We build a discrete-time non-linear model for volatility forecasting purposes. This model belongs to the class of threshold-autoregressive models, where changes in regimes are governed by past returns. The ability to capture changes in volatility regimes and using more accurate volatility...

This paper proposes the Lagrange multiplier test for the null hypothesis thatthe bivariate time series has only a single common stochastic volatility factor and noidiosyncratic volatility factor. The test statistic is derived by representing the model in alinear state-space form under the...

This paper studies equity price volatility in general equilibrium with news shocks about future productivity and monetary policy. As West (1998) shows, in a partial equilibrium present discounted value model, news about the future cash flow reduces asset price volatility. This paper shows that...

This paper shows that bank linkages have a positive effect on international trade. A global banking network (GBN) is constructed at the bank level, using individual syndicated loan data from Loan Analytics for 1990-2007. Network distance between bank pairs is computed and aggregated to country...

We examine the presence of outliers and time-varying jumps in the returns of four major cryptocurrencies (Bitcoin, Ethereum, Ripple, Dogecoin, Litecoin), and a broad cryptocurrency index (CCI30). The results indicate that only Bitcoin returns are contaminated with outliers. Time-varying jumps...

Intraday high-frequency data of stock returns exhibit not only typical characteristics (e.g., volatility clustering and the leverage effect) but also a cyclical pattern of return volatility that is known as intraday seasonality. In this paper, we extend the stochastic volatility (SV) model for...

This study attempts to evaluate the energy and carbon footprint within the framework of international environmental treaties and the efforts made by 11 large polluting countries to mitigate climate change. The econometric methodology accounts for the presence of cross-sectional dependence while...

Financial data (e.g., intraday share prices) are recorded almost continuously and thus take the form of a series of curves over the trading days. Those sequentially collected curves can be viewed as functional time series. When we have a large number of highly correlated shares, their intraday...

A definition of time based on the assumption of scale invariance may enhance and simplify the analysis of historical series with cyclically recurrent patterns and seasonalities. By enforcing simple-scaling and stationarity of the distributions of returns, we identify a successful protocol of...

This paper addresses the problem of forecasting daily stock trends. The key consideration is to predict whether a given stock will close on uptrend tomorrow with reference to today's closing price. We propose a forecasting model that comprises a features selection model, based on the Genetic...