This study investigates the extent of the contribution of the original GARCH model to our understanding of the stochastic process underlying exchange rate price changes, and examines if the movement of current research to GARCH type models exclusively is warranted. GARCH(1,1) parameters are calculated on a yearly basis and used to standardize the exchange rate price change data. Frequency distr...

This paper derives an analytical expression for an impulse-response function for a vector autoregression with multivariate GARCH errors, where the vector of conditional means is a function of the conditional variances. We also provide the appropriate interpretation of an impulse-response function for such models and suggest interesting empirical issues that can be addressed within this framework.

In this paper we investigate the properties of the Lagrange Multiplier LM test for autoregressive conditional heteroskedasticity ARCH and generalized ARCH GARCH in the presence of additive outliers AO s We show an alytically that both the asymptotic size and power are adversely a ected if AO s are neglected the test rejects the null hypothesis of homoskedasticity too often when it is in fact tr...

We introduce a new semiparametric model, GARCH with Functional EX ogeneous Liquidity (GARCH-FunXL), to capture the impact of liquidity, as implied by a stock exchange’s complete electronic limit order book (LOB), on asset price volatility. LOB-implied liquidity can be viewed as a functional rather than scalar or vectorial stochastic process. We adopt recent ideas from the functional data analys...

risk prediction plays an increasing role in financial risk management. this study aims to investigate existence of asymmetry and long memory volatility in tehran stock exchange index daily data over period of 1998-2006. 1467 daily index returns are used for volatility modeling via garch (long & short memory) processes for both normal and t-student innovations. the specification and forecasting ...

in general, energy prices, such as those of crude oil, are affected by deterministic events such as seasonal changes as well as non-deterministic events such as geopolitical events. it is the non-deterministic events which cause the prices to vary randomly and makes price prediction a difficult task. one could argue that these random changes act like noise which effects the deterministic variat...

Yingfu Xie. Maximum Likelihood Estimation and Forecasting for GARCH, Markov Switching, and Locally Stationary Wavelet Processes. Doctoral Thesis. ISSN 1652-6880, ISBN 978-91-85913-06-0. Financial time series are frequently met both in daily life and the scientific world. It is clearly of importance to study the financial time series, to understand the mechanism giving rise to the data, and/or p...

This paper addresses the question of the selection of multivariate GARCH models in terms of variance matrix forecasting accuracy with a particular focus on relatively large scale problems. We consider 10 assets from the NYSE and compare 125 model based one, five and twenty-day ahead conditional variance forecasts over a period of 10 years using the Model Confidence Set (MCS) and the Superior Pr...