Correlation Between Snowflake and Salesforce
Can any of the company-specific risk be diversified away by investing in both Snowflake and Salesforce 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 Snowflake and Salesforce into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Snowflake and Salesforce, you can compare the effects of market volatilities on Snowflake and Salesforce 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 Snowflake with a short position of Salesforce. Check out your portfolio center. Please also check ongoing floating volatility patterns of Snowflake and Salesforce.
Diversification Opportunities for Snowflake and Salesforce
0.67 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Snowflake and Salesforce is 0.67. Overlapping area represents the amount of risk that can be diversified away by holding Snowflake and Salesforce in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Salesforce and Snowflake 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 Snowflake are associated (or correlated) with Salesforce. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Salesforce has no effect on the direction of Snowflake i.e., Snowflake and Salesforce go up and down completely randomly.
Pair Corralation between Snowflake and Salesforce
Given the investment horizon of 90 days Snowflake is expected to generate 3.47 times more return on investment than Salesforce. However, Snowflake is 3.47 times more volatile than Salesforce. It trades about 0.28 of its potential returns per unit of risk. Salesforce is currently generating about 0.34 per unit of risk. If you would invest 11,550 in Snowflake on August 23, 2024 and sell it today you would earn a total of 5,585 from holding Snowflake or generate 48.35% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Snowflake vs. Salesforce
Performance |
Timeline |
Snowflake |
Salesforce |
Snowflake and Salesforce Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Snowflake and Salesforce
The main advantage of trading using opposite Snowflake and Salesforce positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Snowflake position performs unexpectedly, Salesforce 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 Salesforce will offset losses from the drop in Salesforce's long position.The idea behind Snowflake and Salesforce pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.Salesforce vs. Zoom Video Communications | Salesforce vs. C3 Ai Inc | Salesforce vs. Shopify | Salesforce vs. Workday |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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