The economic fundamental and economic policy uncertainty of Mainland China and their impacts on Taiwan and Hong Kong

Sin, Chor-yiu

doi:10.1016/j.iref.2015.02.026

Cited by 33 publications

(15 citation statements)

References 14 publications

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“…As can be seen from Table A2 in the Appendix, there is overwhelming evidence in favor of nonstationarity in the EPU differentials. However, endogeneity of EPUs relative to the exchange rates have been stressed in Colombo (2013) and Sin (2015), and in particular by Duca and Saving (2018), and thus we cannot completely ignore the issue of EPU differentials being endogenous regressors. However, endogeneity of EPUs relative to the exchange rates have been stressed in Colombo (2013) and Sin (2015), and in particular by Duca and Saving (2018), and thus we cannot completely ignore the issue of EPU differentials being endogenous regressors.…”

Section: Datamentioning

confidence: 99%

The role of economic uncertainty in forecasting exchange rate returns and realized volatility: Evidence from quantile predictive regressions

Christou

Gupta

Hassapis

et al. 2018

Journal of Forecasting

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In this paper, we investigate whether the news‐based measure of economic policy uncertainty (EPU) can be used to forecast exchange rate returns and volatility using a quantile regression approach, which accounts for persistence and endogeneity, using data from 13 different countries. Our main findings suggest that: (i) EPU is useful for forecasting exchange rate returns and volatility, (ii) forecasting ability–quantile order relationships exhibit a U‐shape, possibly asymmetric form around the median; and (iii) asymmetries are more pronounced in the case of forecasting volatility.

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Section: Datamentioning

confidence: 99%

The role of economic uncertainty in forecasting exchange rate returns and realized volatility: Evidence from quantile predictive regressions

Christou

Gupta

Hassapis

et al. 2018

Journal of Forecasting

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“…On one hand, Benigno et al, (2012) uses vector autoregressive (VAR) and panel VAR models to analyse the impact of domestic uncertainties (modelled through conditional volatilities of monetary policy, inflation-target and productivity shocks) on the dollar-based real exchange rates of the G6 countries. While on the other hand, Colombo (2013) uses a VAR model to analyse the impact of U.S. uncertainty on the nominal euro-dollar exchange rate, and Sin (2015) using the same approach to study the effect of shocks to Chinese uncertainty on the real exchange rates of Taiwan and Hong Kong relative to the Chinese Yuan. In general, these studies find a significant impact on exchange rates following uncertainty shocks.…”

Section: As Reported In the Triennial Survey Of Global Foreign Exchanmentioning

confidence: 99%

Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test

et al. 2016

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Recent studies have analysed the ability of measures of uncertainty to predict movements in macroeconomic and financial variables. The objective of this paper is to employ the recently proposed nonparametric causality-in-quantiles test to analyse the predictability of returns and volatility of sixteen U.S. dollar-based exchange rates (for both developed and developing countries) over the monthly period of 1999:01-2012:03, based on information provided by a news-based measure of relative uncertainty, i.e., the differential between domestic and U.S. uncertainties. The causality-in-quantile approach allows us to test for not only causality-in-mean (1 st moment), but also causality that may exist in the tails of the joint distribution of the variables. In addition, we are also able to investigate causality-in-variance (volatility spillovers) when causality in the conditional-mean may not exist, yet higher order interdependencies might emerge. We motivate our analysis by employing tests for nonlinearity. These tests detect nonlinearity, as well as the existence of structural breaks in the exchange rate returns, and in its relationship with the EPU differential, implying that the Granger causality tests based on a linear framework is likely to suffer from misspecification. The results of our nonparametric causalityin-quantiles test indicate that for seven exchange rates EPU differentials have a causal impact on the variance of exchange rate returns but not on the returns themselves at all parts of the conditional distribution. We also find that EPU differentials have predictive ability for both exchange rate returns as well as the return variance over the entire conditional distribution for four exchange rates.

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“…forecasting value-at-risk using block structure multivariate stochastic volatility models (Asai, Caporin and McAleer, 2014), the time-varying causality between spot and futures crude oil prices: a regime switching approach (Balcilar, Gungor and Hammoudeh, 2014), a regimedependent assessment of the information transmission dynamics between oil prices, precious metal prices and exchange rates (Balcilar, Hammoudeh and Fru Asaba, 2014), a practical approach to constructing price-based funding liquidity factors (Bouwman, Buis, PieterseBloem and Tham, 2014), realized range volatility forecasting: dynamic features and predictive variables (Caporin and Velo, 2014), modelling a latent daily tourism financial conditions index (Chang, 2014), bank ownership, financial segments and the measurement of systemic risk: an application of CoVaR (Drakos and Kouretas, 2014), model-free volatility indexes in the financial literature: a review (Gonzalez-Perez, 2014), robust hedging performance and volatility risk in option markets: application to Standard and Poor's 500 and Taiwan index options (Han, Chang, Kuo and Yu, 2014), price cointegration between sovereign CDS and currency option markets in the financial crises of 2007-2013(Hui and Fong, 2014, whether zombie lending should always be prevented (Jaskowski, 2014), preferences of risk-averse and risk-seeking investors for oil spot and futures before, during and after the global financial crisis (Lean, McAleer and Wong, 2014), managing financial risk in Chinese stock markets: option pricing and modeling under a multivariate threshold autoregression (Li, Ng and Chan, 2014), managing systemic risk in The Netherlands (Liao, Sojli and Tham, 2014), mean-variance portfolio methods for energy policy risk management (Marrero, Puch and Ramos-Real, 2014), on robust properties of the SIML estimation of volatility under micro-market noise and random sampling (Misaki and Kunitomo, 2014), ALRIGHT: Asymmetric LaRge-Scale (I)GARCH with Hetero-Tails (Paolella and Polak, 2014), the economic fundamentals and economic policy uncertainty of Mainland China and their impacts on Taiwan and Hong Kong (Sin, 2014), prediction and simulation using simple models characterized by nonstationarity and seasonality 5 (Swanson and Urbach, 2014), and volatility forecast of stock indexes by model averaging using high frequency data (Wang and Nishiyama, 2014).…”

Section: Introductionmentioning

confidence: 99%

Advances in financial risk management and economic policy uncertainty: An overview

Hammoudeh

McAleer

2015

International Review of Economics & Finance

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Financial risk management is difficult at the best of times, but especially so in the presence of economic uncertainty and financial crises. The purpose of this special issue on "Advances in Financial Risk Management and Economic Policy Uncertainty" is to highlight some areas of research in which novel econometric, financial econometric and empirical finance methods have contributed significantly to the analysis of financial risk management when there is economic uncertainty, especiallythe power of print: uncertainty shocks, markets, and the economy, determinants of the banking spread in the Brazilian economy: the role of micro and macroeconomic factors, forecasting value-at-risk using block structure multivariate stochastic volatility models, the time-varying causality between spot and futures crude oil prices: a regime switching approach, a regimedependent assessment of the information transmission dynamics between oil prices, precious metal prices and exchange rates, a practical approach to constructing price-based funding liquidity factors, realized range volatility forecasting: dynamic features and predictive variables, modelling a latent daily tourism financial conditions index, bank ownership, financial segments and the measurement of systemic risk: an application of CoVaR, model-free volatility indexes in the financial literature: a review, robust hedging performance and volatility risk in option markets: application to Standard and Poor's 500 and Taiwan index options, price cointegration between sovereign CDS and currency option markets in the global financial crisis, whether zombie lending should always be prevented, preferences of risk-averse and risk-seeking investors for oil spot and futures before, during and after the global financial crisis, managing financial risk in Chinese stock markets: option pricing and modeling under a multivariate threshold autoregression, managing systemic risk in The Netherlands, mean-variance portfolio methods for energy policy risk management, on robust properties of the SIML estimation of volatility under micro-market noise and random sampling, asymmetric large-scale (I)GARCH with hetero-tails, the economic fundamentals and economic policy uncertainty of Mainland China and their impacts on Taiwan and Hong Kong, prediction and simulation using simple models characterized by nonstationarity and seasonality, and volatility forecast of stock indexes by model averaging using high frequency data. JEL Classification AbstractFinancial risk management is difficult at the best of times, but especially so in the presence of

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The economic fundamental and economic policy uncertainty of Mainland China and their impacts on Taiwan and Hong Kong

Cited by 33 publications

References 14 publications

The role of economic uncertainty in forecasting exchange rate returns and realized volatility: Evidence from quantile predictive regressions

The role of economic uncertainty in forecasting exchange rate returns and realized volatility: Evidence from quantile predictive regressions

Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test

Advances in financial risk management and economic policy uncertainty: An overview

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