Correlation Between Malaga Financial and Chestnut Street
Can any of the company-specific risk be diversified away by investing in both Malaga Financial and Chestnut Street 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 Malaga Financial and Chestnut Street into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Malaga Financial and Chestnut Street Exchange, you can compare the effects of market volatilities on Malaga Financial and Chestnut Street 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 Malaga Financial with a short position of Chestnut Street. Check out your portfolio center. Please also check ongoing floating volatility patterns of Malaga Financial and Chestnut Street.
Diversification Opportunities for Malaga Financial and Chestnut Street
-0.13 | Correlation Coefficient |
Good diversification
The 3 months correlation between Malaga and Chestnut is -0.13. Overlapping area represents the amount of risk that can be diversified away by holding Malaga Financial and Chestnut Street Exchange in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Chestnut Street Exchange and Malaga Financial 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 Malaga Financial are associated (or correlated) with Chestnut Street. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Chestnut Street Exchange has no effect on the direction of Malaga Financial i.e., Malaga Financial and Chestnut Street go up and down completely randomly.
Pair Corralation between Malaga Financial and Chestnut Street
Given the investment horizon of 90 days Malaga Financial is expected to generate 3.22 times more return on investment than Chestnut Street. However, Malaga Financial is 3.22 times more volatile than Chestnut Street Exchange. It trades about 0.04 of its potential returns per unit of risk. Chestnut Street Exchange is currently generating about 0.02 per unit of risk. If you would invest 2,138 in Malaga Financial on October 5, 2024 and sell it today you would earn a total of 102.00 from holding Malaga Financial or generate 4.77% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Malaga Financial vs. Chestnut Street Exchange
Performance |
Timeline |
Malaga Financial |
Chestnut Street Exchange |
Malaga Financial and Chestnut Street Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Malaga Financial and Chestnut Street
The main advantage of trading using opposite Malaga Financial and Chestnut Street positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Malaga Financial position performs unexpectedly, Chestnut Street 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 Chestnut Street will offset losses from the drop in Chestnut Street's long position.Malaga Financial vs. MF Bancorp | Malaga Financial vs. United Bancorporation of | Malaga Financial vs. Harbor Bankshares | Malaga Financial vs. BankFirst Capital |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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