The Linkage of Chinese Stock Market to US and UK before and after the Subprime Mortgage Crisis Young-Jae Kim and Li Ying (Pusan National University)

Slides:

Advertisements

Similar presentations

Scott Nelson July 29, Outline of Presentation Introduction to Quantitative Finance Time Series Concepts Stationarity, Autocorrelation, Time Series.

Advertisements

ARCH (Auto-Regressive Conditional Heteroscedasticity)

Are Short Sellers Positive Feedback Traders? Discussion A.G. Malliaris, Quinlan School of Business Loyola University Chicago Multinational Finance Conference,

Analysis of the interrelationship between listed real estate share index and other stock market indexes The Swedish stock market S VANTE M ANDELL.

Modeling of Variance and Volatility Swaps for Financial Markets with Stochastic Volatility Anatoliy Swishchuk Department of Mathematics & Statistics, York.

1 Innovation, Change, Black Swans, and Financial Crises David Marshall* Senior Vice President Federal Reserve Bank of Chicago PhD Project Finance Doctoral.

ROBERT ENGLE DIRECTOR VOLATILITY INSTITUTE AT NYU STERN THE ECONOMICS AND ECONOMETRICS OF COMMODITY PRICES AUGUST 2012 IN RIO.

Persistence and nonlinearities in Economics and Finance “I built bustles for all Europe once, but I've been badly hit, Things have decayed in the bustle.

Indirect Real Estate Investments and their Links with Properties, Common Stocks and the Macroeconomy Alexander Schätz European Real Estate Society Conference.

Juan P. Cajigas Centre for Econometric Analysis

1 DEPARTMENTOFMATHEMATICSUPPSALAUNIVERSITY EMPIRICAL DATA AND MODELING OF FINANCIAL AND ECONOMIC PROCESSES by Maciej Klimek.

DYNAMIC CONDITIONAL CORRELATION : ECONOMETRIC RESULTS AND FINANCIAL APPLICATIONS Robert Engle New York University Prepared for CARLOS III, MAY 24, 2004.

GRA 6020 Multivariate Statistics The regression model OLS Regression Ulf H. Olsson Professor of Statistics.

© K. Cuthbertson and D. Nitzsche Figures for Chapter 5 BASIC STATISTICS (Investments : Spot and Derivatives Markets)

KYIV SCHOOL OF ECONOMICS Financial Econometrics (2nd part): Introduction to Financial Time Series May 2011 Instructor: Maksym Obrizan Lecture notes II.

PREDICTABILITY OF NON- LINEAR TRADING RULES IN THE US STOCK MARKET CHONG & LAM 2010.

Different chi-squares Ulf H. Olsson Professor of Statistics.

GRA 6020 Multivariate Statistics The regression model OLS Regression Ulf H. Olsson Professor of Statistics.

SOME STATISTICAL CONCEPTS Chapter 3 Distributions of Data Probability Distribution –Expected Rate of Return –Variance of Returns –Standard Deviation –Covariance.

Multivariate volatility models Nimesh Mistry Filipp Levin.

GRA 6020 Multivariate Statistics Factor Analysis Ulf H. Olsson Professor of Statistics.

Risk and Returns: part 1 Economics 71a: Spring 2007 Mayo chapter 8 Malkiel, Chap 9-10 Lecture notes 3.2a.

Financial Openness and the Chinese Growth Experience Geert Bekaert Columbia University and NBER Campbell R. Harvey Duke University and NBER Christian T.

Duan Wang Center for Polymer Studies, Boston University Advisor: H. Eugene Stanley.

1 CHAPTER 14 FORECASTING VOLATILITY II Figure 14.1 Autocorrelograms of the Squared Returns González-Rivera: Forecasting for Economics and Business, Copyright.

Volatility Spillovers and Asymmetry in Real Estate Stock Returns Kustrim Reka University of Geneva (Switzerland) Martin Hoesli University of Geneva (Switzerland),

1 Confidence Intervals for Means. 2 When the sample size n< 30 case1-1. the underlying distribution is normal with known variance case1-2. the underlying.

Normal and Sampling Distributions A normal distribution is uniquely determined by its mean, , and variance,  2 The random variable Z = (X-  /  is.

1 Who has more influence on Asian Stock Markets around the Subprime Mortgage Crisis － the U.S. or China? Chien-Chung Nieh* Chao-Hsiang Yang** Yu-Sheng.

Stress testing and Extreme Value Theory By A V Vedpuriswar September 12, 2009.

Impact of Rising Imports and Input Costs on U.S. Chile Industry Ram N. Acharya Department of Ag Econ and Ag Business New Mexico State University.

How volatile are East Asian stocks during high volatility periods? A workshop paper by Carlos C. Bautista College of Business Administration University.

Hong Kong’s Financial Market Interactions with the U.S. and Mainland China in Crisis and Tranquil Times Dong He, Zhiwei Zhang, and Honglin Wang The views.

1 Evidence of time-varying herding behavior from Pacific-Basin stock markets Thomas C. Chiang Marshall M. Austin Chair Professor of Finance LeBow College.

Measuring Sovereign Contagion in Europe Presented by Jingjing XIA Caporin, Pelizzon, Ravazzolo, and Rigobon (2013)

Volatility Spillovers and Financial Contagion in the CEE Stock Markets MSc. Student: ânaru Mihai Supervisor: Professor PhD. Moisă Altăr Academy of Economic.

Stock Volatility during the Recent Financial Crisis G. William Schwert European Financial Management Association Keynote Address June 25,2010 – Aarhus,

Implement Market innovation, Strengthen Enforcement and Promote Standardization Presented by vice chairman, Mr. Geng Liang China Securities Regulatory.

1 Hybrid versus Highbred -A New Approach to Combine Economic Models with Time-series Analyses Ming-Yuan Leon Li Quantitative Finance (SSCI journal), 10,

Literature Review ZHU Cai AMA. Contents Paper-Searching by Journals 2 Paper -Searching by Authors 3 Results of Elementary Analysis 4 Suggestions 5 Introduction.

Academy of Economic Studies DOCTORAL SCHOOL OF FINANCE AND BANKING Bucharest 2003 Long Memory in Volatility on the Romanian Stock Market Msc Student: Gabriel.

Ephraim CLARK, CONSTRUCTING AND TESTING THE “WORLD MARKET PORTFOLIO” FOR DOLLAR BASED INVESTORS Ephraim.

Financial Anomalies: Examination of Chinese B-share Markets from Roger Su Auckland University of Technology, New Zealand Ying Zhao Beihang.

1 The Impact of Low Income Home Owners on the Volatility of Housing Markets Peter Westerheide ZEW European Real Estate Society Conference 2009 Stockholm.

Comments on “Hong Kong’s Financial Market Interactions with the U.S. and Mainland China in Crisis and Tranquil Times” Discussed by Qing Liu SEM, Tsinghua.

Dissertation paper Modelling and Forecasting Volatility Index based on the stochastic volatility models MSc Student: LAVINIA-ROXANA DAVID Supervisor: Professor.

DETERMINANTS OF SPREADS OF ROMANIAN SOVEREIGN BONDS - an application on the EMBIG spreads – Student: BERBECARU CLAUDIA-FLORIANA Supervisor: Professor MOISĂ.

© K. Cuthbertson and D. Nitzsche Chapter 9 Measuring Asset Returns Investments.

GARCH Models Þættir í fjármálum Verkefni 1-f Bjartur Logi Ye Shen

1 Chapter 5 : Volatility Models Similar to linear regression analysis, many time series exhibit a non-constant variance (heteroscedasticity). In a regression.

Lecture 7 Introduction to Risk, Return, and the Opportunity Cost of Capital Managerial Finance FINA 6335 Ronald F. Singer.

Estimating Volatilities and Correlations

1 Stock Valuation Topic #3. 2 Context Financial Decision Making Debt Valuation Equity Valuation Derivatives Real Estate.

Advanced Investment Analysis Strategies January 11, 2016.

Weather effects on the returns and volatility of the Shanghai stock market 國際財管指導老師 : 何啟銘學生 : 林武義學號 :ma

Instructor: Chris Bemis Random Matrix in Finance Understanding and improving Optimal Portfolios Mantao Wang, Ruixin Yang, Yingjie Ma, Yuxiang Zhou, Wei.

Globalization and the Domestic Economy Nichole Benson Miranda Campbell-Magaña Charlie Gipson Murtaza Sharifi.

Econ616 – Spring 2006 The Spillover Effects of Deposit Rate between Japan and the United States: a Bivariate GARCH Model Yan Hu.

Lecture 8 Stephen G. Hall ARCH and GARCH. REFS A thorough introduction ‘ARCH Models’ Bollerslev T, Engle R F and Nelson D B Handbook of Econometrics vol.

Applications of Stochastic Processes in Asset Price Modeling Preetam D’Souza.

1 Returns in commodities futures markets and financial speculation: a multivariate GARCH approach Joint with Matteo Manera and Ilaria Vignati Università.

Expected Return and Risk. Explain how expected return and risk for securities are determined. Explain how expected return and risk for portfolios are.

B). Dependence between crude oil and other commodities © The Author(s) Published by Science and Education Publishing. Zayneb Attaf et al. Dependence.

Chapter Fifteen International Portfolio Investments Chapter Objectives: Why investors diversify their portfolios ( 证券组合 ) internationally. How much investors.

Table 1. Correlations between different indices

Vera Tabakova, East Carolina University

Market Risk VaR: Model-Building Approach

Forecasting the daily dynamic hedge ratios in agricultural futures markets: evidence from the GARCH models Yuanyuan Zhang, School of Management, University.

Carlo A. Favero IGIER, Universita’ Bocconi

Presentation transcript:

The Linkage of Chinese Stock Market to US and UK before and after the Subprime Mortgage Crisis Young-Jae Kim and Li Ying (Pusan National University)

Contents 1.Motivations and Backgrounds 2.Purposes 3.Differences 4.Empirical Analysis 5.Main Results 2/15

1. Motivations and Backgrounds The rapid rising of Chinese economy after the 2008 global financial crisis : So-called G2 The global effects of subprime mortgage crisis in 2007 Possible integration of Chinese stock market to the global market : US and UK 3/15

2. Purposes To investigate the expected correlation of market volatility among the three stock markets : US, UK and China To show the possible shift in the correlation of market volatility before and after the 2007 Subprime mortgage crisis: Strengthened correlations 4/15

3. Differences Very few papers that consider the Chinese stock market in relation to the US and UK markets Explicit incorporation of subprime mortgage crisis Advanced econometric model 5/15

4. Empirical Analysis Sample period : Jan. 2, 2002 to Jan Data : S&P 500 in US, FTSE in UK, Shanghai Composite Index in China from Datastream Structural Change : Sep. 2, 2008 Before crisis period : Jan. 2 – Sep. 2, 2008 After crisis period : Sep. 3, 2008 – Jan. 18, /15

Chow Test 7/15

Key Variables 8/15

The Model Multivariate GARCH-Diagonal VECH Model (by Engle and Kroner (1995))  Mean Equation  Variance Equation  Covariance Equation 9/15

Basic Statistics for Key Variables is a normally distributed Yt MeanStd,Dev.SkewnessKurtosisJB statisticP-value A. Before crisis DLUSA6.15e DLUK4.52e DLSH B. After crisis DLUSA DLUK-9.36e DLSH /15

Autocorrelation : Ljung-Box Q test is not serially correlated ⇔ : Test for Stock Returns Q(k) Q(4)Q(19)Q(36) A. Before crisis DLUSA13.507(0.009)42.476(0.002)66.023(0.002) DLUK48.153(0.000)85.623(0.000)134.99(0.000) DLSH10.357(0.035)27.929(0.085)53.226(0.032) B. After crisis DLUSA18.516(0.001)38.511(0.005)59.455(0.008) DLUK23.143(0.000)73.850(0.000)92.186(0.000) DLSH1.0784(0.898)15.579(0.685)37.864(0.384) 11/15

Conditional Correlation: Entire Period 15/15

Conditional Correlation: Before crisis 12/15

Conditional Correlation: After crisis 13/15

5. Main Results Correlations between China and US, between China and UK have increased after the crisis, which means the Chinese stock market becomes a part of the global market reflecting the rapidly rising Chinese economy. 14/15