The Short-term Impact of Macroeconomic Changes on Stock Return: Study on Chinese Stock Market

Li, Hao (2015) The Short-term Impact of Macroeconomic Changes on Stock Return: Study on Chinese Stock Market. [Dissertation (University of Nottingham only)]

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This study investigates the short-term relationships between stock return and a set of macroeconomic variables: inflation rate, term-structure, the money supply growth gap between M1 and M2 (MSGG), exchange rate, and the Macroeconomic Coincident Climate Index (MCCI) as an indicator of current national macroeconomic condition. A range of Vector auto-regression (VAR) based tests are conducted to examine the short-term explanatory power of the selected macroeconomic variables on stock return. The Granger-Causality tests indicate there are two-way causal relationships between stock return and all the selected macroeconomic variables, only except for term-structure. Impulse response function and forecast error variance decompositions suggest MSGG, exchange rate, and MCCI are significant in explaining stock return. The empirical model estimated in this study perform well in forecasting short-term movement of stock return and MCCI. The findings in this study suggest an inconsistent result with the Efficient Market Hypothesis (EMH), that the stock return in Chinese market can be predicted by using the past value of the macroeconomic variables. However the findings give support to another financial theory that stock market is the barometer of national economy, it reflects business conditions and tends to predict the economy in advance. To stock market investors, the implication of this study is to pay attention to these macroeconomic variable when making short-term speculative strategies. To policy makers, policy changes especially in money supply and exchange rate may cause significant fluctuations in financial market in short-term.

Item Type: Dissertation (University of Nottingham only)
Keywords: Stock return forecast, Macroeconomic variables, Vector auto-regression, Time-series analysis
Depositing User: Li, Hao
Date Deposited: 23 Mar 2016 15:13
Last Modified: 19 Oct 2017 14:58

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