Correlation Between Citigroup and Pyth Network
Can any of the company-specific risk be diversified away by investing in both Citigroup and Pyth Network 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 Pyth Network into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Citigroup and Pyth Network, you can compare the effects of market volatilities on Citigroup and Pyth Network 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 Pyth Network. Check out your portfolio center. Please also check ongoing floating volatility patterns of Citigroup and Pyth Network.
Diversification Opportunities for Citigroup and Pyth Network
-0.07 | Correlation Coefficient |
Good diversification
The 3 months correlation between Citigroup and Pyth is -0.07. Overlapping area represents the amount of risk that can be diversified away by holding Citigroup and Pyth Network in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Pyth Network 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 Pyth Network. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Pyth Network has no effect on the direction of Citigroup i.e., Citigroup and Pyth Network go up and down completely randomly.
Pair Corralation between Citigroup and Pyth Network
Taking into account the 90-day investment horizon Citigroup is expected to generate 0.29 times more return on investment than Pyth Network. However, Citigroup is 3.47 times less risky than Pyth Network. It trades about 0.03 of its potential returns per unit of risk. Pyth Network is currently generating about -0.13 per unit of risk. If you would invest 6,991 in Citigroup on December 28, 2024 and sell it today you would earn a total of 194.00 from holding Citigroup or generate 2.77% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 95.24% |
Values | Daily Returns |
Citigroup vs. Pyth Network
Performance |
Timeline |
Citigroup |
Pyth Network |
Citigroup and Pyth Network Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Citigroup and Pyth Network
The main advantage of trading using opposite Citigroup and Pyth Network positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Citigroup position performs unexpectedly, Pyth Network 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 Pyth Network will offset losses from the drop in Pyth Network's long position.Citigroup vs. PJT Partners | Citigroup vs. National Bank Holdings | Citigroup vs. FB Financial Corp | Citigroup vs. Northrim BanCorp |
Pyth Network vs. Staked Ether | Pyth Network vs. Phala Network | Pyth Network vs. EigenLayer | Pyth Network vs. EOSDAC |
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 Price Ceiling Movement module to calculate and plot Price Ceiling Movement for different equity instruments.
Other Complementary Tools
Technical Analysis Check basic technical indicators and analysis based on most latest market data | |
Idea Optimizer Use advanced portfolio builder with pre-computed micro ideas to build optimal portfolio | |
Pair Correlation Compare performance and examine fundamental relationship between any two equity instruments | |
Price Ceiling Movement Calculate and plot Price Ceiling Movement for different equity instruments | |
Portfolio Analyzer Portfolio analysis module that provides access to portfolio diagnostics and optimization engine |