Correlation Between SIMS METAL and Mitsubishi Materials
Can any of the company-specific risk be diversified away by investing in both SIMS METAL and Mitsubishi Materials 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 SIMS METAL and Mitsubishi Materials into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SIMS METAL MGT and Mitsubishi Materials, you can compare the effects of market volatilities on SIMS METAL and Mitsubishi Materials 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 SIMS METAL with a short position of Mitsubishi Materials. Check out your portfolio center. Please also check ongoing floating volatility patterns of SIMS METAL and Mitsubishi Materials.
Diversification Opportunities for SIMS METAL and Mitsubishi Materials
0.68 | Correlation Coefficient |
Poor diversification
The 3 months correlation between SIMS and Mitsubishi is 0.68. Overlapping area represents the amount of risk that can be diversified away by holding SIMS METAL MGT and Mitsubishi Materials in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mitsubishi Materials and SIMS METAL 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 SIMS METAL MGT are associated (or correlated) with Mitsubishi Materials. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mitsubishi Materials has no effect on the direction of SIMS METAL i.e., SIMS METAL and Mitsubishi Materials go up and down completely randomly.
Pair Corralation between SIMS METAL and Mitsubishi Materials
Assuming the 90 days trading horizon SIMS METAL MGT is expected to generate 1.61 times more return on investment than Mitsubishi Materials. However, SIMS METAL is 1.61 times more volatile than Mitsubishi Materials. It trades about 0.16 of its potential returns per unit of risk. Mitsubishi Materials is currently generating about 0.1 per unit of risk. If you would invest 695.00 in SIMS METAL MGT on December 30, 2024 and sell it today you would earn a total of 165.00 from holding SIMS METAL MGT or generate 23.74% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
SIMS METAL MGT vs. Mitsubishi Materials
Performance |
Timeline |
SIMS METAL MGT |
Mitsubishi Materials |
SIMS METAL and Mitsubishi Materials Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with SIMS METAL and Mitsubishi Materials
The main advantage of trading using opposite SIMS METAL and Mitsubishi Materials positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SIMS METAL position performs unexpectedly, Mitsubishi Materials 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 Mitsubishi Materials will offset losses from the drop in Mitsubishi Materials' long position.SIMS METAL vs. Aya Gold Silver | SIMS METAL vs. British American Tobacco | SIMS METAL vs. CHINA TONTINE WINES | SIMS METAL vs. Platinum Investment Management |
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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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