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

Citigroup  Pyth Network

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

Citigroup

Risk-Adjusted Performance

Weak

Compared to the overall equity markets, risk-adjusted returns on investments in Citigroup are ranked lower than 2 (%) of all global equities and portfolios over the last 90 days. In spite of rather sound fundamental indicators, Citigroup is not utilizing all of its potentials. The newest stock price tumult, may contribute to shorter-term losses for the shareholders.

Pyth Network

Risk-Adjusted Performance

Very Weak

Over the last 90 days Pyth Network has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of unsteady performance in the last few months, the Crypto's fundamental indicators remain rather sound which may send shares a bit higher in April 2025. The latest tumult may also be a sign of longer-term up-swing for Pyth Network shareholders.

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.

The idea behind Citigroup and Pyth Network pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.

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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.