Stock Price Manipulation Detection Based on Mathematical Models

Abstract

Abstract-We investigated two popular scenarios of stock price manipulations: pump-and-dump and spoof trading. Pump-and-dump is a procedure to buy a stock and push its price up. Then, the manipulator dumps all of the stock he holds to make a profit. Spoof trading is a procedure to trick other investors that a stock should be bought or sold at the manipulated price. We proposed mathematical definitions based on level 2 data for both scenarios, and used them to generate a training set consisting of buy/sell orders in an order book of 10 depths. Order cancellations, which are important indicators for price manipulation, are also visible in this level 2 data. In this paper, we considered a challenging scenario where we attempted to use less-detailed level 1 data to detect manipulations even though using level 2 data is more accurate. First, we implemented feedforward neural network models that have level 1 data, containing less-detailed information (no information about order cancellation), but is more accessible to investors as an input. The neural network model achieved 88.28% accuracy for detecting pump-and-dump but it failed to model spoof trading effectively. Therefore, we further investigate the two-dimensional Gaussian model and show that it can detect spoof trading using level 2 data as input.Index Terms-Stock price manipulation, pump-and-dump, spoof trading, neural network. I. INTRODUCTIONStock market gathers participations from all kinds of investors. Millions of buy/sell orders enters the market every day. Stock price fluctuates due to several factors, mainly from the profit that the company can make. However, there are some investors who attempt to get benefits from the stock market using irregular trade behaviors that affect the stock price. Some of these attempts are illegal. The control of these irregular trade behaviors is difficult due to the large amount of trade data.Automatic computer algorithms for detecting price manipulation are the solution to this problem. It can scan large amount of price data and spot manipulations in a short time. Price manipulation can be divided into three categories: trade-based, information-based, and action-based. This research discusses a mathematical model that classifies trade-based price manipulations from normal trades in stock markets. Two types of manipulations are investigated: pump-and-dump and spoof trading. Pump-and-dump is an action of buying stock, making the price to go higher, and then selling to others for a profit. Spoof trading is an action of sending passive orders in large volume to trick others that the stock should be sold at that price. After the manipulators secure enough benefits from that artificial price, they cancel their passive orders. These actions allow the manipulators to sell their stock at a price higher than usual.The effectiveness of manipulation detection depends on how much the information we have. We rely on using the price data that buyers and sellers sent to the market. The trade data can be classified into two levels. Level 1...

Order flow dynamics for prediction of order cancelation and applications to detect market manipulation

“…The same authors extended their work in Leangarun, Tangamchit, and Thajchayapong () and used the same framework and report the same results as in Leangarun et al. (); however, they were able to detect spoofing trading using data with higher granularity and a two‐dimensional Gaussian model for anomaly detection.…”

Unravelling the JPMorgan spoofing case using particle physics visualization methods

“…Mendonça and de Genaro (2020) generated 1‐min LOB snapshots from order data and used both datasets to detect spoofing on the Brazilian Stock Exchange. Leangarun et al (2016) tried to detect, among others, spoofing in three NASDAQ stock markets by training neural networks and using 1‐min LOB intervals.…”

To Detect Irregular Trade Behaviors In Stock Market By Using Graph Based Ranking Methods

“…In this error function ( ) , and belong to 1 . Please note that = ∑ , and is the positive regularization parameter.…”

“…In the stock market, there are some investors who try to get benefits from the stock market by using irregular trade behaviors that affect the stock price. These irregular trade behaviors include pump-and-dump and spoof trading [1]. These trade behaviors are illegal.…”