Sercan Eraslan Knihy

We use volatility impulse response analysis estimated from the bivariate GARCH-BEKK model to quantify the size and the persistence of different types of oil price shocks on stock return volatility and the covariance between oil price changes and stock returns for a wide range of net oil-importing and oil-exporting countries. We find that precautionary demand followed by aggregate demand-side shocks, compared to supply-side ones, have higher positive and persistent effects on the conditional variances of stock returns for all countries. Moreover, we show that precautionary demand shocks, unlike the other types of shocks, mostly affect the covariances between oil price changes and stock returns; their effects being negative for all countries except China, Norway and Russia, where they are positive.

This paper investigates the dynamic linkages in terms of the first and second moments between stock and bond returns, within a wide range of advanced economies, over the different phases of the recent financial crisis. The adopted empirical framework is a bivariate volatility model, where volatility spillovers of either positive or negative sign are allowed for. Our results lend support to the existence of a substantial time-variation in the dynamic linkages between these financial assets over the different stages of the recent crisis. In particular, our results of the return spillovers show that such spillovers mostly run from stocks to bonds and exhibit a time-varying pattern over all three stages of the crisis in most countries. Regarding the volatility spillovers, such spillovers from bond returns to those of stocks are stronger than the other way round and also exhibit a time-varying pattern in most countries. Furthermore, the portfolio performance comparison results show that by considering time-varying return and volatility spillovers when calculating the risk-minimising portfolio weights of the selected assets, the portfolio volatility can be reduced despite limited diversification opportunities within national markets in times of financial crises.

This paper investigates the asymmetries in arbitrage trading with onshore and offshore renminbi spot rates, focusing on the time-varying driving factors behind the deviations of the two rates from their long-run equilibrium. Fundamentally, offshore and onshore renminbi rates represent the same economic quantity and hence should be driven by the same pricing mechanism. However, the two exchange rates deviate remarkably from each other, creating arbitrage opportunities over many days. For the empirical analysis, I build a three-regime threshold vector error correction model with offshore and onshore spot rates and further regime-dependent explanatory variables. The model is estimated in different periods in order to consider the impact of appreciation and depreciation expectations on possible arbitrage trading. The estimation results suggest that directional expectations, global risk sentiment, and local as well as global liquidity conditions dominate the adjustment process in the absence of arbitrage trading when the offshore rate is stronger than its onshore counterpart. However, the error correction mechanism of the offshore (onshore) rate toward its equilibrium with the onshore (offshore) rate is driven by the arbitrage trading due to a relatively weaker (stronger) offshore (onshore) rate in the upper regime in times of appreciation (depreciation) expectations.

We propose a novel time-varying parameters mixed-frequency dynamic factor model which is integrated into a dynamic model averaging framework for macroeconomic nowcasting. Our suggested model can efficiently deal with the nature of the real-time data flow as well as parameter uncertainty and time-varying volatility. In addition, we develop a fast estimation algorithm. This enables us to generate nowcasts based on a large factor model space. We apply the suggested framework to nowcast German GDP. Our recursive out-of-sample forecast evaluation results reveal that our framework is able to generate forecasts superior to those obtained from a naive and more competitive benchmark models. These forecast gains seem to emerge especially during unstable periods, such as the Great Recession, but also remain over more tranquil periods.