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Macroblock and Skardin Industrial 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 Skardin Industrial are associated (or correlated) with Macroblock. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Macroblock has no effect on the direction of Skardin Industrial i.e., Skardin Industrial and Macroblock go up and down completely randomly.
Pair Corralation between Skardin Industrial and Macroblock
Assuming the 90 days trading horizon Skardin Industrial is expected to generate 2.19 times more return on investment than Macroblock. However, Skardin Industrial is 2.19 times more volatile than Macroblock. It trades about -0.01 of its potential returns per unit of risk. Macroblock is currently generating about -0.09 per unit of risk. If you would invest 8,400 in Skardin Industrial on September 5, 2024 and sell it today you would lose (1,210) from holding Skardin Industrial or give up 14.4% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 99.21% |
| Values | Daily Returns |
Skardin Industrial vs. Macroblock
Performance |
| Timeline |
| Skardin Industrial |
| Macroblock |
Skardin Industrial and Macroblock Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Skardin Industrial and Macroblock
The main advantage of trading using opposite Skardin Industrial and Macroblock positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Skardin Industrial position performs unexpectedly, Macroblock 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 Macroblock will offset losses from the drop in Macroblock's long position.| Skardin Industrial vs. Ruentex Engineering Construction | Skardin Industrial vs. Kao Fong Machinery | Skardin Industrial vs. Sporton International | Skardin Industrial vs. Kindom Construction Corp |
| Macroblock vs. Skardin Industrial | Macroblock vs. Feng Ching Metal | Macroblock vs. Great China Metal | Macroblock vs. De Licacy Industrial |
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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