MACROECONOMIC VARIABLES AND STOCK RETURNS IN CHINA

Macroeconomic Variables and Stock Returns in China

ABSTRACT

This paper aims to evaluate the predictive relationships of stock market returns and macroeconomic variables in China over the period January 1999 to June 2010. We consider and compare out-of-sample predictive ability of three different modelling approaches, namely a cointegrated vector autoregressive and error correction (VECM) model, a Nonlinear Auto Regressive Moving Average with eXogenous inputs (NARMAX) model with linear terms, and a NARMAX with nonlinear terms. The forecasting exercise shows that both NARMAX models outperform the VECM model and NARMAX with linear terms has the best out-of-sample predictive ability. Our results also suggest that the movements in stock market returns may mainly be explained by its own innovations. However, macroeconomic conditions still contain useful information for forecasting future stock returns and cannot be neglected in accounting for the dynamics of the returns.

Keywords: stock return predictability, macroeconomic variables, out-of-sample forecasts, VECM, NARMAX

Table of Contents

ABSTRACTII

CHAPTER 01: INTRODUCTIONIV

CHAPTER 02: LITERATURE REVIEWXII

2.1. Backgroundxv

2.7. Summaryxxi

CHAPTER 03: DATA AND DESCRIPTIVE STATISTICSXXIII

CHAPTER 04: METHODOLOGYXXVI

4.1 Vector-autoregressive and error correction (VECM) modelsxxvi

4.2 The NARAMX modelxxvii

CHAPTER 05: EMPIRICAL RESULTSXXXI

5.1 Modelling using VECM techniquesxxxi

5.2 Modelling using the NARMAX technique with linear termsxxxiv

5.3 Modelling using the NARMAX technique with nonlinear termsxxxv

5.4 Out-of-sample forecasting analysisxxxvii

5.5. Unit Root Testxxxviii

5.7. Granger-Causality Testxliv

5.8. Summaryxlvii

CHAPTER 06: CONCLUSIONSXLIX

REFERENCESLIII

APPENDIXLXV

Variableslxix

CHARTSLXXII

Macroeconomic Variables and Stock Returns in China

CHAPTER 01: INTRODUCTION

Over the past several decades, a large quantity of literature has focused on the question of whether macroeconomic variables contain information that is useful for forecasting stock market indices or returns, such as Fama and French (1989 10), Rapach et al (2005 25), Hartmann et al (2008 89), and Laopodis (2010 113). The basic assumption lying behind this stream of literature is that economic fundamental information publicly available in the past has some predictive relationships to the future stock market returns of indices. It is not surprising because macroeconomic variables are likely to exert important influences on firms¡¦ expected earnings or discount rates and are therefore likely to be related to stock market returns.

Extensive empirical studies have examined the predictability of stock market returns using macroeconomic variables, such as GNP/GDP or industrial production, monetary growth, interest rates, inflation, exchange rates, and so on. In regard to Chinese stock market returns, some other macroeconomic variables, such as hot money or speculative capital flow (Guo and Huang, 2010 87), have been investigated as well. Overall, the mixed results in the existing literature show that it is difficult to determine whether economic fundamentals or which particular macroeconomic variables (if any) are reliable indicators of stock market returns.

In this paper, we use China's experience to re-examine the predictability of stock market returns based on macroeconomic variables. Among developing countries, China is particularly suitable as a case study for analyzing the relationship between stock market returns and economic fundamentals. On the one hand, China's stock market is relatively new but has developed really rapidly since its establishment. Its two official stock exchanges, the Shanghai Exchange and the Shenzhen Exchange, were established in December 1990 and July ...