What will Pyth Network (PYTH) be valued at in 2024, 2025, 2025, and up to 2053? In this Pyth Network price prediction, we will look more closely at Pyth Network's current market position concerning trading volume, market capitalization, and past price movements to support investors set price targets and assess confidence levels. We will also break down expert analysis and technical indicators that give a better view of where PYTH might head in the coming months & years.

We utilize one of the most common statistical approaches to time-series forecasting known as the ARIMA model for the price prediction of cryptocurrencies.
ARIMA-ARMA plus differencing to create a stationary time series. A stationary series is one whose statistical properties are constant over time. Differencing cancels out any trend or pattern this method might have, enabling the model to interpret data structure and provide a good forecast.

According to our current Pyth Network price prediction, the value of Pyth Network is expected to INCREASE by 423%, reaching $1.28 by mid 2026. As of now, there are 4 technical analysis indicators showing BULLISH signals, while 12 are indicating BEARISH signals. Additionally, 1 indicators suggest a NEUTRAL stance, makes the general sentiment BEARISH for Pyth Network. Added to this is the fact that the Fear & Greed Index is reading 26, indicating that feelings around Pyth Network are cautious or slightly bearish. The aforementioned data places Pyth Network in Oversold state. Since October, Pyth Network has DECREASED by 7%. Based on this trend, we anticipate a possible stabilization in the coming month. By the end of January, the value of Pyth Network is projected to INCREASE by -31% and reach approximately $0.2723. At the moment, Pyth Network is trading BELOW the 200-day moving average, which indicates a BEARISH trend. Besides that, the price is BELOW the 50-day simple moving average (SMA), giving DOWNWARD momentum for Pyth Network. Currently, the RSI reads at 44.02, meaning therefore means that Pyth Network is in the position of NEUTRAL. The Relative Strength Index (RSI) data shows whether cryptocurrency is oversold (less than 30) or overbought (above 70), using an RSI-momentum oscillator.

Mastering Pyth Network technical analysis is the key to predicting its trends effectively. Our page will break down the essential components of Pyth Network technical analysis to equip you with the cryptocurrency market's ups and downs.

The presence of bearish signals across multiple momentum indicators for Pyth Network suggests a prevailing downward trend. Indicators like the Rate of Change, Awesome Oscillator, and Williams %R reflect declining momentum and a potential continuation of the downtrend. This alignment of bearish signals across various metrics reinforces the expectation of further price decreases.

• Relative Strength Index (RSI): The RSI for Pyth Network is 44.02, indicating a bearish trend. The market is showing signs of being in a downward solid phase, with prices likely making lower lows and lower highs. This suggests that bearish pressure could continue.
• Commodity Channel Index (CCI): The CCI for Pyth Network is -53.11, placing it in the neutral zone. This suggests that the market is balanced with no strong overbought or oversold conditions. Rate of Change (ROC): The ROC for Pyth Network is -11.32, which indicates a bearish signal. This suggests that Pyth Network is experiencing downward momentum, potentially leading to further price declines, and signaling a possible bearish trend.
• Awesome Oscillator (AO): AO for Pyth Network is below the zero line, indicating that momentum is shifting downward. This suggests a bearish trend, meaning the market is experiencing downward pressure, and potential sell or short opportunities might arise.
• Williamson%R (14): The Williams %R for Pyth Network is -56.36, indicating a bearish trend. This suggests downward momentum, with potential sell or short opportunities as prices continue to fall.
• Momentum: The momentum for Pyth Network is above zero, suggesting a bullish trend. The price is rising, and the upward trend may continue.

Neutral trend indicators for Pyth Network are evident when the MACD line is close to the signal line, ADX is between 20 and 25, or SAR dots are near the price level. These conditions suggest a lack of clear directional movement, with the market potentially consolidating or lacking a strong trend. Neutral signals imply that market conditions are indecisive, with no strong trend direction indicated.

• MACD (12,26,9): The MACD for Pyth Network is -0.02, placing it in the bearish zone. Not only has the MACD line crossed below the signal line, signaling a potential downtrend, but it is also below zero, confirming the continuation of the bearish trend. Traders might consider selling or taking short positions based on this signal.
• Average Directional Index - ADX (14): The ADX for Pyth Network is 21.22, placing it in the neutral zone. This suggests that the trend strength is uncertain at the moment, and the market does not show a clear directional bias. Traders may need to exercise caution, as the trend could shift either way.
• Parabolic SAR: The SAR for Pyth Network dots are positioned below the price, signalling a bullish trend. This indicates that the price is on an upward trend and may continue.

Neutral oscillator readings for Pyth Network are observed when the MFI is 50, the StochRSI is between 45 and 55, or the UO is between 45 and 55. These values imply a lack of strong momentum in either direction, suggesting that the market is in a consolidation phase or lacks a clear trend direction.

• Money Flow Index (MFI): The MFI for Pyth Network is 30.03, indicating bearish conditions. This suggests weak buying pressure and a potential downtrend.
• StochRSI – Stochastic Relative Strength Index: The StochRSI for Pyth Network is 20.57, indicating bullish momentum. This suggests intense buying pressure, with potential for further upward movement.
• Ultimate Oscillator (UO): The UO for Pyth Network is 55.30 neutral, showing no strong directional momentum, indicating the market is in a stable state without a clear trend.

The ARIMA model is defined by three parameters: p, d, and q.

• p: the number of past observations that the model will consider. This is the AR component which is expressed as below: $$ X_t = \phi_1 X_{t-1} + \phi_2 X_{t-2} + \cdots + \phi_p X_{t-p} + Z_t$$
  $$ X_t = \sum_{i=1}^{p} \phi_i X_{t-i} + Z_t $$
• d: the degree of differencing, which is the number of times needed to subtract the previous day’s price from today’s price to make the data consistent at all points in time. (The I component)
• q: the number of past errors in prediction. This is the MA component and is expressed as: $$ X_t = Z_t + \theta_1 Z_{t-1} + \theta_2 Z_{t-2} + \cdots + \theta_q Z_{t-q} $$
  $$ X_t = Z_t + \theta_1 Z_{t-1} + \theta_2 Z_{t-2} + \cdots + \theta_q Z_{t-q} $$

The ARIMA(p, d, q) model is the combination of the AR(p) and MA(q) and differencing: $$ \Delta dX_t = \sum_{i=1}^{p} \phi_i \Delta dX_{t-i} + Z_t + \sum_{i=1}^{q} \theta_i Z_{t-i} $$ Where:

• 𝑋𝑡: the time series X at a time t, and 𝑋𝑡−𝑖 is X at a previous point in time.
• 𝑍𝑡: the error terms or white noise, and 𝑍𝑡−𝑖 is Z at a previous point in time.
• 𝜙: the parameters of the autoregressive part of the model.
• 𝜃: the parameters of the moving average part of the model.
• ∇ 𝑑𝑋𝑡: the differenced time series (d times).