🔮Price Prediction Model

This page details Jarvis' ERC-20 Token Price Prediction Model.

Price Analysis & Technical Price Prediction:

Jarvis AI’s Price Prediction Model leverages advanced machine learning techniques to forecast future price movements of cryptocurrency tokens on the Ethereum Blockchain.

The model begins by collecting: historical data, includingprice trends, trading volumes,market capitalization, and otherrelevant on-chain data.

Through meticulous data preprocessing and feature engineering, it is ensured that the input is conducive to Jarvis’s effective learning.

Employing a time-series prediction approach, a Long Short-Term Memory (LSTM) network has been selected for Jarvis’s price prediction Model, as a result of its capability to capture intricate patterns in cryptocurrency market dynamics.

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At its core, Jarvis’s Price Prediction Model is based on the interpretation of disparities between the traded token’s moving averages and discrepancies in its volume metrics.

Evaluated moving averages include:

• The Simple Moving Average (SMA)

• The Exponential Moving Average (EMA)

• The Weighted Moving Average (WMA)

Evaluated volume metrics include:

• Trading Volume

• Relative Volume

• On-Balance Volume (OBV).

• Volume Moving Averages are also evaluated.

Jarvis’s price prediction accuracy is further improved through the evaluation and interpretation of other technical factors.

These include:

• The Fibonacci Retracement Levels

• The Relative Strength Index (RSI)

• The Moving Average Convergence Divergence (MACD).

The combined interpretation of all factors mentioned above allows Jarvis to accurately predict a token’s price movement. The model is trained on historical data, undergoing constant evaluation and fine-tuning to optimize its performance. Regular updates and periodic retraining mechanisms are implemented to ensure adaptability to the evolving nature of the cryptocurrency market.