Wash Trade Type 1 Detection
Description
This test identifies accounts engaging in wash trading, a manipulative practice where a trader buys and sells the same security to create misleading market activity. This specific test targets self-trading, where the same individual or entity acts as both buyer and seller, inflating trading volumes or distorting price signals.
Use Cases
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Market Manipulation Detection: Identify traders engaging in self-trading to artificially inflate trading volumes or distort price signals.
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Regulatory Compliance: Support adherence to financial regulations by flagging wash trades, helping platforms avoid penalties and maintain transparency.
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Fraud Prevention: Protect market participants by detecting and mitigating fraudulent behaviors that could harm other investors or destabilize the market.
Required Data
Trades Data
| Variable | Description |
|---|---|
timestamp | Timestamp of the trade made (YYYY-MM-DD hh:mm:ss). |
user_id | User ID to identify the individual user. |
counterparty_user_id | The user ID of the counterparty in the trade (buyer or seller). |
symbol_pair | The asset symbol; e.g., BTCUSDT, SHIBETH, DOGEUSDT. |
side | Whether the trade is a BUY or SELL. |
price_usd | The price of the symbol in USD. |
price | The execution price of the symbol pair. |
amount | The amount of the symbol being traded. |
Parameters
| Parameter | Description | Type | Default Value | Configurable |
|---|---|---|---|---|
analysis_minimum_transaction_count | Minimum number of transactions required to flag as Wash Trade Type 1. | Integer | 0 | Yes |
analysis_minimum_aggregate_dollar_threshold | Minimum total dollar value required to flag as Wash Trade Type 1. | Float | 0 | Yes |
analysis_window | Time window (in days) for analyzing wash trade activity. | Integer | 1 | Yes |
create_ticket | Flag to determine if tickets should be created for alerts. | Boolean | True | Yes |
Methodology
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Identify Self-Trading Filter trades where the user ID matches the counterparty ID, indicating self-trading activity.
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Aggregate and Evaluate Data Group the filtered data by user to calculate key metrics, such as the primary traded symbol, total transaction count, and cumulative trade value. Apply thresholds to flag accounts exhibiting significant self-trading behavior.
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Generate Outputs Create tickets and generate files related to the flagged user.