Correlation Between Carebook Technologies and Salesforce
Can any of the company-specific risk be diversified away by investing in both Carebook Technologies 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 Carebook Technologies and Salesforce into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Carebook Technologies and SalesforceCom CDR, you can compare the effects of market volatilities on Carebook Technologies 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 Carebook Technologies with a short position of Salesforce. Check out your portfolio center. Please also check ongoing floating volatility patterns of Carebook Technologies and Salesforce.
Diversification Opportunities for Carebook Technologies and Salesforce
-0.58 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Carebook and Salesforce is -0.58. Overlapping area represents the amount of risk that can be diversified away by holding Carebook Technologies and SalesforceCom CDR in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SalesforceCom CDR and Carebook Technologies 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 Carebook Technologies 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 SalesforceCom CDR has no effect on the direction of Carebook Technologies i.e., Carebook Technologies and Salesforce go up and down completely randomly.
Pair Corralation between Carebook Technologies and Salesforce
Assuming the 90 days trading horizon Carebook Technologies is expected to generate 19.53 times more return on investment than Salesforce. However, Carebook Technologies is 19.53 times more volatile than SalesforceCom CDR. It trades about 0.19 of its potential returns per unit of risk. SalesforceCom CDR is currently generating about -0.25 per unit of risk. If you would invest 5.50 in Carebook Technologies on October 10, 2024 and sell it today you would earn a total of 4.00 from holding Carebook Technologies or generate 72.73% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Carebook Technologies vs. SalesforceCom CDR
Performance |
Timeline |
Carebook Technologies |
SalesforceCom CDR |
Carebook Technologies and Salesforce Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Carebook Technologies and Salesforce
The main advantage of trading using opposite Carebook Technologies and Salesforce positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Carebook Technologies 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.Carebook Technologies vs. SalesforceCom CDR | Carebook Technologies vs. Metalero Mining Corp | Carebook Technologies vs. Leons Furniture Limited | Carebook Technologies vs. NeXGold Mining Corp |
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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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