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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.

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