Reviewing the history is aimed to predict the future. History contains the thread and the inherent law of the development of a thing. Can investors make investment decisions and predict the future trend through the analysis of stock market history? In this paper, taking Shanghai Composite Index, Shenzhen Compositional Index, Nikkei 225 and S&P 500 index as the samples, the dynamic estimation method is used to analysis the time-varying characteristics of long memory in the stock market, and the value of historical information is explored;and using the modified R/S method and LW estimates, two more novelty correction LW estimation method are employed for comparison, and the research of stock market long memory characteristics is expected to promoted. The empirical results show that, although the specific values are not exactly the same from different methods, but the same conclusions about the stock market long memory can be obtained;the stock return series did not have significantly long memory in the whole sample interval, but with extreme events, such as the 1990's real estate crisis in the Japanese, the Asian financial crisis in 1997, the U.S. financial crisis in 2008 and so on, return series exhibit a significant correlation, which inflect the time-varying characteristics of stock market long memory, and the extreme risk can be avoided by analysis historical information. Without regarding to the differences of cultural, economic and social background, this paper researches the China, Asia and globally representative stock index, and discusses the long memory characteristics of return series. An empirical evidence is provided for comprehensive understanding of the effective market hypothesis theory, and a support for risk management use the market's history information is also provided.
[1] Bachelier L. Théorie de la speculation [J]. Annales Sci-entifiques de I' cole Normale Supérieure, 1900, 3(17): 21-86.
[2] Roberts H. Stock market “patterns” and financial analysis: Methodological suggestions[J]. The Journal of Finance, 1959, 14(1): 1-10.
[3] Osborne M F M. Brownian motion in the stock market [J]. Operations Research March/April, 1959, 7(2):145-173.
[4] Granger C, Morgenstern O. Spectral analysis of New York stock exchange prices [J]. Kyklos, 1963, 16(1): 1-27.
[5] Fama E F. The behavior of stock market prices [J]. Journal of Business, 1965a, 38(1):34-105.
[6] Fama E F. Random walks in stock market prices [J]. Financial Analysts Journal, 1965b, 21(5): 55-59.
[7] Samuelson P A. Proof that properly anticipated prices fluctuate randomly [J]. Industrial Management Review, 1965, 6 (2):41-49.
[8] LeRoy S F. Risk aversion and the martingale property of stock prices [J]. International Economic Review, 1973, 14(2):436-446.
[9] Lucas Jr R E.Asset prices in an exchange economy [J]. Econometrica, 1978, 46(6):1429-1445.
[10] Fama E F. Efficient capital markets: A review of theory and empirical work [J]. The Journal of Finance, 1970, 25(2): 383-417.
[11] Solnik B. Note on the validity of the random walk for european stock prices [J]. Journal of Finance, 1973, 28(5): 1151-1159.
[12] Cagan P. The monetary dynamics of hyper inflation [M]//Friedman M. Studies in the quantity theory of money. Chicago: University of Chicago Press, 1957.
[13] Kahneman D, Tversky A. Prospect theory: An analysis of decisions under risk [J]. Econometrics, 1979, 47(2):197-291.
[14] Kahneman D, Tversky A. Choices, values, and frames [J]. The American Psychologist Association, 1984, 39(4):341-350.
[15] Fama E F, French K R. Permanent and temporary components of stock prices [J]. Joumal of Political economy, 1988, 96(2):246-273.
[16] Poterba J, Summers L. Mean reversion in stock prices [J]. Journal of Financial Economics, 1988, 22(1):27-59.
[17] Lo A W, Mackinlay A C. Stock market price do not follow random walks: Evidence from a simple specification test [J]. Review of Financial Studies, 1988,1(1):44-46.
[18] Jegadeesh N, Titman S. Returns to buying winners and selling loser: Implications for stock market efficiency [J]. Journal of Finance, 1993, 48(1):65-91.
[19] Shiller R. Irrational exuberance [M]. Princeton: Princeton University Press, 2000.
[20] Campbell J Y, Thompson S B. Predicting the equity premium out of sample: Can anything beat the historical average? [J]. Review of Financial Studies, 2008, 21 (4):1509-1531.
[21] 吴世农.我国证券市场效率的分析[J]. 经济研究,1996,4(16):13-20.
[22] 罗登跃,王玉华.上海股市收益率和波动性长记忆特征实证研究[J]. 金融研究,2005,(11):109-116.
[23] 李国俊,李霞.中外股市不同阶段市场有效性的对比分析[J]. 中南财经政法大学研究生学报,2010,(1):54-59.
[24] 张兵,李晓明. 中国股票市场的渐进有效性研究[J]. 经济研究, 2003,(1): 54-61.
[25] 王少平,杨继生.联合p值综列单位根检验的扩展及其对中国股市的弱有效性检验[J]. 统计研究,2006,23(4):69-72.
[26] 朱孔来,李静静.中国股票市场有效性的复合评价[J]. 数理统计与管理,2013,32(1):145-154.
[27] 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):913-934.
[28] 俞乔.市场有效、周期异常与股价波动—对上海、深圳股票市场的实证分析[J]. 经济研究,1994,(9):43-50.
[29] 叶中行,曹奕剑.Hurst指数在股票市场有效性分析中的应用[J]. 系统工程,2001, 19(3):21-24.
[30] 兰秋军,马超群,甘国君,等. 中国股市弱有效吗?———来自数据挖掘的实证研究[J]. 中国管理科学,2005,13(4):17-23.
[31] 林宇. 基于双曲线记忆HYGARCH模型的动态风险上海股市收益率和波动性长记忆特征实证研究VaR测度能力研究[J]. 中国管理科学,2011,19(6):15-24.
[32] 曹广喜,曹杰,徐龙炳.双长记忆GARCH族模型的预测能力比较研究[J]. 中国管理科学,2012,20(2):41-49.
[33] 杨科,田凤平.长记忆性结构突变条件下中国股市波动率的高频预测[J]. 管理工程学报,2013,27(2):129-136.
[34] Hurst H E. Long-term storage capacity of reservoirs [J]. Transactions of the American Society Civil Engineers, 1951,116:770-779.
[35] Lo A W. Long term memory in stock market prices [J]. Econometrica, 1991,59(5):1279-1313.
[36] Haubrich J G,Lo A W. The sources and nature of long term memory in aggregate output [J]. Economic Review of the Federal Reserve Bank of Cleveland, 2001,37(2):15-30.
[37] Andrews D W K. Heteroskedasticity and autocorrelation consistent covariance matrix estimation [J]. Econometrica, 1991,59(3):817-858.
[38] Robinson P M. Gaussian semiparametric estimation of long range dependence [J]. Annals of Statistics, 1995,23(5):1630-1661.
[39] Phillips P C B, Shimotsu K.Local Whittle estimation in nonstationary and unit root cases [J]. Annals of Statistics, 2004,32(2):656-692.
[40] Phillips P C B, Shimotsu K. Exact local Whittle estimation of fractional integration [J]. Annals of Statistics, 2005,33(4):1890-1933.
[41] Shimotsu K. Exact local Whittle estimation of fractional integration with unknown mean and time trend [J]. Econometric Theory, 2010,26(2):501-540.
[42] Cunado J, Gil-Alana L A, De Gracia F P. Persistence in some energy futures markets [J]. The Journal of Futures Markets, 2010,30(5): 490-507.