经济理论与实践

基于小波包去噪的量价择时策略研究

  • 王峰虎 ,
  • 许冉 ,
  • 齐祥会 ,
  • 贺毅岳
展开
  • 西北大学 经济管理学院,陕西 西安 710127
王峰虎(1970-),男,副教授,博士,研究方向:金融投资与风险管理;许冉(1991-),女,硕士研究生,研究方向:金融投资;齐祥会(1993-),男,硕士研究生,研究方向:金融投资;贺毅岳(1982-),男,副教授,博士,研究方向:数据挖掘和金融数据分析。

收稿日期: 2017-06-11

  网络出版日期: 2020-11-27

基金资助

教育部人文社会科学研究青年项目“基于多尺度时序模式挖掘的股票在线算法交易策略研究”(16XJC630001);陕西省自然科学基金项目“基于多粒度时序模式挖掘与预测的股票算法交易策略研究”(2015JQ7278)

A Study of Timing Strategy of Volume and Price Based on Wavelet Denoising

  • Wang Fenghu ,
  • Xu Ran ,
  • Qi Xianghui ,
  • He Yiyue
Expand
  • Northwest University, Xi’an 710127, China

Received date: 2017-06-11

  Online published: 2020-11-27

摘要

资产价格与成交量之间具有一定的相关关系。本文引入了小波包非线性阈值去噪方法以有效消除上证综指量价序列的噪声,去噪后的协整分析表明,月度成交量变动可以解释月度价格变动,依据月度量价关系可以判断市场长期趋势;结合更灵敏的短期均线指标,本文提出了具体的量价择时策略。回测结果表明,小波包去噪对提高策略绩效有显著贡献。

本文引用格式

王峰虎 , 许冉 , 齐祥会 , 贺毅岳 . 基于小波包去噪的量价择时策略研究[J]. 新疆财经, 2017 , 0(5) : 14 -21 . DOI: 10.16716/j.cnki.65-1030/f.2017.05.002

Abstract

There is a certain correlation between asset prices and volume. This paper eliminates the noise in time series of price and volume of Shanghai Composite Index by using the wavelet nonlinear threshold denoising method, and the denoised co-integration analysis indicates the degree of price changes can be explained on the basis of monthly volume changes, and meanwhile the relation of price volume can determine the long-term trends in the market; combined with more sensitive short-term moving average index, a specific timing strategy based on these indicators is proposed. The back-testing results show that wavelet denoising can improve the performance of the strategy significantly.

参考文献

[1]Clark P.A..Subordinated Stochastic Process Models with Finite Variance for Speculative Prices[J].Econometrica,1973(41):135-155.
[2]Chen,Shyh-Wei and Chen,Chun-Wei.Testing for Nonlinear Granger Causality in the Price-Volume Relations of Taiwan’s Stock and Foreign Exchange Markets[J].Economics and Management,2006,2(1):21-51.
[3]Hiemstra C.,Jones J.D..Testing for Linear and Nonlinear Granger Causality in the Stock Price—Volume Relation[J].Finance,1994,49(5):1639-1664.
[4]陈晓杰,黄志刚.基于价量关系的股指期货投资技术——以台湾加权指数期货为例[J].金融理论与实践,2008(3):107-109.
[5]S Lahmiri.Multi-Scaling Analysis of the S&P 500 under Different Regimes in Wavelet Domain[J].International Journal of Strategic Decision Sciences,2014,5(2):43-55.
[6]刘晓迪.基于小波变换的金融时间序列奇异点识别模型与研究[D].昆明:昆明理工大学,2011.
[7]张维,刘博,熊熊.日内金融高频数据的异常点检测[J].系统工程理论与实践,2009,29(5):44-50.
[8]曲文龙,杨炳儒,贺毅朝.基于奇异事件特征的时间序列相似模式匹配[J].计算机工程,2007,33(23):19-21.
[9]兰秋军,马超群,文凤华.金融时间序列去噪的小波变换方法[J].科技管理研究,2004(6):118-120.
[10]章浙涛,等.小波包多阀值去噪法及其在形变分析中的应用[J].测绘学报,2014,43(1):13-20.
[11]丁玲娟.基于小波分析和ARMA-SVM模型的股票指数预测分析[D].上海:华东师范大学,2012.
[12]Donoho.D.L.,Johnstone I.M..Ideal Spatial Adaptation by Wavelet Shrinkage[J].Biometrika,1994,81(3):425-455.
[13]王红兵,谢江.基于成交量波动率的行业配置因子研究[R].深圳:华泰联合证券,2012.
[14]King Benjamin F..Market and Industry Factors in Stock Price Behavior[J].The Journal of Businesss,1996,39(1):139-190.
[15]Cavaglia,Stefano,and Christopher Brightman, and Michael Aked.The Increasing Importance of Industry Factors[J].Financial Analysts Journal,2006,56(5):42-54.
[16]Hong,Harrison,Walter Torous and Rossen Valkanov.Do Industries Lead Stock Markets?[J].Journal of Financial Economics,2007,83(2):367-396.
文章导航

/