scholarly journals Impact of exchange rate on uncertainty in stock market: Evidence from Markov regime-switching GARCH family models

2020 ◽  
Vol 8 (1) ◽  
pp. 1802806
Author(s):  
Mehdi Zolfaghari ◽  
Saeid Hoseinzade
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Regime Switching ◽  
Markov Regime Switching ◽  
Family Models

Do global sentiment shocks spillover towards emerging and frontier markets?

2020 ◽  
Vol 47 (3) ◽  
pp. 433-465 ◽  
Author(s):  
Mobeen Ur Rehman ◽  
Nicholas Apergis
Keyword(s):  
Stock Market ◽  
Regime Switching ◽  
Linear Models ◽  
Market Returns ◽  
Markov Regime Switching ◽  
Stock Market Returns ◽  
Content Type ◽  
Regime Switching Model ◽  
Switching Model ◽  
Investor Sentiments

PurposeThis study aims to investigate the impact of sentiment shocks based on US investor sentiments, bearish and bullish market conditions. Earlier studies, though very few, only consider the effect of investor sentiments on stock returns of emerging frontier Asian (EFA) markets.Design/methodology/approachThis study uses the application of regime switching model because of its capability to explore time-varying causality across different regimes unlike traditional linear models. The Markov regime switching model uses regime switching probabilities for capturing the potential asymmetries or non-linearity in a model, in this study’s case, thereby adjusting investor sentiments shocks to stock market returns.FindingsThe results of the Markov regime switching method suggests that US sentiment, bullish and bearish market shocks act as a main contributors for inducing variation in EFA stock market returns. The study’s non-parametric robustness results highlight an asymmetric relationship across the mean series, whereas a symmetric relationship across variance series. The study also reports Thailand as the most sensitive market to global sentiment shocks.Research limitations/implicationsThe sensitivity of the EFA markets to these global sentiment shocks highlights their sensitivity and implications for investors relying merely on returns correlation and spillover. These findings also suggest that spillover from developed to emerging and frontier equity markets only in the form of returns following traditional linear models may not be appropriate.Practical implicationsThis paper supports the behavioral aspect of investors and resultant spillover from developed market sentiments to emerging and frontier market returns across international equity markets offering more rational justification for an irrational behavior.Originality/valueThe study’s motivation to use the application of regime switching models is because of its capability to explore time-varying causality across different regimes unlike traditional linear models. The Markov regime switching model uses regime switching probabilities for capturing the potential asymmetries or non-linearity in a model, in the study’s case, thereby adjusting investor sentiments shocks to stock market returns. It is also useful of the adjustment attributable to exogenous events.

scholarly journals Modeling the exchange rate pass-through in Turkey with uncertainty and geopolitical risk: a Markov regime-switching approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Faik Bilgili ◽  
Fatma Ünlü ◽  
Pelin Gençoğlu ◽  
Sevda Kuşkaya
Keyword(s):  
Exchange Rate ◽  
Regime Switching ◽  
Regime Shifts ◽  
Demand Side ◽  
Economic Uncertainty ◽  
Markov Regime Switching ◽  
Content Type ◽  
Domestic Prices ◽  
The Exchange Rate ◽  
Pass Through

Purpose This paper aims to investigate the pass-through (PT) effect in Turkey by using quarterly data for the period 1998: Q1-2019: Q2 to understand the dynamic potential effects of exchange rates on domestic prices. Design/methodology/approach The paper launches several nonlinear models in which the basic determinants of domestic prices in Turkey are determined through Markov regime-switching models (MSMs). Hence, this research follows the variables of the consumer price index (CPI), USD exchange rate, gross domestic product (GDP; demand side of the economy), industrial production index (production side of the economy), economic uncertainty and geopolitical risk index for Turkey. Findings This work explores that the exchange rate and demand side of the economy (GDP) follow a positive nonlinear relationship with CPI at both regimes. The production side of the economy (IP) affects negatively the CPI during regime 0. Economic uncertainty influences the CPI positively at Regime 1, while geopolitical risk has a negative association with CPI at Regime 0. Eventually, the paper provides some policy proposals associated with the impacts of GDP, IP, economic uncertainty and geopolitical risk on CPI in Turkey. Originality/value One may claim that any PT model, which does not observe the possible structural or regime shifts in estimated parameters, might fail to estimate the coefficients unbiasedly and efficiently. Hence, this work differs from available relevant works in the literature since this paper considers linearity or nonlinearity important and reveals that the relevant PT model follows a nonlinear path rather than a linear path, this nonlinear path is converged strongly by MSMs and estimates the significant regime shifts in the constant term and, in parameters of independent variables of PT by MSMs.

scholarly journals Markov Regime-Switching Autoregressive Model of Stock Market Returns in Nigeria

2021 ◽  
pp. 65-83
Author(s):  
Oluwasegun A. Adejumo ◽  
Seno Albert ◽  
Omorogbe J. Asemota
Keyword(s):  
Stock Market ◽  
Regime Switching ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Ar Model ◽  
Stock Market Volatility ◽  
Market Returns ◽  
Markov Regime Switching ◽  
Stock Market Returns ◽  
Returns Forecasting

This study is designed to model and forecast Nigeria’s stock market using the All-Share Index (ASI) as a proxy. By employing the Markov regime-switching autoregressive (MS-AR) model with data from April 2005 to September 2019, the study analyzes the stock market volatility in three distinct regimes (accumulation or distribution – regime 1; big-move – regime 2; and excess or panic phases – regime 3) of the bull and bear periods. Six MS-AR candidate models are estimated and based on the minimum AIC value, MS(3)-AR(2) is returned as the optimal model among the six candidate models. The MS(3)-AR(2) analysis provides evidence of regime-switching behaviour in the stock market. The study also shows that only extreme events can switch the ASI returns from regime 1 to regime 2 and to regime 3, or vice versa. It further specifies an average duration period of 9, 3 and 4 weeks for the accumulation/distribution, big-move and excess/panic regimes respectively which is an evidence of favorable market for investors to trade. Based on Root Mean Square Error and Mean Absolute Error, the fitted MS-AR model is adjudged the most appropriate ASI returns forecasting model. The study recommends investments in stock across the regimes that are switching between accumulation/distribution and big-move phases for promising returns.

scholarly journals Effect of Oil Prices on Exchange Rate Movements in Korea and Japan Using Markov Regime-Switching Models

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4402
Author(s):  
Suyi Kim ◽  
So-Yeun Kim ◽  
Kyungmee Choi
Keyword(s):  
Exchange Rate ◽  
Financial Crisis ◽  
Foreign Exchange ◽  
Regime Switching ◽  
Oil Prices ◽  
Information Criteria ◽  
Markov Regime Switching ◽  
Regime Switching Models ◽  
Switching Models ◽  
Exchange Rate Movements

We examined the effects of oil prices along with fundamental economic variables on exchange rate movements in the Korean and Japanese foreign exchange markets, using two-regime Markov Regime Switching Models (MRSMs) over the period from January 1991 to March 2019. We selected the best MRSMs explaining their exchange rate movements using the Maximum Log-Likelihood and Akaike Information Criteria, and analyze effects of oil prices on their exchange rates based on the selected best MRSMs. We consider two regimes, regime 1 with high-volatility and regime 2 with low-volatility. In Korea, two apparent regimes are observed, and unstable regime 1 consists of two distinct prolonged periods, the 1997 Asian Financial Crisis and the 2008 Global Financial Crisis. Meanwhile in Japan, no evident prolonged regimes are observed. Rather, the two regimes occasionally alternate. Oil prices influence exchange rate movements in regime 2 with low-volatility in Korea, while they do not influence exchange rate movements in either regimes in Japan. The Japanese foreign exchange market is more resistant to external oil price shocks because the Japanese industry and economy has less dependence on oil than Korea.

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