Asean 5 Stock Markets, Currency Risk and Volatility Spillover

INTRODUCTION Generally, volatility spillover occurs when changes in price volatility in one market create a lagged impact in other markets. When applied to currencies and stock markets, volatility spillover occurs when changes in foreign currency markets affect stock markets, over and above local effects. As several European and Asian countries consider the benefits of joining the Eurozone and ASEAN, respectively, the impact of volatility transmissions and spillovers raises key financial and policy questions that need to be further studied. From a business perspective, the prevalence of volatility spillovers can guide multinational corporations in managing their currency risk and exposure in these countries, a key element in their international diversification efforts. (Kanas, 2000). This research investigates the interdependence of stock returns and exchange rate changes in the ASEAN5 countries. The countries included are the Philippines, Singapore, Malaysia, Thailand and Indonesia for the period January 4, 2000 to December 31, 2010. This study will also examine if there are volatility spillovers from stock returns to exchange rate changes present in each country and the ASEAN5. THEORETICAL AND CONCEPTUAL FRAMEWORK The Nature of Volatility Transmission and Volatility Spillover Two approaches provide the possible link between exchange rates to the other economic and financial sectors. The first, so-called looks at the impact of exchange rates on the balance of trade, such as those studied by Mundell in 1963 and by Dornbusch and Fisher in 1980. The flow model posits that changes in exchange rates affect international competitiveness and trade balances, thereby influencing real income and output. Stock prices, generally interpreted as the present values of future cash flows of firms, react to exchange rate changes and form the link among future income, interest rate innovations, and current investment and consumption decisions. (Yang and Doong, 2004) The other model, stock-oriented models of exchange rates such as those studied by Branson (1983) and Frankel (1983) models view exchange rates as equating the supply and demand for assets such as stocks and bonds. This approach gives the capital account an important role in determining exchange rate dynamics. Since the values of financial assets are determined by the present values of their future cash flows, expectations of relative currency values play a considerable role in their price movements, especially for internationally held financial assets. Therefore, stock price innovations may affect, or be affected by, exchange rate dynamics. (Ibid, 1984) An illustration of the second approach can be seen in Figure 1, where transmission and spillover is seen as an input-process-output model: Because there has been no dominant approach to explain the impact of volatility spillover, numerous studies have populated the literature in recent years. The residual effect of the Global Financial Crisis still being felt in many countries as well as those integrated economies such as the Eurozone and ASEAN provide the motivation for sustained interest in this field of study. LITERATURE REVIEW Kanas (1998 and 2000) was one of the first to have examined volatility spillovers in the foreign exchange and stock markets. Using EGARCH, he studied the interdependence of stock returns and exchange rate changes among six industrialized countries, namely the United States (US), the United Kingdom (UK), Japan, Germany, France and Canada. The study concluded that there is evidence of volatility spillovers from stock returns to exchange rates changes for all countries except Germany. However, volatility spillovers from exchange rate changes to stock returns are insignificant for all countries. [FIGURE 1 OMITTED] Mishra and Rahman (2010) examined the dynamics of stock market returns volatility of India and Japan using the Threshold Generalized Autoregressive Conditional Heteroskedasticity (TGARCH-M) model. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.