Inflation and inflation uncertainty in China

The study examines the relationship between inflation and inflation uncertainty in China using Generalized Autoregressive Conditional Heteroscedasticity model. Particularly, this link is investigated in China’s urban and rural sectors, motivated by the substantial urban–rural divide. The results provide strong statistical supportive evidence that higher inflation raises inflation uncertainty. On the other hand, evidence on the effect of inflation uncertainty on inflation is mixed depending on the sample periods and areas examined. The understanding of inflation-uncertainty nexus in China could provide implications to policymakers in the adoption of monetary policies.     

Islamic equity market integration and volatility spillover between emerging and US stock markets

The purpose of this paper is to study the conditional correlations across the US market and a sample of five Islamic emerging markets, namely Turkey, Indonesia, Pakistan, Qatar, and Malaysia. The empirical design uses MSCI (Morgan Stanley Capital International) Islamic equity index since it applies stringent restrictions to include companies. Indeed, two main restrictions must be met: (i) the business activity must be compliant with Shari’ah (i.e., Islamic law) guidelines and (ii) interest-bearing investments and leverage ratios should not exceed upper limits. Three models are used: multivariate GARCH BEKK, CCC, and DCC. The estimation results of the three models show that the US and Islamic emerging equity markets are weakly correlated over time. No sheer evidence supports that the US market spills over into the Islamic emerging equity markets. Besides interpreting the results in terms of weak market integration, the peculiar specificities of the Islamic finance industry and the admittance conditions to the MSCI Islamic equity index contribute to explaining them. Indeed, Islamic finance bans interest-bearing investments and imposes some rules, such as asset-backing, which has sizeable impacts on volatility spillover and shocks transmissions, alongside with the close linkage between real and financial sectors. These findings suggest that investors should take caution when investing in the Islamic emerging equity markets and diversifying their portfolios in order to minimize risk.     

Nonlinear causality testing with stepwise multivariate filtering: Evidence from stock and currency markets

We examine the spillovers of the US subprime crisis to Asian and European economies and in particular to what extent currency and stock markets have been affected by the crisis. Linear and nonlinear dependencies are detected after pairwise and system-wise causality analysis. A new stepwise multivariate filtering approach is implemented after controlling for conditional heteroskedasticity in the raw data and in VAR/VECM residuals using multivariate GARCH models. Significant nonlinear causal linkages persisted even after the application of GARCH-BEKK, CCC-GARCH and DCC-GARCH modelling. This indicates that volatility effects might partly induce nonlinear causality. Perhaps new short-term asset-pricing models could be developed to explain this stylized fact. These results might also have important implications for hedging, trading strategies and financial market regulation.     

Long memory in the volatility of China stock returns

In this paper, we empirically examine the volatility process of China's stock market returns using daily and weekly Shanghai and Shenzhen stock indices during January 1990 to August 2008. To investigate the property of the process, we used the FIGARCH (fractionally integrated GARCH) model including GARCH and IGARCH processes as special cases. Since the FIGARCH model allows fractional integration order, it can detect hyperbolically decaying volatility processes which cannot be explained by previous models with integer integration order. Our results show that the Shanghai and Shenzhen stock indices exhibit long-term dependencies. The long memory properties of the Shanghai and Shenzhen stock markets do not seem to be spuriously induced without exception.     

Intraday bidirectional volatility spillover across international stock markets: does the global financial crisis matter?

This article studies volatility spillover between the US and the three largest European stock markets (Frankfurt, London and Paris) around the time of the recent Subprime crisis. In order to investigate the impact of the latter, we break our sample down into two sub-periods: a pre-crisis period and a post-crisis period, using a structural break test that has the advantage of endogenously testing for further breaks in the data. Unlike previous studies that have frequently investigated this issue using low frequency data, our article makes use of intraday data. Accordingly, using Threshold generalized autoregressive conditional heteroscedasticity (GARCH) model estimations, we find weak evidence of volatility transmission between the two regions before the Subprime crisis. However, during the post-crisis period, we record returns and volatility spillover from US to European markets and vice versa at different times of the trading day, indicating that the two regions became more dependent during the recent Subprime crisis, a finding that supports the contagion hypothesis between the US and European stock markets.     

Revisiting the risk-return relation in the Chinese stock market: Decomposition of risk premium and volatility feedback effect

The empirical results of the risk-return relationship are mixed for both mature and merging markets. In this paper, we develop a new volatility model to revisit the risk-return relation of the aggregate stock market index by extending the Realized GARCH model of Hansen et al. (2012) with the Wang and Yang (2013) framework, in which the overall risk-return relation is decomposed into a risk premium and a volatility feedback effect. An empirical analysis of three major Chinese stock indices reveals positive risk premium and negative volatility feedback effect, and those findings are stable across different markets and sub-samples. However, their relative magnitudes differ between markets and varies through time.     

Measuring liquidity with return volatility: An analytical approach based on heavy-tailed Censored-GARCH model

The measurement of liquidity based on low-frequency data is a crucial issue in the financial market microstructure literature. This paper extends the commonly used LOT liquidity model by incorporating the characterization of the volatility dynamics and distributional properties of return series, thereby significantly improving both the goodness-of-fit of liquidity model and the estimation performance of the existing low-frequency liquidity measures. The new models, which have a special form of heavy-tailed Censored-GARCH model, have challenges in estimation. We then provide an approximate maximum likelihood estimation method to circumvent this problem. A real data analysis is conducted to evaluate the performance of the new liquidity measures. The results show overwhelming evidence that our new measures have advantages over the existing measures in both estimation error and correlation coefficient with high-frequency bid-ask spread. The robustness check analysis further illustrates that the advantages of our new measures are stable across different stock industries and different turnover levels.     

Forecasting the volatility of asset returns: The informational gains from option prices

A new class of forecasting models is proposed that extends the realized GARCH class of models through the inclusion of option prices to forecast the variance of asset returns. The VIX is used to approximate option prices, resulting in a set of cross-equation restrictions on the model’s parameters. The full model is characterized by a nonlinear system of three equations containing asset returns, the realized variance, and the VIX, with estimation of the parameters based on maximum likelihood methods. The forecasting properties of the new class of forecasting models, as well as a number of special cases, are investigated and applied to forecasting the daily S&P500 index realized variance using intra-day and daily data from September 2001 to November 2017. The forecasting results provide strong support for including the realized variance and the VIX to improve variance forecasts, with linear conditional variance models performing well for short-term one-day-ahead forecasts, whereas log-linear conditional variance models tend to perform better for intermediate five-day-ahead forecasts.     

Global economic uncertainty and the Chinese stock market: Assessing the impacts of global indicators

We comparatively assess the influence of global economic uncertainty measures on Chinese stock market volatility. Using a model based on generalized autoregressive conditional heteroskedasticity and mixed-data sampling, the results show that the global economic policy uncertainty index, the geopolitical risk index, and the global economic condition index all significantly influence the long-term volatility of China’s equity market. We highlight which of these measures has the most explanatory power under differing contexts. As uncertainty measures have wide applicability, investors, policymakers, and academicians will be quite interested in our results.     

Causality and volatility patterns between gold prices and exchange rates

This paper provides a new perspective on the link between gold prices and exchange rates. Based on gold prices denominated in five different currencies and the related bilateral exchange rates, we put causalities and short-run volatility transmission under closer scrutiny. We provide evidence that the identification of a strong hedge function of gold requires an explicit modeling of the volatility component. For all currencies, exchange rate depreciations initially have a negative impact on the gold price after one day which turns out to be positive after two days in most of the cases. Contrary to previous studies, our results point to a specific role of the dollar in the context of gold-exchange rate relationships: volatility of dollar exchange rates more frequently results in strong hedging functions of gold prices. Furthermore, the gold price denominated in the US dollar tends to increase after a depreciation of the dollar.