Forecasting Economic Growth with the Hungarian Composite Stock Market Index – a Granger Causality Test

Abstract

The relationship between the stock market and the economy, for developed markets, has been subjected to scrutiny, in the field of economic forecasting, since the late 90s.This research revisits the concept, the methodology and the findings of previous works and presents a new updated algorithm of testing the relationship between the economy and the stock market of a developing economy.Following a rigorous examination of the stock markets' strengths and shortfalls in predicting the economy, supported by the efficient market hypothesis, this paper presents the methodology for evaluating the BUX Hungarian composite stock market indicator as a leading indicator of economic growth.The quarterly data from the BUX is traced back to the second quarter of 1995 effectively providing 86 observations spanning across 26 years.Through the application of the ADF and the KPSS tests it is further determined in the work that the data is indeed mean reverting and independent of the time domain, and therefore, stationary.The coefficients of the autoregressive distributed lag model are further determined in the work through running an OLS regression test.It is determined that changes in the Hungarian GDP directly affect the immediate changes in the BUX composite stock index in a predictable way.The results of the Granger causality test, further strengthen the argument of the BUX being an important leading indicator, of the Hungarian economy.

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