Correlation Between Cisco Systems and Mairs Power
Can any of the company-specific risk be diversified away by investing in both Cisco Systems and Mairs Power 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 Cisco Systems and Mairs Power into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cisco Systems and Mairs Power Minnesota, you can compare the effects of market volatilities on Cisco Systems and Mairs Power 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 Cisco Systems with a short position of Mairs Power. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cisco Systems and Mairs Power.
Diversification Opportunities for Cisco Systems and Mairs Power
-0.5 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Cisco and Mairs is -0.5. Overlapping area represents the amount of risk that can be diversified away by holding Cisco Systems and Mairs Power Minnesota in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mairs Power Minnesota and Cisco Systems 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 Cisco Systems are associated (or correlated) with Mairs Power. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mairs Power Minnesota has no effect on the direction of Cisco Systems i.e., Cisco Systems and Mairs Power go up and down completely randomly.
Pair Corralation between Cisco Systems and Mairs Power
Given the investment horizon of 90 days Cisco Systems is expected to generate 4.62 times more return on investment than Mairs Power. However, Cisco Systems is 4.62 times more volatile than Mairs Power Minnesota. It trades about 0.18 of its potential returns per unit of risk. Mairs Power Minnesota is currently generating about 0.12 per unit of risk. If you would invest 4,528 in Cisco Systems on September 3, 2024 and sell it today you would earn a total of 1,393 from holding Cisco Systems or generate 30.76% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Cisco Systems vs. Mairs Power Minnesota
Performance |
| Timeline |
| Cisco Systems |
| Mairs Power Minnesota |
Cisco Systems and Mairs Power Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Cisco Systems and Mairs Power
The main advantage of trading using opposite Cisco Systems and Mairs Power positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cisco Systems position performs unexpectedly, Mairs Power 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 Mairs Power will offset losses from the drop in Mairs Power's long position.| Cisco Systems vs. Highway Holdings Limited | Cisco Systems vs. QCR Holdings | Cisco Systems vs. Partner Communications | Cisco Systems vs. Acumen Pharmaceuticals |
| Mairs Power vs. BlackRock Intermediate Muni | Mairs Power vs. IQ MacKay Municipal | Mairs Power vs. Overlay Shares Municipal | Mairs Power vs. IQ MacKay Municipal |
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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