Financial asset returns are known to be conditionally heteroskedastic and generally non-normally distributed, fat-tailed and often skewed. These features must be taken into account to produce accurate forecasts of Value-at-Risk (VaR). We provide a comprehensive look at the problem by considering...

The study proposes and a family of regime switching GARCH neural network models to model volatility. The proposed MS-ARMA-GARCH-NN models allow MS type regime switching in both the conditional mean and conditional variance for time series and further augmented with artificial neural networks to...

We construct a framework for measuring economic activity at high frequency, potentially in real time. We use a variety of stock and flow data observed at mixed frequencies (including very high frequencies), and we use a dynamic factor model that permits exact filtering. We illustrate the...

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from many limitations. HF data feature microstructure problem,...

The purpose of this paper is to investigate whether a dynamic Value at Risk model and high frequency realized volatility models can improve the accuracy of 1-day ahead VaR forecasting beyond the performance of frequently used models. As such, this paper constructs 60 conditional volatility...

Presentation slides highlighting the forecasting technique NNS.ARMA using nonlinear nonparametric statistics in the R-package "NNS".Explains the determination of seasonality using the coefficient of variance of subset series and the implementation of both linear and nonlinear regressions on the...

We use the monetary model of exchange rate determination to generate in-sample and out-of-sample forecasts of the Rupee-Dollar exchange rate. The assumptions of flexible prices and maintenance of Purchasing Power Parity implies that the domestic price level and the exchange rate are endogenously...

This paper attempts to examine, compare and forecast the per capita GDP of India, the USA, China, and Japan for a period of ten years from 2020 to 2029. It studies the concept of economic convergence which states that the developing economies’ per capita income levels tend to move at a faster...

This paper studies the time-varying parameter (TVP) regression model in which the regression coefficients are random walk latent states with time dependent conditional variances. This TVP model is flexible to accommodate a wide variety of timevariation patterns but requires effective shrinkage...

The multi-fractal analysis has been applied to investigate various stylized facts of the financial market including market efficiency, financial crisis, risk evaluation and crash prediction. This paper examines the daily return series of stock index of NASDAQ stock exchange. Also, in this study,...