Correlation Between Pyth Network and Near

Can any of the company-specific risk be diversified away by investing in both Pyth Network and Near 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 Pyth Network and Near into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between Pyth Network and Near, you can compare the effects of market volatilities on Pyth Network and Near 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 Pyth Network with a short position of Near. Check out your portfolio center. Please also check ongoing floating volatility patterns of Pyth Network and Near.

Diversification Opportunities for Pyth Network and Near

0.8

Correlation Coefficient

Pyth Network  Near

Very poor diversification

The 3 months correlation between Pyth and Near is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Pyth Network and Near in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Near and Pyth Network 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 Pyth Network are associated (or correlated) with Near. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Near has no effect on the direction of Pyth Network i.e., Pyth Network and Near go up and down completely randomly.

Pair Corralation between Pyth Network and Near

Assuming the 90 days trading horizon Pyth Network is expected to generate 1.02 times more return on investment than Near. However, Pyth Network is 1.02 times more volatile than Near. It trades about 0.22 of its potential returns per unit of risk. Near is currently generating about 0.21 per unit of risk. If you would invest  26.00  in Pyth Network on September 1, 2024 and sell it today you would earn a total of  24.00  from holding Pyth Network or generate 92.31% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Strong
Accuracy	100.0%
Values	Daily Returns

Pyth Network  vs.  Near

Pyth Network

Risk-Adjusted Performance

17 of 100

Solid

Compared to the overall equity markets, risk-adjusted returns on investments in Pyth Network are ranked lower than 17 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady fundamental indicators, Pyth Network exhibited solid returns over the last few months and may actually be approaching a breakup point.

Near

Risk-Adjusted Performance

16 of 100

Solid

Compared to the overall equity markets, risk-adjusted returns on investments in Near are ranked lower than 16 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady fundamental indicators, Near exhibited solid returns over the last few months and may actually be approaching a breakup point.

Pair Trading with Pyth Network and Near

The main advantage of trading using opposite Pyth Network and Near positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Pyth Network position performs unexpectedly, Near 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 Near will offset losses from the drop in Near's long position.

The idea behind Pyth Network and Near 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 Crypto Correlations module to use cryptocurrency correlation module to diversify your cryptocurrency portfolio across multiple coins.