Testing Weak-Form Efficiency and Long-Term Causality of the Emerging Capital Markets in Romania, India, Poland, and Hungary

Testing Weak-Form Efficiency and Long-Term Causality of the Emerging Capital Markets in Romania, India, Poland, and Hungary

DOI: 10.4018/978-1-5225-9269-3.ch008

Abstract

The main purpose of this chapter is testing weak-form efficiency and long-term causality of the emerging capital markets in Romania, India, Poland and Hungary. According to Spulbar and Birau, the empirical analysis is focused on BET index (Romania), WIG 20 index (Poland), BSE index (India) and BUX index (Hungary) from January 2000 to July 2018. The empirical results revealed that there is no long-term causality between the selected emerging stock markets analyzed during the period of January 2000 to July 2018. The book chapter provides additional empirical evidence of emerging capital markets behavior since the empirical analysis revealed that ADF t statistics rejected the null hypotheses of a unit root, so the selected financial data series are stationary in all selected cases. Moreover, the empirical results have revealed that the efficient market hypothesis has not been validated and there is no long-term causality between the selected emerging stock markets during the sample period from January 2000 to July 2018.
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Introduction

In terms of justifying the selection of the international portfolio, we will highlight in the paragraphs below both the similarities and the differences between the markets in Romania, Poland, Hungary and India. Romania, Poland and Hungary are member states of the European Union but reveals different levels of socio-economic development. Moreover, Romania, Poland and Hungary, are all former communist countries in Central and Eastern Europe. Hungary and Romania are neighbors and share a common past in certain key aspects. Nevertheless, Hungary and Poland joined the European Union (EU) in 2004 and Romania became a member in 2007. Moreover, all three countries are full members of NATO. All the three selected European countries are democratic.

According to FTSE Country Classifications, data provided on March 2018, there is the following classification of countries: developed, advanced emerging, secondary emerging and frontier. Hungary is included in the category of advanced emerging markets, while Romania is included in the category of frontier markets, but on the Watch List for a possible reclassification from frontier to secondary emerging. On the other hand, Poland is also included in the category of advanced emerging markets, but it will be promoted to developed market status, effective from September 2018.

India is included in the category of secondary emerging and also member of the BRICS group which includes Brazil, Russia, India, China and South Africa. As can be easily noticed, India is perceived as an alternative in case of a Black Swan1 event based on international portfolio diversification. The Indian stock market is seemingly uncorrelated with the capital markets in Europe and this aspect can lead to significant long-term diversification benefits. Stock market interdependencies are very important in the context of a diversified international portfolio.

This book subchapter provides a comprehensive investigation of the efficient market hypothesis in terms of emerging capital markets as an extension of previous research studies of the authors. One of the essential assumptions of classical finances implies that investors are rational, and they are concerned to select an efficient portfolio a combination of asset classes chosen as to achieve the greatest possible returns over the long term, but under the conditions of a tolerable level of risk. The efficient market hypothesis is based on the “random walk” theory.

This approach leads to the quintessence of efficient market theory, which is based on the idea that an efficient market “fully reflect” available information. The efficient market hypothesis focuses on three main pillars, i.e.: investor rationality, uncorrelated errors, and the idea that there are no limits to arbitrage. Technically, arbitrage is defined as “the simultaneous purchase and sale of the same, or essentially similar, security in two different markets for advantageously different prices” (Sharpe & Alexander, 1990). A market is efficient with respect to a set of information if it is impossible to obtain economic profits by trading on the basis of this information set (Ross, 1987).

Fama (1965) stated that: “an efficient market is defined as a market where there are large numbers of rational, profit-maximizers actively competing, with each trying to predict future market values of individual securities, and where important current information is almost freely available to all participants.” On the other hand, Peters (1994) suggested that: “If all information had the same impact on all investors, there would be no liquidity. When they received information, all investors would be executing the same trade, trying to get the same price.”

Korajczyk (1995) suggested that “the measure of market segmentation tends to be much larger for emerging markets than for developed markets, which is consistent with larger barriers to capital flows into or out of the emerging markets”. However, emerging capital markets are characterized by a number of inefficiencies such as: mispricings (Korajczyk, 1995), financial frictions, misallocation of financial resources (capital), irrational investment decision making, the impact of informational asymmetry and return anomalies.

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