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Do fiscal shocks explain bond yield in high and low debt economiesApergis, Nicholas; Rehman, Mobeen; Cooray, Arusha; University of Derby; Ton Duc Thang University; Embassy of Sri Lanka, Oslo, Norway (Emerald, 2020-06-29)The goal of this paper is to explore determinants of short-, medium- and long-run bond yields through time series data analysis for 11 developed countries, with five of them being high-debt and remaining as the low-debt economies. By applying variance decomposition using structural vector autoregression (SVAR) model, empirical findings confirm an important role of demand and supply factors that drive the interest rates across their frequency spectrum. Our results also highlight that for interest rates of different maturities, these factors exhibit heterogeneous behavior across high- and low-debt countries during the pre- and post-crisis regimes.
Do global sentiment shocks spillover towards emerging and frontier markets?Apergis, Nicholas; Rehman, Mobeen; University of Derby; Ton Duc Thang University (Emerald, 2020-02-28)This 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. This 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. The 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. The 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. This 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. The 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.