High-Frequency Trader Detection

Implementation Details

Class Names

Model Name
Parameters Class
Data Class

HighFrequencyTraderDetection

HighFrequencyTraderQueryParams

HighFrequencyTraderData

Import Statement

pythonCopyEditfrom satoshi_terminal.models.high_frequency_trader_detection import (
    HighFrequencyTraderDetection,
    HighFrequencyTraderQueryParams,
    HighFrequencyTraderData,
)

Parameters

Name
Type
Description
Default
Optional

blockchain_name

str

Blockchain to monitor for high-frequency trading activity.

None

False

time_window

int

Time window (in minutes) to detect trading patterns.

60

True

trade_frequency_threshold

int

Minimum number of trades per minute to flag as high-frequency.

10

True


Data

Name
Type
Description

trader_id

str

Identifier of the detected high-frequency trader (e.g., wallet address).

trade_count

int

Number of trades executed in the specified time window.

transaction_volume

float

Total transaction volume (in USD).

market_impact

float

Estimated market impact of the detected activity.

timestamp

datetime

Timestamp of the detection.


Key Features

  • Real-Time Detection: Monitors and flags high-frequency trading activity in real time.

  • Market Impact Estimation: Quantifies how detected trading patterns influence market prices.

  • Customizable Thresholds: Allows users to define thresholds for trade frequency and volume.

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