Correlation Between SMA Solar and Applied Materials
Can any of the company-specific risk be diversified away by investing in both SMA Solar and Applied 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 SMA Solar and Applied Materials into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SMA Solar Technology and Applied Materials, you can compare the effects of market volatilities on SMA Solar and Applied 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 SMA Solar with a short position of Applied Materials. Check out your portfolio center. Please also check ongoing floating volatility patterns of SMA Solar and Applied Materials.
Diversification Opportunities for SMA Solar and Applied Materials
0.51 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between SMA and Applied is 0.51. Overlapping area represents the amount of risk that can be diversified away by holding SMA Solar Technology and Applied Materials in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Applied Materials and SMA Solar 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 SMA Solar Technology are associated (or correlated) with Applied Materials. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Applied Materials has no effect on the direction of SMA Solar i.e., SMA Solar and Applied Materials go up and down completely randomly.
Pair Corralation between SMA Solar and Applied Materials
Assuming the 90 days trading horizon SMA Solar Technology is expected to under-perform the Applied Materials. In addition to that, SMA Solar is 1.31 times more volatile than Applied Materials. It trades about -0.16 of its total potential returns per unit of risk. Applied Materials is currently generating about -0.01 per unit of volatility. If you would invest 18,403 in Applied Materials on September 3, 2024 and sell it today you would lose (753.00) from holding Applied Materials or give up 4.09% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
SMA Solar Technology vs. Applied Materials
Performance |
| Timeline |
| SMA Solar Technology |
| Applied Materials |
SMA Solar and Applied Materials Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with SMA Solar and Applied Materials
The main advantage of trading using opposite SMA Solar and Applied Materials positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SMA Solar position performs unexpectedly, Applied 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 Applied Materials will offset losses from the drop in Applied Materials' long position.| SMA Solar vs. Catalyst Media Group | SMA Solar vs. CATLIN GROUP | SMA Solar vs. Magnora ASA | SMA Solar vs. RTW Venture Fund |
| Applied Materials vs. SMA Solar Technology | Applied Materials vs. Arcticzymes Technologies ASA | Applied Materials vs. DXC Technology Co | Applied Materials vs. Waste Management |
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 Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.
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