Correlation Between Pyth Network and NKN

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

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

Diversification Opportunities for Pyth Network and NKN

0.98

Correlation Coefficient

Pyth Network  NKN

Almost no diversification

The 3 months correlation between Pyth and NKN is 0.98. Overlapping area represents the amount of risk that can be diversified away by holding Pyth Network and NKN in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on NKN 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 NKN. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of NKN has no effect on the direction of Pyth Network i.e., Pyth Network and NKN go up and down completely randomly.

Pair Corralation between Pyth Network and NKN

Assuming the 90 days trading horizon Pyth Network is expected to under-perform the NKN. In addition to that, Pyth Network is 1.39 times more volatile than NKN. It trades about -0.15 of its total potential returns per unit of risk. NKN is currently generating about -0.19 per unit of volatility. If you would invest  9.11  in NKN on December 29, 2024 and sell it today you would lose (4.64) from holding NKN or give up 50.93% of portfolio value over 90 days.

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

Pyth Network  vs.  NKN

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.

NKN

Risk-Adjusted Performance

Very Weak

Over the last 90 days NKN 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 basic 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 NKN shareholders.

Pair Trading with Pyth Network and NKN

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

The idea behind Pyth Network and NKN 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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.