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Analysis of Longmemory and Nonsymmetry of Timeseries Data of Chinese Stock Market
Author: ZhangXingWang
Tutor: JiaZuo
School: Southwestern University of Finance and Economics
Course: Quantitative Economics
Keywords: Longmemory Nonsymmetry Hurst R/S FISTAR Shanghai Composite Index Shenzhen Composite Index
CLC: F224
Type: Master's thesis
Year: 2008
Downloads: 69
Quote: 0
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Abstract
The analysis of timeseries econometrics has a great progress in the past two decades,The traditional analysis of timeseries bases on the stationarity and the classic econometric hypothesis.As the devolopment of analysis of econometric timeseries,the tradional analysis of stationary timeseries gives way to nonstationary timeseries.There are lots of nonstationary timeseires in the field of economics and finance,such as aggregate marcoeconomics,and the volatility of financial markets.The analysis of nonstationary timeseries includes unit root timeseries and nonlinearity and so on.Longmemory process extends the unit root process.Nonsymmetry exist in stock market and other financial markets widely.There are six chapters in all,the general content of every chapter are:Chapter 1the part of introductionIt introduces the background and significance of the subject which the writer choose,and introduces the method and tools which have been used.The writer found out that the analysis of longmemory and nonsymmetry of timeseries of stock market before, mostly commence in two separate ways.Meanwhile,the writer red a paper about the study the monthly datas of American unemployment,inspired by this,the writer wants to model the longmemory and nonsymmetry of the stock markets’time series datas together by one model.Chapter 2the part of introduction of the papers about longmemory and nonsymmetry of stock markets.In this chaper,firstly introduce the papers about longmemory in and abroad,the second part,introduces the paers about nonsymmetry.Chapter 3Longmemory in stock timeseriesIn this chaper and the next one,the writer has a complete academic analysis about longmemory and nonsymmetry.Chapter 3 has a detailed introduciton about the definition,verifying,measurement of longmemory and modeling.It gives the definition in two ways:the definition in the way of autocorrelate function and the definition in the way of spectrum density. But in this paper, it defines the longmemory by the way of autocorrelation function. In this chapter, the writer simulates the timeseries which have different characters about memory using the Excel and Eviews. The writer also gives a detailed introduction of rescaledrange, which used to measurement of longmemory of timeseries. The writer also points out that the shortage of the standard rescaledrange,and introduce another concept:Adjusted Recaledrange.In this chapter,the writer introduces the concept of Fractional Integration,which used to model the longmemory of timeseries.Chapter 4Nonsymmetry of stock timeseriesIn this chapter, the writer introduces the nonsymmetry of the stock timeseries. Firstly, it gives a brief introduction of the models of TAR, and the general form STAR. The next part, the writer had a detailed introduction of the volatility of stock market and the GARCH model to capture the character of nonsymmetry of stock market. Meanwhile, give the reasons of the exist of nonsymmetry: leverage effect and volatility feedback effect.Chapter 5the nestal model of longmemory and nonsymmery of stock timeseries datasIn this chapter,the writer intriduces two kinds of nestal models.One is Fractional Integration Smooth Transition Autoregression,which can capture the characters of longmemory and nonlinearity of shortmemroy mechanism.The other one is Fractional Integration GARCH model,it extend the GARCH model to the form of longmemory,to capture the longmemory of the volatility of stock market. Chapter 6the positive analysis of the P.R.C.’s stock timeseriesThis is the part of positive ananlysis,the writer has a positive analysis of the day return of the index of Shanghai stock and the index of Shenzhen stock.The writer computes the index of Hurst of the index of Shanghai and Shenzhen.and find out that,except the day return of index of Shenzhen,the other series have a Hurst more than 0.5.Particularly,the volatility series of two markets,both have bigger Hursts,it means the volatility of two stock markets both have longmemory.In the second part,the writer models the nonsymmetry GARCH,and gives the reason of the exist of nonsymmetry of stock market. As a whole,the particular part of the paper are:firstly,Stochastically simulating the timeseries which have different characters of memory.Secondly,computing the index of Husrt of the related series of Shanghai and Shenzhen Stock markets by Excel and Eviews;Thirdly,the writer analysis longmemory and nonsymmetry together,other than the other scholars,and established a nestal model to capture these two characters of nonstationary series.

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