Correlation Between BLZ and Pyth Network

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

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

Diversification Opportunities for BLZ and Pyth Network

0.66

Correlation Coefficient

BLZ  Pyth Network

Poor diversification

The 3 months correlation between BLZ and Pyth is 0.66. Overlapping area represents the amount of risk that can be diversified away by holding BLZ and Pyth Network in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Pyth Network and BLZ 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 BLZ 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 BLZ i.e., BLZ and Pyth Network go up and down completely randomly.

Pair Corralation between BLZ and Pyth Network

Assuming the 90 days trading horizon BLZ is expected to generate 1.83 times less return on investment than Pyth Network. But when comparing it to its historical volatility, BLZ is 1.52 times less risky than Pyth Network. It trades about 0.18 of its potential returns per unit of risk. Pyth Network is currently generating about 0.21 of returns per unit of risk over similar time horizon. If you would invest  10.00  in Pyth Network on April 28, 2025 and sell it today you would earn a total of  3.00  from holding Pyth Network or generate 30.0% return on investment over 90 days.

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

BLZ  vs.  Pyth Network

BLZ

Risk-Adjusted Performance

Insignificant

Compared to the overall equity markets, risk-adjusted returns on investments in BLZ are ranked lower than 4 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady basic indicators, BLZ exhibited solid returns over the last few months and may actually be approaching a breakup point.

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 rather sound fundamental indicators, Pyth Network is not utilizing all of its potentials. The latest stock price tumult, may contribute to shorter-term losses for the shareholders.

Pair Trading with BLZ and Pyth Network

The main advantage of trading using opposite BLZ and Pyth Network positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BLZ 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 BLZ 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 Fundamental Analysis module to view fundamental data based on most recent published financial statements.