This study employs the asymmetric threshold cointegration test suggested by Enders and Siklos (2001) and creates EC-EGARCH(1, 1)M model to investigate the pass-through of money market rate to banking retail rates in Taiwan and Hong Kong. It further explores the impact of interest volatility on interest rates. Over the period of February 1988 to December 2004, we find that the interest pass-thou...

In this paper, we investigate the long run dynamics of the intraday range of the GBP/USD, JPY/USD and CHF/USD exchange rates. We use a non-parametric filter to extract the low frequency component of the intraday range, and model the cyclical deviation of the range from the long run trend as a stationary autoregressive process. We find that the long run trend is time-varying but highly persisten...

This paper makes a comparison of global, feedback and smoothed-piecewise neural prediction models for financial time series (FTS) prediction problem. Each model is implemented by various neural network (NN) architectures: global model by a multilayer perceptron (MLP), feedback model by a recurrent neural network (RNN) and smoothed-piecewise model by a mixture of experts (MoE) structure. The adv...

Financial time series forecast has been classified as standard problem in forecasting due to its high non-linearity and high volatility in data. Statistical methods such as GARCH, GJR, EGARCH and Artificial Neural Networks (ANNs) based on standard learning algorithms such as backpropagation have been widely used for forecasting time series volatility of various fields. In this paper, we propose...

In this paper we conduct a close examination of the relationship between return shocks and conditional volatility. We do so in a framework where the impact of return shocks on conditional volatility is specified as a general function and estimated nonparametrically using implied volatility data—the Market Volatility Index (VIX). This setup can provide a good description of the impact of return ...