An Autoregressive Conditional Filtering Process to Remove Intraday Seasonal Volatility and Its Application to Testing the Noisy Rational Expectations Model

doi 10.25148/etd.fi08121903

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Jang Hyung Cho

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Florida International University

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An Autoregressive Conditional Filtering Process to Remove Intraday Seasonal Volatility and Its Application to Testing the Noisy Rational Expectations Model

Full Text

Abstract

Date

Authors

Publisher

Related search

Modelling Tourism Demand Volatility Using a Seasonal Autoregressive Integrated Moving Average Autoregressive Conditional Heteroscedasticity Model for Victoria Falls Rainforest Arrivals in Zimbabwe

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Intraday Volatility Forecasting From Implied Volatility

Quantile Autoregressive Distributed Lag Model With an Application to House Price Returns*

Learning Process and Rational Expectations: An Analysis Using a Small Macroeconomic Model for New Zealand

Prediction of the Volatility of Ghana Stock Exchange Main Index by Using the Generalised Autoregressive Conditional Heteroskedasticity Model

A Slightly Depressing Jump Model: Intraday Volatility Pattern Simulation

Application of Vector Autoregressive (VAR) Process in Modelling Reshaped Seasonal Univariate Time Series