Correlation Between Citigroup and Federated Mdt
Can any of the company-specific risk be diversified away by investing in both Citigroup and Federated Mdt 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 Citigroup and Federated Mdt into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Citigroup and Federated Mdt Small, you can compare the effects of market volatilities on Citigroup and Federated Mdt 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 Citigroup with a short position of Federated Mdt. Check out your portfolio center. Please also check ongoing floating volatility patterns of Citigroup and Federated Mdt.
Diversification Opportunities for Citigroup and Federated Mdt
0.91 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Citigroup and Federated is 0.91. Overlapping area represents the amount of risk that can be diversified away by holding Citigroup and Federated Mdt Small in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Federated Mdt Small and Citigroup 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 Citigroup are associated (or correlated) with Federated Mdt. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Federated Mdt Small has no effect on the direction of Citigroup i.e., Citigroup and Federated Mdt go up and down completely randomly.
Pair Corralation between Citigroup and Federated Mdt
Taking into account the 90-day investment horizon Citigroup is expected to generate 1.39 times more return on investment than Federated Mdt. However, Citigroup is 1.39 times more volatile than Federated Mdt Small. It trades about 0.26 of its potential returns per unit of risk. Federated Mdt Small is currently generating about 0.3 per unit of risk. If you would invest 6,361 in Citigroup on September 1, 2024 and sell it today you would earn a total of 726.00 from holding Citigroup or generate 11.41% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 95.45% |
| Values | Daily Returns |
Citigroup vs. Federated Mdt Small
Performance |
| Timeline |
| Citigroup |
| Federated Mdt Small |
Citigroup and Federated Mdt Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Citigroup and Federated Mdt
The main advantage of trading using opposite Citigroup and Federated Mdt positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Citigroup position performs unexpectedly, Federated Mdt 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 Federated Mdt will offset losses from the drop in Federated Mdt's long position.| Citigroup vs. JPMorgan Chase Co | Citigroup vs. Wells Fargo | Citigroup vs. Toronto Dominion Bank | Citigroup vs. Nu Holdings |
| Federated Mdt vs. Touchstone Mid Cap | Federated Mdt vs. Virtus Kar Small Cap | Federated Mdt vs. Mid Cap Growth | Federated Mdt vs. Harding Loevner International |
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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