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This thesis includes three main topics in the field of spillovers using the multivariate EGARCH model. Put differently, this thesis is making use of a battery of econometrical models described in each chapter to capture return and volatility spillovers. The structure of the thesis is as follows
Chapter I represents the literature overview
Chapter II examines the dynamics of volatility spillover between stock and foreign exchange market: Empirical evidence from Central and Eastern European countries.
Chapter III addresses the question: Does volatility transmission between stock market returns of Central and Eastern European countries vary from normal to turbulent periods?
Chapter IV investigates volatility behavior of the foreign exchange rate and transmission among Central and Eastern European countries
Chapter I briefly reviews several articles that investigate the volatility spillovers among financial markets in the CEE countries.
Chapter II investigates the asymmetric volatility spillover effects between stock and foreign exchange markets using daily data. Obviously, the interlinkage between the two main financial markets had produced loads of papers for a long time. According to Wong (2017), the interrelatedness between stock prices and exchange rates may influence the execution of monetary policy and fiscal policy. Furthermore, a strong connectedness between them would have significant implications for economic policies and international capital budgeting decisions because negative innovations influencing one market may be quickly dispatched to another through contagious effects (Chkili and Nguyen, 2014). Kanas (2000) concludes that the huge increase in interdependency has also increased volatility spillovers between stock and foreign exchange markets. For example, Kanas (2000), Yang and Doong (2004), Aloui (2007), Valls and Chuliá (2014), Mozumder et al. (2015), Segal, Shaliastovich and Yaron (2015), Jebran and Iqbal (2016), Baruník, Kočenda and Vácha (2016) among others analysed the links between stock and foreign exchange returns.
Bivariate EGARCH model is employed to examine the volatility spillovers and co-movement between stock and foreign exchange markets of the five CEE countries. The entire investigation period is subdivided into two sub-periods:
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the pre-crisis period, from 1 April 2000 to 29 August 2008; and the post-crisis period, from 1 September 2008 to 29 September 2018. The results point to bidirectional volatility spillovers between the stock and foreign exchange markets of Hungary in all periods, and of Poland in the post-crisis period, unidirectional volatility spillovers in Croatia in the pre-crisis period, and from the stock market to the exchange market in the Czech Republic during two periods. In the post-crisis period, the two financial markets show the absence of volatility spillovers in Croatia.
Chapter III focuses on the integration of the CEE stock markets using daily data that also subdivided into pre and post the global financial crisis. The main reasons why to investigate the transmission mechanism of price and volatility spillovers across Budapest, Warsaw, Prague, Bucharest and Zagreb stock markets is threefold. First, the pivotal role of emerging markets which is becoming more interesting for investors and policymakers. Second, Central and Eastern European countries have attempted to increase cooperation and trade among themselves. Third, we modeled the possible returns and asymmetric volatility spillovers among five emerging markets in which previous studies only focused on the dynamic relationship between returns and transmissions.
There have been numerous investigations among stock markets in different countries to identify the transmission mechanism (Jebran et al. 2017; Huo and Ahmed, 2017; Bala and Takimoto, 2017; Ghouse and Khan, 2017; Baumohl et al. 2018; Mensi et al. 2018; Morales Zumaquero and Sosvilla Rivero, 2018;
Caloia et al. 2018; Lau and Sheng, 2018; BenSaida et al. 2018; Tiwari et al.
2018; Ahmed and Huo, 2018; Naresh et al. 2018; Xuan Vinh and Ellis, 2018).
The main aim of this chapter empirically formulates and estimates the volatility spillover by a multivariate EGARCH model of the daily stock markets returns for selected countries. The model is employed to examine the first and second-moment interdependencies among the various markets. The results reveal that the volatility transmission mechanism is asymmetric, bad news in a given market increase volatility in the next market to trade considerably more than positive innovations for the whole period. However, these results exclude the Croatian stock market in the pre-crisis period and the Czech Republic stock market in the post-crisis period. We find evidence of price spillovers of the intraregional linkages among the stock price movements in the five Central and
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Eastern European countries. For the second moment interactions, the results highlight certain interesting findings that the stock markets are more substantially integrated into a crisis.
Finally, chapter IV focuses on the foreign exchange rate markets in the CEE countries based on the model developed in chapter III. There is a slight difference between the model used in chapter III, we also apply the multivariate EGARCH model but the first moment of return series are used in the mean equation instead of the second moment in chapter III. This measure represents the magnitude of asymmetric shocks and the degree of bilateral interrelatedness because these markets are less volatile than stock returns. Over the past several decades, the majority of Central and Eastern countries running de jure floating exchange rate regimes have smoothly progressed. There are several substantial papers such as (Fidrmuc and Horváth, 2008; Bubak, 2009; Greenwood et al.
2016) who are interested in the analysis of foreign exchange market interdependence and detection of the return and volatility spillovers targeting at helping many market participants make the financial decisions.
This study utilizes the daily US dollar exchange rate data in an attempt to answer the question of the changing nature of volatility spillovers among foreign exchange markets in these nations. The findings indicate that the return spillovers exhibit more significant in the pre-crisis period than in the post-crisis period in the CEE countries. The foreign exchange markets become more independent in a crisis situation. Similarly, the volatility spillover between the foreign exchange markets decreases dramatically and financial markets have not been transmitted during the crisis period. The results also show that Polish and Romania exchange markets influence other markets, especially during the turmoil period. These results raise a question related to the role of market consensus versus information during the period of stress. It would be tested by future researchers using new or more enhanced models to capture the effects and predictions of volatility behavior during the extreme turbulent periods.
Based on the three above topics, we have produced three paper-based thesis namely, “Dynamics of volatility spillover between stock and foreign exchange market: empirical evidence from Eastern European countries”, “Does volatility transmission between stock market returns of Central and Eastern European
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countries vary from normal to turbulent periods? evidence from EGARCH model?” and “Volatility Behavior of the Foreign Exchange Rate and Transmission among Central and Eastern European Countries: Evidence from EGARCH model”, respectively, which are accepted for publication.
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LITERATURE OVERVIEW
There are countless studies conducted in exploring integration and spillover effects across financial markets in the finance literature. Most of the researchers made their significant contribution to the existing literature by filling the gap of exploring knowledge about the volatility transmission mechanism of the dynamic linkage between the exchange rates and the stock market in the different countries. In this study, we primarily based on the previous literature in connection with the topic of volatility transmission across countries. In addition, the flow-oriented and stock-oriented models are two original models widely used by the majority of the previous investigations.