Stock price manipulation detection using a computational neural network model

Conference proceedings article

ผู้เขียน/บรรณาธิการ

กลุ่มสาขาการวิจัยเชิงกลยุทธ์

ไม่พบข้อมูลที่เกี่ยวข้อง

รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่ง: Leangarun T., Tangamchit P., Thajchayapong S.

ผู้เผยแพร่: Hindawi

ปีที่เผยแพร่ (ค.ศ.): 2016

หน้าแรก: 337

หน้าสุดท้าย: 341

จำนวนหน้า: 5

ISBN: 9781467377829

นอก: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84966472127&doi=10.1109%2fICACI.2016.7449848&partnerID=40&md5=826a23ba5004993c0fb1581733b9cd9d

ภาษา: English-Great Britain (EN-GB)

ดูบนเว็บไซต์ของสำนักพิมพ์

บทคัดย่อ

We investigated the characteristics of stock price manipulation. Two manipulation models were studied: 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 constructed mathematical models that use level 2 data for both procedures, and used them to generate a training set consisting of buy/sell orders within on order book of 10 depths. Order cancellations, which are important indicators for price manipulation, are also visible in our level 2 data. In this paper, we consider a challenging scenario where we attempt to use less-detailed level 1 data to detect manipulations even though using level 2 data is more accurate. 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 input. The neural network model achieved 88.28% for detecting pump-and-dump but it failed to model spoof trading effectively. ฉ 2016 IEEE.

คำสำคัญ

pump-and-dump, spoof trading, stock price manipulation