Predictive Whale Movement Analysis

Implementation Details

Class Names

Model Name	Parameters Class	Data Class
PredictiveWhaleMovement	PredictiveWhaleQueryParams	PredictiveWhaleData

Import Statement

pythonCopyEditfrom satoshi_terminal.models.predictive_whale_movement import (
    PredictiveWhaleMovement,
    PredictiveWhaleQueryParams,
    PredictiveWhaleData,
)

---

Parameters

Name	Type	Description	Default	Optional
wallet_address	Union[str, List[str]]	Wallet address(es) of whales to monitor.	None	False
movement_type	str	Type of movement to predict (e.g., "Accumulation," "Sell-off").	None	True
prediction_window	int	Forward-looking window (in hours) for movement predictions.	24	True

---

Data

Name	Type	Description
wallet_address	str	Address of the whale wallet being monitored.
predicted_movement	str	Predicted movement type (e.g., "Accumulation," "Sell-off").
confidence_score	float	AI-generated confidence score for the prediction.
market_impact_estimation	float	Projected market impact (% price change).
timestamp	datetime	Timestamp of the prediction.

---

Key Features

• Behavioral Pattern Analysis: Leverages historical behavior to predict future wallet movements.

• Market Impact Estimation: Calculates the potential impact of whale movements on token price and liquidity.

• Customizable Prediction Windows: Flexible time horizons for users to adapt predictions to their strategy.

• AI-Driven Confidence Scores: Provides clarity on the reliability of each prediction.