Correlation Between Salesforce and Applied Materials
Can any of the company-specific risk be diversified away by investing in both Salesforce 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 Salesforce and Applied Materials into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Salesforce and Applied Materials, you can compare the effects of market volatilities on Salesforce 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 Salesforce with a short position of Applied Materials. Check out your portfolio center. Please also check ongoing floating volatility patterns of Salesforce and Applied Materials.
Diversification Opportunities for Salesforce and Applied Materials
-0.04 | Correlation Coefficient |
Good diversification
The 3 months correlation between Salesforce and Applied is -0.04. Overlapping area represents the amount of risk that can be diversified away by holding Salesforce and Applied Materials in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Applied Materials and Salesforce 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 Salesforce 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 Salesforce i.e., Salesforce and Applied Materials go up and down completely randomly.
Pair Corralation between Salesforce and Applied Materials
Assuming the 90 days trading horizon Salesforce is expected to generate 4.79 times less return on investment than Applied Materials. But when comparing it to its historical volatility, Salesforce is 1.35 times less risky than Applied Materials. It trades about 0.06 of its potential returns per unit of risk. Applied Materials is currently generating about 0.22 of returns per unit of risk over similar time horizon. If you would invest 11,827 in Applied Materials on April 22, 2025 and sell it today you would earn a total of 4,731 from holding Applied Materials or generate 40.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Salesforce vs. Applied Materials
Performance |
Timeline |
Salesforce |
Applied Materials |
Salesforce and Applied Materials Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Salesforce and Applied Materials
The main advantage of trading using opposite Salesforce and Applied Materials positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Salesforce 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.Salesforce vs. SAP SE | Salesforce vs. Rocket Internet SE | Salesforce vs. AUREA SA INH | Salesforce vs. SIVERS SEMICONDUCTORS AB |
Applied Materials vs. Parkson Retail Group | Applied Materials vs. RCS MediaGroup SpA | Applied Materials vs. PICKN PAY STORES | Applied Materials vs. Flutter Entertainment PLC |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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