基于股市和汇市成交量信息视角的股价波动预测
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摘要
以往研究忽略了汇市成交量包含的信息对股价波动的影响,可能导致模型参数的有偏估计.基于泊松分布的随机波动率模型不仅可有效解决传统做法对成交量信息使用不足的问题,而且通过将汇市成交量信息引入模型,与现有文献形成有益补充.通过SMC算法编程实现了SV-VOL模型的有效估计,发现股市成交量信息有助于股价波动预测;汇市成交量信息是通过股市流入净资本这一间接渠道最终影响股票收益率与股市量价关系.
Previous studies have neglected the influence of the information contained in the volume of foreign exchange market on the stock price volatility, which leads to the biased estimation of the model parameters probably. SV-VOL model based on Poisson distribution, not only can effectively solve the traditional the problem of insufficient use of volume information, but also form a useful supplement to the existing literature by introducing the volume information into the model through weighted processing.SMC algorithm by programming to achieve the effective estimation of the SV-VOL model, found that the stock market trading volume information is helpful to the stock price volatility forecast, exchange market volume information ultimately affects stock returns and stock price-volume relationship through the indirect channel of net capital in-flows of stock market.
Previous studies have neglected the influence of the information contained in the volume of foreign exchange market on the stock price volatility, which leads to the biased estimation of the model parameters probably. SV-VOL model based on Poisson distribution, not only can effectively solve the traditional the problem of insufficient use of volume information, but also form a useful supplement to the existing literature by introducing the volume information into the model through weighted processing.SMC algorithm by programming to achieve the effective estimation of the SV-VOL model, found that the stock market trading volume information is helpful to the stock price volatility forecast, exchange market volume information ultimately affects stock returns and stock price-volume relationship through the indirect channel of net capital in-flows of stock market.
引文
[1]吴冲锋,吴文锋.基于成交量的股价序列分析[J].系统工程理论方法应用,2001,10(1):1-7.Wu C F, Wu W F. An analysis of volume-based stock price[J]. Systems Engineering—Theory Methodology Application, 2001, 10(1):1-7.
[2]Smirlock M, Starks L. An empirical analysis of the stock price-volume relationship[J]. Journal of Banking&Finance, 1988, 12(1):31-41.
[3]陈浪南,罗嘉雯,刘昊.基于TVP-VAR-GCK模型的量价时变关系研究[J].管理科学学报,2015, 18(9):72-85.Chen L N, Luo J W, Liu H. Time-varying price-volume relationship based on TVP-VAR-GCK model[J]. Journal of Management Sciences in China, 2015, 18(9):72-85.
[4]吴鑫育,李心丹.中国股市量价尾部相关性研究——基于随机copula模型的实证[J].金融理论与实践,2017(1):93-97.Wu X Y, Li X D. Tail correlation of volume and price in China's stock market—Empirical study based on stochastic copula model[J]. Financial Theory&Practice, 2017(1):93-97.
[5]刘俊山,张陶伟.成交量与股价波动ARCH效应的实证研究[J].财经科学,2004(3):14-17.Liu J S, Zhang T W. Empirical study on ARCH effect of volume and stock price fluctuation[J]. Finance and Economics, 2004(3):14-17.
[6]郑方镳,吴超鹏,吴世农.股票成交量与收益率序列相关性研究——来自中国股市的实证证据[J].金融研究,2007(3A):140-150.Zheng F B, Wu C P, Wu S N. Study on correlation between stock volume and yield series—Empirical evidence from China's stock market[J]. Journal of Financial Research, 2007(3A):140-150.
[7]唐齐鸣,刘亚清.市场分割下A、B股成交量、收益率与波动率之间关系的SVAR分析[J].金融研究,2008(2):113-126.Tang Q M, Liu Y Q. SVAR analysis of the relationship between A, B stock volume, yield and volatility under market segmentation[J]. Journal of Financial Research, 2008(2):113-126.
[8]张永东,黎荣舟.上海股市日内波动性与成交量之间引导关系的实证分析[J].系统工程理论与实践,2003, 23(2):19-23.Zhang Y D, Li R Z. Testing for causality in the intraday volatility-volume relation:Shanghai stock market's evidence[J]. Systems Engineering—Theory&Practice, 2003, 23(2):19-23.
[9]罗登跃,王春峰.上证指数收益率、波动性与成交量动态关系研究——基于日数据的非线性动力学实证分析[J].系统工程理论与实践,2005, 25(7):41-48.Luo D Y, Wang C F. Empirical analysis of the relation between daily return rate, volatility and trading volume of Shanghai stock market comprising index based on nonlinar dynamics[J]. Systems Engineering—Theory&Practice, 2005, 25(7):41-48.
[10]Hiemstra C, Jones J D. Testing for linear and nonlinear Granger causality in the stock price-volume relation[J].The Journal of Finance, 1994, 49(5):1639-1664.
[11]Zhang W, Bi Z, Shen D. Investor structure and the price-volume relationship in a continuous double auction market:An agent-based modeling perspective[J]. Physica A:Statistical Mechanics and its Applications, 2017,467:345-355.
[12]张庆翠,王春峰.中国股价波动性与成交量共同的长期记忆性研究[J].管理科学学报,2005, 8(2):38-45.Zhang Q C, Wang C F. Research on common long memory between trading volume and volatility in Chinese stock market[J]. Journal of Management Sciences in China, 2005,8(2):38-45.
[13]Chen S H, Liao C C. Agent-based computational modeling of the stock price-volume relation[J]. Information Sciences, 2005, 170(1):75-100.
[14]唐勇.基于高频数据的波动率与成交量动态关系研究[J].成都理工大学学报(社会科学版),2011,19(3):8-16.Tang Y. Research on dynamic relationship between volatility and trading volume based on high-frequency data[J].Journal of Chengdu University of Technology(Social Sciences), 2011, 19(3):8-16.
[15]王鹏.成交量信息有助于预测中国股票市场的波动吗?[J].数理统计与管理,2013, 32(2):332-342.Wang P. Can volume be helpful to predict Shanghai stock market volatility?[J]. Application of Statistics and Management, 2013, 32(2):332-342.
[16]邓燊,杨朝军.汇率制度改革后中国股市与汇市关系——人民币名义汇率与上证综合指数的实证研究[J].金融研究,2008(1):29-41.Deng S, Yang C J. The relationship between China's stock market and foreign exchange market after the reform of exchange rate system—An empirical study of RMB nominal exchange rate and Shanghai Composite Index[J].Journal of Financial Research, 2008(1):29-41.
[17]Moore T, Wang P. Dynamic linkage between real exchange rates and stock prices:Evidence from developed and emerging Asian markets[J]. International Review of Economics Finance, 2014, 29:1-11.
[18]陈云.人民币汇率与中美股市之间的信息溢出效应——基于内生结构突变的实证研究[J].经济评论,2013(2):112-120.Chen Y. Information spillover effects between RMB exchange rate and Sino-US stock markets:An empirical study based on endogenous structural break[J]. Economic Review, 2013(2):112-120.
[19]舒家先,谢远涛.人民币汇率与股市收益的动态关联性实证研究[J].技术经济,2008, 27(2):116-119.Shu J X, Xie Y T. Dynamic relationship between RMB exchange rate and stock return[J]. Technology Economics,2008, 27(2):116-119.
[20]陈虹,徐融.中国股市量价关系研究[J].经济问题,2017(3):30-34.Chen H, Xu R. The analysis on the price-amount relationship of Chinese stock exchanges[J]. On Economic Problems, 2017(3):30-34.
[21]Domowitz I, Wang J. Auctions as algorithms:Computerized trade execution and price discovery[J]. Journal of Economic Dynamics and Control, 1994, 18(1):29-60.
[22]范言慧,席丹,郑建明,等.股票市场发展、实际汇率与中国制造业出口[J].国际金融研究,2015(12):65-74.Fan Y H, Xi D, Zheng J M, et al. Stock market development, real exchange rate and China's manufacturingexports[J]. Studies of International Finance, 2015(12):65-74.
[23]Abanto-Valle C A, Migon H S, Lopes H F. Bayesian modeling of financial returns:A relationship between volatility and trading volume[J]. Applied Stochastic Models in Business and Industry, 2010, 26(2):172-193.
[24]Abanto-Valle C A, Dey D K, Lachos V H. Stock return volatility, heavy tails, skewness and trading volume:A Bayesian approach[R]. Federal University of Rio de Janeiro, 2014.
[25]刘洋,陈守东.带有成交量的随机波动模型SMC算法[J].数量经济研究,2015,6(2):62-71.Liu Y, Chen S D. SMC algorithm on stochastic volatility models with volume[J]. The Journal of Quantitative Economics,2015,6(2):62-71.
[26]Pitt M K, Shephard N. Filtering via simulation:Auxiliary particle filters[J]. Journal of the American Statistical Association, 1999, 94(446):590-599.
[27]Liu J, West M. Combined parameter and state estimation in simulation-based filtering[M]//Sequential Monte Carlo Methods in Practice. New York:Springer New York, 2001:197-223.
[28]段琳琳,屠新曙.已实现波动率在我国金融市场的应用前景[J].统计与决策,2005(12X):18-20.Duan L L, Tu X S. The application prospect of realized volatility in China's financial market[J]. Statistics and Decision, 2005(12X):18-20.
[29]Glosten L R, Milgrom P R. Bid, ask and transaction prices in a specialist market with heterogeneously informed traders[J]. Journal of Financial Economics, 1985, 14(1):71-100.
[30]Milgrom P, Stokey N. Information, trade and common knowledge[J]. Journal of Economic Theory, 1982, 26(1):17-27.
[31]Ross S A. Information and volatility:The no-arbitrage martingale approach to timing and resolution irrelevancy[J]. The Journal of Finance, 1989, 44(1):1-17.
[32]Andersen T G. Return volatility and trading volume:An information flow interpretation of stochastic volatility[J].The Journal of Finance, 1996, 51(1):169-204.
[33]Feller W. An introduction to probability theory and its applications:Volume I[M]. London:John Wiley&Sons,1968.
[34]Mahieu R, Bauer R. A Bayesian analysis of stock return volatility and trading volume[J]. Applied Financial Economics, 1998, 8(6):671-687.
[35]廖料.由美元兑韩币成交量预判汇率和股市走势[N].上海证券报,2009-03-18(A03).Liao L. Anticipation of exchange rate and stock market trend from the volume of US dollar to Korean[N].Shanghai Securities News, 2009-03-18(A03).
[36]Carvalho C M,Lopes H F. Simulation-based sequential analysis of Markov switching stochastic volatility models[J]. Computational Statistics&Data Analysis, 2007, 51(9):4526-4542.
[37]陈守东,孙彦林,刘洋.货币政策对流动性去向的动态影响[J].财经科学,2015(10):1-13.Chen S D, Sun Y L, Liu Y. Dynamic effect analysis of liquidity flow direction from the monetary policy[J].Finance&Economics, 2015(10):1-13.
1.需要注意的是,常说的大盘成交量指代成交金额,因此被选作为本文的股市成交量数据.
2.信息权重的确定需要根据值域进行标准化处理,保证其值域落在[0,1].
3.vol表示汇市成交量信息权重为0的v_t.
4.图3(a)至(f)中三条线依次为各参数在75%(1)、50%(m)及25%(u)分位数下的后验估计.
5.将通过直接渠道确定的v_t所得到的m_0与m_1的后验估计结果(如图5)作为次坐标轴.
[2]Smirlock M, Starks L. An empirical analysis of the stock price-volume relationship[J]. Journal of Banking&Finance, 1988, 12(1):31-41.
[3]陈浪南,罗嘉雯,刘昊.基于TVP-VAR-GCK模型的量价时变关系研究[J].管理科学学报,2015, 18(9):72-85.Chen L N, Luo J W, Liu H. Time-varying price-volume relationship based on TVP-VAR-GCK model[J]. Journal of Management Sciences in China, 2015, 18(9):72-85.
[4]吴鑫育,李心丹.中国股市量价尾部相关性研究——基于随机copula模型的实证[J].金融理论与实践,2017(1):93-97.Wu X Y, Li X D. Tail correlation of volume and price in China's stock market—Empirical study based on stochastic copula model[J]. Financial Theory&Practice, 2017(1):93-97.
[5]刘俊山,张陶伟.成交量与股价波动ARCH效应的实证研究[J].财经科学,2004(3):14-17.Liu J S, Zhang T W. Empirical study on ARCH effect of volume and stock price fluctuation[J]. Finance and Economics, 2004(3):14-17.
[6]郑方镳,吴超鹏,吴世农.股票成交量与收益率序列相关性研究——来自中国股市的实证证据[J].金融研究,2007(3A):140-150.Zheng F B, Wu C P, Wu S N. Study on correlation between stock volume and yield series—Empirical evidence from China's stock market[J]. Journal of Financial Research, 2007(3A):140-150.
[7]唐齐鸣,刘亚清.市场分割下A、B股成交量、收益率与波动率之间关系的SVAR分析[J].金融研究,2008(2):113-126.Tang Q M, Liu Y Q. SVAR analysis of the relationship between A, B stock volume, yield and volatility under market segmentation[J]. Journal of Financial Research, 2008(2):113-126.
[8]张永东,黎荣舟.上海股市日内波动性与成交量之间引导关系的实证分析[J].系统工程理论与实践,2003, 23(2):19-23.Zhang Y D, Li R Z. Testing for causality in the intraday volatility-volume relation:Shanghai stock market's evidence[J]. Systems Engineering—Theory&Practice, 2003, 23(2):19-23.
[9]罗登跃,王春峰.上证指数收益率、波动性与成交量动态关系研究——基于日数据的非线性动力学实证分析[J].系统工程理论与实践,2005, 25(7):41-48.Luo D Y, Wang C F. Empirical analysis of the relation between daily return rate, volatility and trading volume of Shanghai stock market comprising index based on nonlinar dynamics[J]. Systems Engineering—Theory&Practice, 2005, 25(7):41-48.
[10]Hiemstra C, Jones J D. Testing for linear and nonlinear Granger causality in the stock price-volume relation[J].The Journal of Finance, 1994, 49(5):1639-1664.
[11]Zhang W, Bi Z, Shen D. Investor structure and the price-volume relationship in a continuous double auction market:An agent-based modeling perspective[J]. Physica A:Statistical Mechanics and its Applications, 2017,467:345-355.
[12]张庆翠,王春峰.中国股价波动性与成交量共同的长期记忆性研究[J].管理科学学报,2005, 8(2):38-45.Zhang Q C, Wang C F. Research on common long memory between trading volume and volatility in Chinese stock market[J]. Journal of Management Sciences in China, 2005,8(2):38-45.
[13]Chen S H, Liao C C. Agent-based computational modeling of the stock price-volume relation[J]. Information Sciences, 2005, 170(1):75-100.
[14]唐勇.基于高频数据的波动率与成交量动态关系研究[J].成都理工大学学报(社会科学版),2011,19(3):8-16.Tang Y. Research on dynamic relationship between volatility and trading volume based on high-frequency data[J].Journal of Chengdu University of Technology(Social Sciences), 2011, 19(3):8-16.
[15]王鹏.成交量信息有助于预测中国股票市场的波动吗?[J].数理统计与管理,2013, 32(2):332-342.Wang P. Can volume be helpful to predict Shanghai stock market volatility?[J]. Application of Statistics and Management, 2013, 32(2):332-342.
[16]邓燊,杨朝军.汇率制度改革后中国股市与汇市关系——人民币名义汇率与上证综合指数的实证研究[J].金融研究,2008(1):29-41.Deng S, Yang C J. The relationship between China's stock market and foreign exchange market after the reform of exchange rate system—An empirical study of RMB nominal exchange rate and Shanghai Composite Index[J].Journal of Financial Research, 2008(1):29-41.
[17]Moore T, Wang P. Dynamic linkage between real exchange rates and stock prices:Evidence from developed and emerging Asian markets[J]. International Review of Economics Finance, 2014, 29:1-11.
[18]陈云.人民币汇率与中美股市之间的信息溢出效应——基于内生结构突变的实证研究[J].经济评论,2013(2):112-120.Chen Y. Information spillover effects between RMB exchange rate and Sino-US stock markets:An empirical study based on endogenous structural break[J]. Economic Review, 2013(2):112-120.
[19]舒家先,谢远涛.人民币汇率与股市收益的动态关联性实证研究[J].技术经济,2008, 27(2):116-119.Shu J X, Xie Y T. Dynamic relationship between RMB exchange rate and stock return[J]. Technology Economics,2008, 27(2):116-119.
[20]陈虹,徐融.中国股市量价关系研究[J].经济问题,2017(3):30-34.Chen H, Xu R. The analysis on the price-amount relationship of Chinese stock exchanges[J]. On Economic Problems, 2017(3):30-34.
[21]Domowitz I, Wang J. Auctions as algorithms:Computerized trade execution and price discovery[J]. Journal of Economic Dynamics and Control, 1994, 18(1):29-60.
[22]范言慧,席丹,郑建明,等.股票市场发展、实际汇率与中国制造业出口[J].国际金融研究,2015(12):65-74.Fan Y H, Xi D, Zheng J M, et al. Stock market development, real exchange rate and China's manufacturingexports[J]. Studies of International Finance, 2015(12):65-74.
[23]Abanto-Valle C A, Migon H S, Lopes H F. Bayesian modeling of financial returns:A relationship between volatility and trading volume[J]. Applied Stochastic Models in Business and Industry, 2010, 26(2):172-193.
[24]Abanto-Valle C A, Dey D K, Lachos V H. Stock return volatility, heavy tails, skewness and trading volume:A Bayesian approach[R]. Federal University of Rio de Janeiro, 2014.
[25]刘洋,陈守东.带有成交量的随机波动模型SMC算法[J].数量经济研究,2015,6(2):62-71.Liu Y, Chen S D. SMC algorithm on stochastic volatility models with volume[J]. The Journal of Quantitative Economics,2015,6(2):62-71.
[26]Pitt M K, Shephard N. Filtering via simulation:Auxiliary particle filters[J]. Journal of the American Statistical Association, 1999, 94(446):590-599.
[27]Liu J, West M. Combined parameter and state estimation in simulation-based filtering[M]//Sequential Monte Carlo Methods in Practice. New York:Springer New York, 2001:197-223.
[28]段琳琳,屠新曙.已实现波动率在我国金融市场的应用前景[J].统计与决策,2005(12X):18-20.Duan L L, Tu X S. The application prospect of realized volatility in China's financial market[J]. Statistics and Decision, 2005(12X):18-20.
[29]Glosten L R, Milgrom P R. Bid, ask and transaction prices in a specialist market with heterogeneously informed traders[J]. Journal of Financial Economics, 1985, 14(1):71-100.
[30]Milgrom P, Stokey N. Information, trade and common knowledge[J]. Journal of Economic Theory, 1982, 26(1):17-27.
[31]Ross S A. Information and volatility:The no-arbitrage martingale approach to timing and resolution irrelevancy[J]. The Journal of Finance, 1989, 44(1):1-17.
[32]Andersen T G. Return volatility and trading volume:An information flow interpretation of stochastic volatility[J].The Journal of Finance, 1996, 51(1):169-204.
[33]Feller W. An introduction to probability theory and its applications:Volume I[M]. London:John Wiley&Sons,1968.
[34]Mahieu R, Bauer R. A Bayesian analysis of stock return volatility and trading volume[J]. Applied Financial Economics, 1998, 8(6):671-687.
[35]廖料.由美元兑韩币成交量预判汇率和股市走势[N].上海证券报,2009-03-18(A03).Liao L. Anticipation of exchange rate and stock market trend from the volume of US dollar to Korean[N].Shanghai Securities News, 2009-03-18(A03).
[36]Carvalho C M,Lopes H F. Simulation-based sequential analysis of Markov switching stochastic volatility models[J]. Computational Statistics&Data Analysis, 2007, 51(9):4526-4542.
[37]陈守东,孙彦林,刘洋.货币政策对流动性去向的动态影响[J].财经科学,2015(10):1-13.Chen S D, Sun Y L, Liu Y. Dynamic effect analysis of liquidity flow direction from the monetary policy[J].Finance&Economics, 2015(10):1-13.
1.需要注意的是,常说的大盘成交量指代成交金额,因此被选作为本文的股市成交量数据.
2.信息权重的确定需要根据值域进行标准化处理,保证其值域落在[0,1].
3.vol表示汇市成交量信息权重为0的v_t.
4.图3(a)至(f)中三条线依次为各参数在75%(1)、50%(m)及25%(u)分位数下的后验估计.
5.将通过直接渠道确定的v_t所得到的m_0与m_1的后验估计结果(如图5)作为次坐标轴.
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