Evolving Efficiency and Noise Trading of China's Copper Futures Market

Abstract

Abstract:

Investigating the impact of noise trading on efficiency from the perspective of behavioral finance has become a hot topic in the field of micro finance. This paper studies the evolving efficiency of Shanghai copper futures market and the impact of noise trading on it. We firstly measure the noise trading using EGARCH model, secondly build a state space model to measure the evolving efficiency using Kalman filtering, and finally investigate the impact of noise trading on the efficiency using GARCH model from both first and second moment. Through the empirical study, we find that:the market tends to be weakly efficient, with a distinctive stage characteristic. Specifically, before early June 2013 its market effectiveness is poor and then it gradually improves after beneficial policy was introduced. In the long run, the noise trading weakly enhances the efficiency due to promoting market depth, while in short term, it magnifies the volatility of the evolving efficiency, because it will amplify variance of yield. The results indicates that noise trading isn't the primary cause of copper futures market's inefficiency, but trading system and market environment are likely to be the key factors.

Key words: Shanghai copper futures market, noise trading, evolving efficiency, first and second moment, market depth

Ji Junwei, Fu Qiang, Zhang Xingmin. Evolving Efficiency and Noise Trading of China's Copper Futures Market[J]. , 2019, 31(2): 17-35.

References

[1] Alwathainani A. M. Consistent Winners and Losers[J]. International Review of Economics and Finance, 2012,21(1):210-220.
[2] Corredor P., Ferrer E., Santamaria R. Investor Sentiment Effect in Stock Markets:Stock Characteristics or Country-Specific Factors?[J]. International Review of Economics and Finance, 2013,27(6):572-591.
[3] Black F. Noise[J]. Journal of Finance, 1986,41(3):529-543.
[4] 易蓉,周学军,张松,等. 沪铜期货基差之非线性动态调整特性研究[J]. 管理评论, 2008,20(10):3-7.
[5] 刘向丽,成思危,汪寿阳,等. 参数法、半参数法和非参数法计算我国铜期货市场VaR之比较[J]. 管理评论, 2008,20(6):3-8.
[6] 林宇,魏宇,高勇,等.上海伦敦铜期货市场风险的测度与传导效应研究[J].管理评论, 2008,20(11):3-9.
[7] 韩立岩,郑葵方. 铜期货市场信息的国际传递[J]. 管理评论, 2008,20(1):9-16.
[8] 吴晓霖,蒋祥林,阳桦. 上海、伦敦铜期货市场价格互动关系演变研究[J]. 统计与决策, 2009,(21):125-128.
[9] 彭红枫,陈奕. 中国铜期货市场最优套期保值比率估计——基于马尔科夫区制转移GARCH模型[J]. 中国管理科学, 2015,23(5):14-22.
[10] 陈冲,刘向丽,徐山鹰,等. 基于基差角度的中国铜期货动态套保策略研究[J]. 管理科学学报, 2012,15(6):49-58.
[11] Fama E. Efficient Capital Markets:A Review of Theory and Empirical Work[J]. Journal of Finance, 1970,25(2):383-417.
[12] Hall E., Zalewska-Mitura A. Evolving Market Efficiency with An Application to Some Bulgarian Shares[J]. Economics of Planning, 1997,30 (2-3):75-79.
[13] Zalewska-Mitura A., Hall S. G. Examining the First Stages of Market Performance:A Test for Evolving Market Efficiency[J]. Economics Letters, 1999,64(1):1-12.
[14] Lim K. P., Brooks D. Price Limits and Stock Market Efficiency:Evidence from Rolling Bicorrelation Test Statistic[J]. Chaos, Solitons & Fractals, 2009,40(3):1271-1276.
[15] Zhang B., Li X. M., He F. Testing the Evolution of Crude Oil Market Efficiency:Data Have the Conn[J]. Energy Policy, 2014,68(5):39-52.
[16] Vaalmikki A. Microstructures, Financial Reforms and Informational Efficiency in an Emerging Market[J]. Research in International Business and Finance, 2016,36(1):112-126.
[17] Scrugges J. T. Noise Trader Risk:Evidence from the Siamese Twins[J]. Journal of Financial Markets, 2007,10(1):76-105.
[18] Shiller R. J. Do Stock Prices Move Too Much to Be Justified by Subsequent in Dividends[J]. American Economic Review, 1981,71(3):421-436.
[19] De Long J. B., Shleifer A., Summers L. H., et al. Noise Trader Risk in Financial Markets[J]. Journal of Political Economy, 1990,98(4):703-738.
[20] 刘毅,李景华. 噪声交易者在金融市场的长期存在性研究[J]. 管理评论, 2012,24(7):34-39.
[21] Kyle A. S. Continuous Auctions and Insider Trading[J]. Econometrica, 1985,53(6):1315-1335.
[22] Admati R. A., Pfleiderer P. A Theory of Intraday Patterns:Volume and Price Variability[J]. Review of Financial Studies, 1988,1(4):3-40.
[23] Shleifer A., Vishny R. The Limits of Arbitrage[J]. Journal of Finance, 1997,52(1):35-55.
[24] Albert W. F. Unformed Arbitrage with Speculative Noise Trading[J]. Journal of Banking & Finance, 2010,34(2):304-313.
[25] Gao P., Liang P. J. Informational Feedback, Adverse Selection, and Optimal Disclosure Policy[J]. Journal of Account Research, 2013,51(5):1133-1158.
[26] Han B., Tang Y., Yang L. Public Information and Uninformed Trading:Implications for Market Liquidity and Price Efficiency[J]. Journal of Economic Theory, 2016,163(5):604-643.
[27] Madhavan A. Trading Mechanisms in Securities[J]. Journal of Finance, 1992,47(2):607-641.
[28] Handa P., Schwartz R.,Tiwari A. Quote Setting and Price Formation in An Order Driven Market[J]. Journal of Financial Markets, 2003,6(4):461-489.
[29] 陈很荣,吴冲锋. 基于噪声交易理论的对策博弈分析[J]. 预测, 2001,20(1):40-43.
[30] Barber B., Odean T. All That Glitters:The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors[J]. The Review of Financial Studies, 2008,21(2):785-818.
[31] Massimo P., Daniela V., Lucia B. Internet, Noise Trading and Commodity Futures Prices[J]. International Review of Economics & Finance, 2014,33:82-89.
[32] 汪宜霞,夏新平. 噪声交易者与IPO溢价[J]. 管理科学, 2007,20(3):91-95.
[33] 苏冬蔚. 噪声交易与市场质量[J]. 经济研究, 2008,(9):82-95.
[34] 唐勇,寇贵明. 股票市场微观结构噪声、跳跃、流动性关系分析[J]. 中国管理科学, 2012,20(2):11-19.
[35] 李学峰,王兆宇,李佳明. 噪声交易与市场渐进有效性[J]. 经济学(季刊), 2013,12(3):914-934.
[36] 许涤龙,吕忠伟. 深圳证券市场有效性的统计检验[J]. 数量经济技术经济研究, 2003,(6):158-161.
[37] 陈灯塔,洪永淼. 中国股市是弱式有效的吗——基于一种新方法的实证研究[J]. 经济学(季刊), 2003,(3):97-124.
[38] 张敏,陈敏,田萍. 再论中国股票市场的弱有效性[J]. 数理统计与管理, 2007,26(6):1091-1099.
[39] 何诚颖,程兴华. 基于中国证券市场的有效性研究——以高B-M类上市公司为例[J]. 管理世界, 2005,(11):145-151.
[40] 张林,李荣钧,刘小龙. 基于小波领袖多重分形分析法的股市有效性及风险检测[J]. 中国管理科学, 2014,22(6):17-26.
[41] 侯晓鸿,曾继民,李一智. 市场弱型有效检验方法研究——兼论我国商品期货市场效率[J]. 管理工程学报, 2000,14(1):69-70.
[42] 张小艳,张宗成. 期货市场有效性理论与实证检验[J]. 中国管理科学, 2005,13(6):1-5.
[43] 黄健柏,汤建. 中国金属期货市场的渐进有效性分析[J]. 求索, 2011,(8):45-46.
[44] 陈刚,唐衍伟. 期货市场价格波动与市场弱有效性的检验与分析[J]. 系统工程, 2004,22(11):40-45.
[45] 韩冰,田洪,唐莉. 我国期货市场有效性及风险的实证研究[J]. 统计与决策, 2005, (3):90-92.
[46] 王良,冯涛. 中国ETF基金交易量与价格之间的波动溢出效应[J]. 系统工程理论与实践, 2011,31(11):2043-2051.
[47] Chiu C. L., Lee M. C., Lin C. M., et al. Studies on the Effect of Trading Volume and Return Volatility on Call Warrant and Underlying Stocks in Taiwan[J]. Quarterly Journal of Business & Economics, 2005,44(1):29-44.
[48] 许香存,李平,曾勇. 中国股票市场开放式集合竞价对波动性影响的实证研究[J]. 金融研究, 2007,(7):151-164.
[49] 王志强,吴世农. 我国股票市场透明度变革效应研究[J]. 管理科学学报, 2008,11(5):110-119.
[50] 史金凤,刘维奇. 印花税调整政策对股票市场效率的影响分析[J]. 数理统计与管理, 2014,33(1):170-180.
[51] Chakravarty S., Gulen H., Mayhew S. Informed Trading in Stock and Option Markets[J]. Journal of Finance, 2004,59(3):1235-1257.
[52] Lei Q., Wu G. J. Time-Varying Informed and Uninformed Trading Activities[J]. Journal of Financial Market, 2005,8(2):153-181.
[53] Lee W. Y., Jiang C. X., Indro D. C. Stock Market Volatility, Excess Returns, and the Role of Investor Sentiment[J]. Journal of Banking and Finance, 2002,26(12):2277-2299.
[54] Antweiler W., Frank M. Z. Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards[J]. Journal of Finance, 2004,59(3):1259-1294.
[55] 赵秀娟,朱凯誉,汪寿阳. 封闭式基金价格指数波动溢出效应研究——以深市基金指数为例[J]. 中国管理科学, 2011,19(6):1-9.
[56] 徐剑刚,唐国兴. 期货波动与交易量和市场深度关系的实证研究[J]. 管理科学学报, 2006,9(2):69-75.
[57] Ramazan S., Shawkat H., Chang C. L., et al. Causality between Market Liquidity and Depth for Energy and Grains[J].Energy Economics, 2012,34(5):1683-1692.
[58] 郦金梁,雷曜,李树憬. 市场深度、流动性和波动率——沪深300股票指数期货启动对现货市场的影响[J]. 金融研究, 2012,(6):124-138