The Influence of Volume and Volatility on Predicting Shanghai Stock Exchange Trends

被引：0
|
作者：
Pierrot, Romain [1 ]
Liu, Hongyan [1 ]
机构：
[1] Tsinghua Univ, Sch Econ & Management, Beijing 100084, Peoples R China
来源：
FIFTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 1, PROCEEDINGS | 2008年
关键词：
Stock Data Mining; Time Series forecasting; Associative Rule Mining; Associative Classification;
D O I：
10.1109/FSKD.2008.88
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Most of the previous studies concerning mining association rules from stock time series simply use confidence and support thresholds. In this paper we introduce two new thresholds - trading volume and stock volatility- that suit stock time series behaviour better. In this study, we test the influence of volatility and volume on share price weekly trends. Various experimental results yield the strong correlation between trading volume and classifying accuracy. We use the mined rules to classify and predict future trends. A new method, namely weighted confidence, is proposed for carrying out associative classification/prediction. Its accuracy is equivalent to other traditional measures.
引用
收藏
页码：470 / 474
页数：5
相关论文
共 50 条
  • [1] Volatility, Spread and Volume's Impact on Trading Duration-Evidence from Shanghai Stock Exchange
    Zhang, Xiaoxiao
    Wu, Qizong
    [J]. PROCEEDINGS OF 2012 2ND INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT 2012), 2012, : 1150 - 1153
  • [2] Interday and intraday volatility: Additional evidence from the Shanghai stock exchange
    Tian G.G.
    Guo M.
    [J]. Review of Quantitative Finance and Accounting, 2007, 28 (3) : 287 - 306
  • [3] Predicting stock index volatility: Can market volume help?
    Brooks, C
    [J]. JOURNAL OF FORECASTING, 1998, 17 (01) : 59 - 80
  • [4] Modeling Shanghai stock market volatility
    J. Xu
    [J]. Annals of Operations Research, 1999, 87 : 141 - 152
  • [5] Modeling Shanghai stock market volatility
    Xu, JG
    [J]. ANNALS OF OPERATIONS RESEARCH, 1999, 87 (0) : 141 - 152
  • [6] No news is not good news: evidence from the intra-day return volatility-volume relationship in Shanghai Stock Exchange
    Krishnamurti, Chandrasekhar
    Tian, Gary Gang
    Xu, Min
    Li, Guangchuan
    [J]. JOURNAL OF THE ASIA PACIFIC ECONOMY, 2013, 18 (01) : 149 - 167
  • [7] Shanghai Stock Composite Index moving trends and volatility with Markov Regime Switching Model
    Dai, Hongkun
    Zhang, Lei
    [J]. PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT, 2010, : 244 - 247
  • [8] Trading intensity and the volume-volatility relationship on the Tunis Stock Exchange
    Karaa, Rabaa
    Slim, Skander
    Hmaied, Dorra Mezzez
    [J]. RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE, 2018, 44 : 88 - 99
  • [9] VOLUME, VOLATILITY, AND NEW-YORK-STOCK-EXCHANGE TRADING HALTS
    LEE, CMC
    READY, MJ
    SEGUIN, PJ
    [J]. JOURNAL OF FINANCE, 1994, 49 (01): : 183 - 214
  • [10] Impact of CPEC on PSX and Shanghai Stock Exchange Market Volatility Using GARCH Method
    Mehmood, Waqas
    Ahmad, Nawaz
    [J]. SUSTAINABLE ECONOMIC GROWTH, EDUCATION EXCELLENCE, AND INNOVATION MANAGEMENT THROUGH VISION 2020, VOLS I-VII, 2017, : 568 - 585
12345