CHANGE DETECTION OF ORDERS IN STOCK MARKETS USING A GAUSSIAN MIXTURE MODEL

被引:8
|
作者
Miyazaki, Bungo [1 ]
Izumi, Kiyoshi [1 ,2 ]
Toriumi, Fujio [1 ]
Takahashi, Ryo [3 ]
机构
[1] Univ Tokyo, Bunkyo Ku, Tokyo, Japan
[2] CREST, JST, Chiyoda Ku, Tokyo, Japan
[3] Japan Exchange Grp Inc, Chuo Ku, Tokyo, Japan
关键词
Gaussian mixture model; stock market; order book; insider trading; change detection;
D O I
10.1002/isaf.1356
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
We propose a method for detecting changes in the order balance in stock markets by applying a stochastic model to the feature vectors extracted from the order-book data of stocks. First, the data are divided into training and test periods. Next, a Gaussian mixture model is estimated from the feature vectors extracted from the order-book data in the training period. Finally, the goodness of fit of the feature vectors in the test period over this model is calculated. Using the proposed method, we found that the order balances of stocks for which insider trading was reported were unusual. Copyright (C) 2014 John Wiley & Sons, Ltd.
引用
收藏
页码:169 / 191
页数:23
相关论文
共 50 条
  • [21] Vehicle Detection and Tracking using Gaussian Mixture Model and Kalman Filter
    Indrabayu
    Bakti, Rizki Yusliana
    Areni, Intan Sari
    Prayogi, A. Ais
    [J]. 2016 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND CYBERNETICS, 2016, : 115 - 119
  • [22] Stock price prediction using a novel approach in Gaussian mixture model-hidden Markov model
    Gopinathan, Kala Nisha
    Murugesan, Punniyamoorthy
    Jeyaraj, Joshua Jebaraj
    [J]. INTERNATIONAL JOURNAL OF INTELLIGENT COMPUTING AND CYBERNETICS, 2024, 17 (01) : 61 - 100
  • [23] Spatio-contextual Gaussian mixture model for local change detection in underwater video
    Rout, Deepak Kumar
    Subudhi, Badri Narayan
    Veerakumar, T.
    Chaudhury, Santanu
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2018, 97 : 117 - 136
  • [24] Anomaly Detection Using Gaussian Mixture Probability Model to Implement Intrusion Detection System
    Blanco, Roberto
    Malagon, Pedro
    Briongos, Samira
    Moya, Jose M.
    [J]. HYBRID ARTIFICIAL INTELLIGENT SYSTEMS, HAIS 2019, 2019, 11734 : 648 - 659
  • [25] A Gaussian Mixture Model with Gaussian Weight Learning Rate and Foreground Detection using Neighbourhood Correlation
    Panda, Deepak Kumar
    Meher, Sukadev
    [J]. 2013 IEEE ASIA PACIFIC CONFERENCE ON POSTGRADUATE RESEARCH IN MICROELECTRONICS & ELECTRONICS (PRIMEASIA), 2013, : 158 - 163
  • [26] A Small Sample-Based Multiclass Change Detection Method Using Change Vector Analysis With Adaptive Weight Gaussian Mixture Model
    He, Fachuan
    Chen, Hao
    Yang, Shuting
    Guo, Zhixiang
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 61 : 1 - 16
  • [27] Robust Background Generation Using a Modified Mixture of Gaussian Model for Object Detection
    Maik, Vivek
    Kim, Hyungtae
    Kim, Daehee
    Chae, Eunjung
    Paik, Joonki
    [J]. 18TH IEEE INTERNATIONAL SYMPOSIUM ON CONSUMER ELECTRONICS (ISCE 2014), 2014,
  • [28] Fault detection for turbine engine disk using adaptive Gaussian mixture model
    Chen, Jiusheng
    Zhang, Xiaoyu
    Zhang, Na
    Guo, Kai
    [J]. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING, 2017, 231 (10) : 827 - 835
  • [29] Automated Detection of Root Crowns using Gaussian Mixture Model and Bayes Classification
    Kumar, Pankaj
    Cai, Jinhai
    Miklavcic, Stan
    [J]. 2012 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COMPUTING TECHNIQUES AND APPLICATIONS (DICTA), 2012,
  • [30] Road Crack Detection Using Gaussian Mixture Model for Diverse Illumination Images
    Chen, Da-Ren
    Chiu, Wei-Min
    [J]. 2020 30TH INTERNATIONAL TELECOMMUNICATION NETWORKS AND APPLICATIONS CONFERENCE (ITNAC), 2020, : 189 - 194