This study compares parametric and non-parametric techniques in terms of their forecasting power on implied volatility indices. We extend our comparisons using combined and model-averaging models. The forecasting models are applied on eight implied volatility indices of the most important stock...

This study provides a new approach for implied volatility indices forecasting. We assess whether non-parametric techniques provide better predictions of implied volatility compared to standard forecasting models, such as AFRIMA and HAR. A combination of Singular Spectrum Analysis (SSA) and...

Surpassing the decoupling expectation, the global economic crisis is now spreading into Indian economy through various channels. Indeed, this brief survey of the effects of crisis suggests that India’s financial and real sectors are closely integrated with the global financial and export...

This study seeks to address a number of rising policy concerns from the aftermath of the recent subprime crisis. Did foreign bank lending decline sharply and transmit the financial shocks from the advanced economies to the SEACEN emerging markets? Was the decline driven by the drying-up in...

Amidst the global financial uncertainties since 2007, the East and Southeast Asian economies continued to attract a significant bulk of the global banks’ loans to emerging markets, albeit at a decelerating rate. The alleged advantages of these lending are wellknown. Yet the recent interruption...

In the 19th century, Japan was one of the nations where the Mexican dollar had a lasting presence. The Meiji government introduced the yen as a new domestic currency during the 1870s and began tightening regulations on yogin trading, which involved the foreign exchange of Mexican and Japanese...

This paper investigates the estimation of the Value-at-Risk (VaR) across various probability levels for the log-returns of a comprehensive dataset comprising four thousand crypto-assets. Employing four recently introduced Adaptive Conformal Inference (ACI) algorithms, we aim to provide robust...

This paper investigates the economic importance of nonparametrically/semiparametrically modelling the shape and the change in the unknown distribution of returns in portfolio allocation problems from a Bayesian perspective. Besides parametric multivariate GARCH (MGARCH) benchmark models for...

This paper introduces a novel Bayesian time series model that combines the nonparametric features of an infinite hidden Markov model with the volatility persistence captured by the GARCH framework, to effectively model and forecast short-term interest rates. When applied to US 3-month Treasury...

Using parametric and nonparametric methods, inflation persistence is examined through the relationship between the exclusions-from-core measure of inflation and total inflation for two sample periods and five in-sample forecast horizons ranging from one to twelve quarters over fifty vintages of...