The Forecast Performance of Alternative Models of Inflation NATIONAL ECONOMICS UNIVERSITY INSTITUTE OF SOCIAL STUDIES HANOI THE HAGUE VIETNAM – NETHERLANDS CENTER FOR DEVELOPMENT ECONOMICS AND PUBLIC[.]
NATIONAL ECONOMICS UNIVERSITY STUDIES INSTITUTE OF SOCIAL HANOI THE HAGUE VIETNAM – NETHERLANDS CENTER FOR DEVELOPMENT ECONOMICS AND PUBLIC POLICY Non-linear model predictability of Vietnam stock market price A thesis presented by DINH VAN TUAN– MDE15 In partial fulfillment of the requirements for the obtaining the Degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS Supervisor Ph.D NGUYEN VIET HUNG HANOI - 2012 CERTIFICATION "I certify that the substance of this dissertation has not already been submitted for any degree and is not being currently submitted for any other degree I certify that to the best of my knowledge any help received in preparing this dissertation, and all sources used, have been acknowledged in this dissertation" Dinh Van Tuan November, 2011 LIST OF CONTENTS ACKNOWLEDGEMENTS ABBREVIATION LIST OF TABLES .5 LIST OF FIGURES CHAPTER 1: INTRODUCTION .7 1.1 Problem Statement 1.2 Reseach Objective .8 1.3 Research questions 1.4 Literature review .8 1.5 Thesis Methodology 11 1.6 Thesis Structure .11 CHAPTER 2: ANALYTICAL FRAMWORK 12 2.1 Concept and Definition 12 2.2 Models for predicting stock market price 13 CHAPTER 3: PERFORMANCE OF VIETNAM STOCK MARKET .19 3.1 Overview of Vietnam Stock Market .19 3.2 Performance of five Blue Chips in therecent time 27 CHAPTER 4: MODEL SPECIPICATION AND DATA ANALYSIS 32 4.1 Description of data 32 4.2 Estimated results 32 CHAPTER 5: CONCLUSIONS 46 REFERENCE .47 APPENDIX 50 ACKNOWLEDGEMENTS I would like to express my special thanks Ph.D Nguyen Viet Hung, at National Economic University in Hanoi for his valuable instructions, comments, criticism, and correction during the development of this thesis My deepest gratitude goes to the Vietnam - Netherlands Project for MA Program in Development Economics where I have learned and been able to write this thesis I would like to thank all lecturers and the staff in the Project for their long, kind encouragement and timely assistance And I wish to express my warmest thanks to my family and my friends for their encouragement and constructive suggestions throughout my course Without their spiritual and support, the thesis would have been made impossible Hanoi, November2011 Dinh Van Tuan ABBREVIATION HSX Hochiminh Stock Exchange HNX Hanoi Stock Exchange LSTR Logistic Smooth Transition Regression STR Smooth Transition Regression GBM Geometric Brownian Motion MR Mean Reversion Model AR Autoregressive Process ARIMA Autoregressive integrated moving average ADF Augmented Dickey-Fuller VAR Vector auto regression GSO General Statistics Office LIST OF TABLES Table 1: Capitalization level, proportion, and growth rate of the stock market 20 Table 2: The growth rate of the number of stock companies and asset management companies.22 Table 3: Business performance of Blue Chips 27 Table 4: Testing linear or non-linear of data series for suggesting model 33 Table 5: Augmented Dickey-Fuller (ADF) Unit Root Test results 37 Table 6: Estimation results of LSTR1 model .40 LIST OF FIGURES Figure 1: Size of listing on Vietnam’s Stock Trading Center 21 Figure 2: VN-Index in 2010 .24 Figure 3: Upcom-Index and tranding value in Upcom market 26 Figure 4: Performances of Blue chips on the stock market up to 31 October, 2011 .30 Figure 5: Defining initial values of γ and c by using the method of GRID SEARCH .35 Figure 7: ADF Test for residual of error terms with one lag .40 Figure 8: The graph of STR model 42 Figure 9: VN-Index, HN-Index, and five blue chips forecast 45 CHAPTER 1: INTRODUCTION 1.1 Problem Statement Vietnam’s stock market has operated for nearly ten years and played an important role on Vietnam’s economy Nowadays, most of financial organizations and investors have paid more their attentions to predict stock market, notably by analyzing random-walk behavior of stock time series, in order to take benefits from investing in the stock market However, there are lacking in qualitative studies in forecasting Vietnam’s stock market The main reason is that Vietnamese forecasters are lacking in professional knowledge and qualitative analysis skills Moreover, forecasting stock market has been becoming more difficulty due to the data of the economy, enterprises, and the market are not enough long time series and less confidence Nowadays, many scientists and researchers have paid more attention to develop an adaptive analysis method for non-linear time series A number of time series forecasting models have been developed and applied in analysing and forecasting the stock market and stock price moves such as Smoothing Exponential Regression, Threshold Regression, Artificial Neural Network, and Smooth Transition Regression (STAR), Logistic Smooth Transition Regression (LSTR), etc In fact, there are only some typical studies in analyzing Vietnam’s stock market such as Hoang Dinh Tuan (2008) and most of current studies used ARIMA model to forecast stock index in short-term Therefore, this study is going to predict stock index, particularly VN-index, HNIndex and some of stock index with large capitalization, by applying non-linear model (Logistic Smooth Transition Regression – LSTR) in order to provide useful information for investors and financial organizations The result of this study hopefully contributes an effective method in analyzing and forecasting the stock market and stock prices in Vietnam 1.2 Research Objectives The objective of this study is predicting the stock market and stock price moves, particularly VN-index and HN-Index and blue-chip stock price of stock with large capitalization, by applying non-linear model (Logistic Smooth Transition Regression – LSTR) in order to provide useful information for investors as well as financial organizations Suggesting recommendations and policy implications for developing Vietnam’s stock market in the near future is also an objective of this study 1.3 Research questions Question 1: Whether non-linear model will be used to predict VN-Index and HNIndex? Question 2: How does blue-chip stock price of HSX (Hochiminh Stock Exchange) and HNX (Hanoi Stock Exchange) look like by using non-linear model? 1.4 Literature review Analyzing and forecasting Vietnam’s stock market always attracts more concern of financial organizations and investors in the world, especially in term of stock market prices Bachelier (1900) shows that stock market prices were changed consecutively with an augmentation: S(t+Δ)-S(t)=ΔΔ)-S(t)=Δ)-S(t)=ΔΔ)-S(t)=Δ1/2 at time t In 1923, Alber Einstein given Brown W(t) moving process as studying kinematic elements and then the stock market price is a component of Brown W(t) According to L.Savege, stock market prices were never negative Brownian Motion Model was given in order to describe kinematics regarding to the market price of different kinds of stocks (P.Samuelson, 1965), for instance: S(t) =Δ exp(at+Δ)-S(t)=ΔbW(t)) As of the end of 1960s and the beginning of 1970s, Robert C Merton continued to develop financial theory based on Samuelson’s model Fischer Black and Myron Scholes (1973) declared their important study which is an application of Brownian Motion Model in generating stock valuation formulas suitable for options and other derivative securities Then, these formulas are known as Black-Scholes’s formula that is used by many investors and business to identify price evaluation options in various markets all over the world Studying works of Merton and Scholes were awarded the Nobel Prize in 1997 People often use Geometric Brownian Motion Model in financial mathematics to evaluate prices suitable for financial options Although, this model is relatively simple, it has still not reflected kinds of stock prices exactly Nowadays, analyzing and forecasting stock market prices in developed countries are often based on two major methods including (1) Trend Analysis and (2) Artificial Neuron Network However, these methods have not had high accurate level because of large standard error In empirical studies, there are some quantitative analyses for stock markets such as United State, United Kingdom, Canada, New Zealand, Ireland, and Japan stock markets est For example, Nektarios Aslanidis at all (2002) shows that a variety of financial and macroeconomic series, namely GDP, interest rates, inflation, money supply and US stock prices are assumed to influence UK stock returns In order to examine for a potential non- linear relationship between UK index returns and both financial and macroeconomic variables, David G McMillan (2002) used smooth-transition threshold models The result of his study states that investor behavior does differ between large and small return Using cross-sectional power gained from industry-sorted portfolios, Gropp (2004) addressed that there is a significantly positive speed of reversion with a half-life of approximately four years and a half to eight years to revert to long-term equilibrium Moreover, time series forecasting has received increasing attention in many studies in recent years Most of recent studies use the STAR model to analysis and forecast stock price indexes in the world Rodrigo Aranda and Patricio Jaramillo (2008) estimate Smooth