Pyth Network PYTH
Rank #117Pyth Network (PYTH) trades at $0.0486, the 117th-largest cryptocurrency by market capitalisation at $392.6 M. Over the past 24 hours it is -5.02% and over the week +10.77%. Our composite Price Strength score reads 42/100, liquidity health 37/100, and 7-day annualised volatility sits near 90% — higher than 88% of the top 100 coins.
Pyth Network · At a glance
Ecoonomia composite scores derived from live market data. Methodology →
Pyth Network · Price chart (7 days)
Price performance
| 1h | 24h | 7d | 14d | 30d | 60d | 200d | 1y |
|---|---|---|---|---|---|---|---|
| -1.58% | -5.02% | +10.77% | +25.51% | +24.68% | +14.26% | -18.81% | -59.71% |
Market statistics
Pyth Network · Market analysis
Volatility & risk
Realised volatility for PYTH is elevated, with a 7-day annualised reading near 90%, placing it above 88% of the top 100 by volatility. Expect wide swings and size positions accordingly.
Liquidity & depth
Around $40.1 M changed hands in 24 hours — about 10.2% of market value turning over daily — which we read as adequate liquidity for its size.
Correlation with Bitcoin
Over the past week PYTH's returns correlate 0.04 with Bitcoin: it moves with relative independence from Bitcoin. Correlation regimes shift, so treat this as a snapshot.
PYTH to USD
| PYTH | USD |
|---|---|
| 0.5 PYTH | $0.0243 |
| 1 PYTH | $0.0486 |
| 5 PYTH | $0.2428 |
| 1 PYTH | $0.4856 |
| 25 PYTH | $1.21 |
| 5 PYTH | $2.43 |
| 1 PYTH | $4.86 |
| 5 PYTH | $24.28 |
| 1, PYTH | $48.56 |
| 10, PYTH | $485.65 |
Supply & tokenomics
Pyth Network has a circulating supply of 7,874,981,681 PYTH against a hard cap of 10,000,000,000 — 78.7% of the maximum already exists. A meaningful share is still to be released, so emission schedules are worth tracking.
Pyth Network · Price prediction 2026–2027
| Period | Low | Average | High | Potential | Bias |
|---|---|---|---|---|---|
| 24 Hours | $0.0476 | $0.0486 | $0.0499 | -0.01% | Neutral |
| 7 Days | $0.0460 | $0.0485 | $0.0521 | -0.04% | Neutral |
| 30 Days | $0.0433 | $0.0485 | $0.0559 | -0.18% | Neutral |
| 3 Months | $0.0392 | $0.0483 | $0.0611 | -0.55% | Neutral |
| 6 Months | $0.0353 | $0.0480 | $0.0661 | -1.10% | Neutral |
| 1 Year | $0.0297 | $0.0475 | $0.0728 | -2.19% | Neutral |
| End of 2026 | $0.0359 | $0.0481 | $0.0653 | -1.00% | Neutral |
| End of 2027 | $0.0257 | $0.0470 | $0.0772 | -3.18% | Neutral |
| 2031 | $0.006991 | $0.0435 | $0.0951 | -10.50% | Bearish |
The ensemble blends a technical (momentum), statistical (volatility) and relative (comparable peers) model. Probabilistic scenarios, not financial advice.
About Pyth Network
How Pyth Network works
Pyth Network powers a decentralised oracle network that feeds real-world data (prices, events, randomness) to smart contracts on many blockchains. A network of independent node operators is paid in PYTH to deliver and secure that data.
What is Pyth Network used for?
PYTH is used to pay node operators and secure the network; the project's value is tied to how much value across DeFi depends on its data feeds.
Risks & considerations
All crypto-assets are volatile and high-risk; never invest more than you can afford to lose. Specific risks include data-feed manipulation, node collusion and over-reliance of DeFi on a single oracle provider.
Where to buy Pyth Network
Regional platforms
In Latin America and Spain you can buy Pyth Network on local Spanish-speaking platforms:
| Bitso | Mexico · LatAm |
| Lemon · Buenbit | Argentina |
| Bit2Me · Bitnovo | Spain |
| Binance · Coinbase · Kraken | Global |
Pyth Network vs comparable coins
| Coin | Price | 24h | 7d | Cap |
|---|---|---|---|---|
| Venice Token VVV | $11.04 | +0.51% | -1.30% | $522.6 M |
| USX USX | $0.9998 | -0.03% | +0.02% | $522.9 M |
| YLDS YLDS | $0.9998 | -0.01% | +0.01% | $551.8 M |
| Usual USD USD0 | $0.9986 | -0.01% | +0.04% | $552.4 M |
| XDC Network XDC | $0.0278 | +2.01% | +1.78% | $553.5 M |
| Flare FLR | $0.006499 | -2.70% | -2.44% | $564.3 M |
Pyth Network · FAQ
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Disclaimer: informational content only, not financial advice. Cryptocurrencies are volatile and high-risk. Predictions are model estimates and may be inaccurate.