scholarly journals Nonlinear Interactions and Volatility Spillovers between Stock and Foreign Exchange Markets: The STVEC-STGARCH-DCC Approach

2021 ◽  
pp. 45-77
Author(s):  
Hsiang-Hsi Liu ◽  
Pi-Hsia Hung ◽  
Po-Hung Luo Cho

This study aims to investigate the interactions, volatility spillovers and smooth transition effects between stock and foreign exchange markets in emerging versus developed countries by the Smooth Transition Vector Error Correction-Smooth Transition GARCH with Dynamic Conditional Correlation model (STVE-STGARCH-DCC). The empirical results yield several findings. Firstly, boom stock markets in emerging countries will trigger their domestic currency appreciation, while prosperous stock markets in developed countries result in currency depreciation. Secondly, the conditional variances for stock markets mainly result from unexpected shocks, past volatility, and short-term impact effects, thus leading to a persistence of volatility in both emerging and developed markets. The conditional variances for foreign exchange markets display similar patterns but show weaker short-term impact effects and slower transition speeds. Thirdly, unexpected shocks in a stock market broadly affect its own stock volatility, while those only affect India’s volatility in the rupee market. In contrast, unexpected shocks in foreign exchange markets mainly affect foreign exchange volatility, except for India; however, those influence their stock volatility only for emerging countries, such as India and South Africa. Lastly, developed markets are more efficient than emerging markets are. JEL classification numbers: C32, C51, C52, G11, G15 Keywords: Asymmetric Effects, Bivariate STVEC-STGARCH-DCC, Market Efficiency, Nonlinear Model, Smooth Transition Auto-regression, ICSS Algorithm.

2021 ◽  
Vol 14 (6) ◽  
pp. 270
Author(s):  
Walid Abass Mohammed

In this paper, we investigate the “static and dynamic” return and volatility spillovers’ transmission across developed and developing countries. Quoted against the US dollar, we study twenty-three global currencies over the time period 2005–2016. Focusing on the spillover index methodology, the generalised VAR framework is employed. Our findings indicate no evidence of bi-directional return and volatility spillovers between developed and developing countries. However, unidirectional volatility spillovers from developed to developing countries are highlighted. Furthermore, our findings document significant bi-directional volatility spillovers within the European region (Eurozone and non-Eurozone currencies) with the British pound sterling (GBP) and the Euro (EUR) as the most significant transmitters of volatility. The findings reiterate the prominence of volatility spillovers to financial regulators.


Risks ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 120 ◽  
Author(s):  
Fengming Qin ◽  
Junru Zhang ◽  
Zhaoyong Zhang

This study examines empirically the volatility spillover effects between the RMB foreign exchange markets and the stock markets by employing daily returns of the Chinese RMB exchange rates and the stock markets in China and Japan during the period in 1998–2018. We find evidence that there exist co-volatility effects among the financial markets in China and Japan, and the volatility of RMB exchange rates contribute to the co-volatility spillovers across the financial markets. Reversely, the return shock from the stock markets can also generate co-volatility spillover to the foreign exchange markets. The bidirectional relationship reveals that both the fundamental hypothesis and the investor-induced hypothesis are valid. Our estimates also show that the spillover effects led by the stock market in Japan are stronger than that from the foreign exchange markets and the Chinese stock markets, implying that market with higher accessibility has greater spillover effects onto other markets. We also found that the average co-volatility spillover effects among the RMB exchange markets and the stock markets in Japan and China are generally negative. These findings have important policy implications for risk management and hedging strategies.


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