Excessive Accumulation - Own
Description
This test identifies patterns of excessive asset accumulation by comparing a user's recent trading activity to their own historical benchmarks. It evaluates whether a user's trades deviate significantly from their historical behavior, flagging potential anomalies for further investigation.
Use Cases
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Market Manipulation Detection: Identify users engaging in unusual patterns of asset accumulation, which may signal attempts to manipulate prices or create artificial demand or supply.
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Insider Trading Surveillance: Flag users whose trading behavior deviates significantly from historical norms, potentially indicating knowledge of non-public information or coordinated trading activity.
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Risk and Exposure Monitoring: Detect users accumulating assets at an unusual rate, which could pose risks to liquidity or lead to concentrated exposure that impacts the exchange’s stability.
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. |
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. |
amount | The amount of the symbol being traded. |
Parameters
| Parameter | Description | Type | Default Value | Configurable |
|---|---|---|---|---|
analysis_window | Number of days over which trades are analyzed for alerts. | Integer | 1 | Yes |
historical_window | Number of days to look back for historical trades. | Integer | 7 | Yes |
analysis_minimum_aggregate_dollar_threshold | Minimum trade value in USD to qualify for alerts. | Float | 10000.0 | Yes |
analysis_minimum_transaction_count_threshold | Minimum transaction count per user in analysis period to be considered. | Integer | 5 | Yes |
historical_minimum_number_transactions | Minimum number of historical transactions required to calculate user-specific characteristics. | Integer | 10 | Yes |
historical_minimum_number_unique_days | Minimum number of unique dates required in the historical period. | Integer | 5 | Yes |
analysis_buy_proportion_threshold | Threshold for the proportion of buys to flag accumulation in analysis window. | Float | 0.7 | Yes |
analysis_buy_trade_count_threshold | Threshold for the minimum buy trade counts. | Integer | 5 | Yes |
analysis_sell_trade_count_threshold | Threshold for the minimum sell trade counts. | Integer | 5 | Yes |
Methodology
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Aggregate Historical and Recent Trade Data Calculate total, buy, and sell dollar values for each user over the historical lookback period and the analysis period.
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Compute Proportions and Benchmarks Determine the proportions of buys and sells relative to total trade value and calculate historical mean and standard deviation for these metrics, excluding users with insufficient trades or unique dates.
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Flag Anomalies in Buy and Sell Activity Compare recent trade proportions against user-specific historical benchmarks (own history) to identify excessive accumulation.
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Generate Alerts and Reports Create CSV files or tickets for flagged users, summarizing their trade metrics and deviations for further investigation.