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Generalized autoregressive conditional heteroskedasticity
A natural generalization of the ARCH (Autoregressive Conditional Heteroskedastic) process introduced in Engle (1982) to allow for past conditional variances in the current conditional varianceExpand
ANSWERING THE SKEPTICS: YES, STANDARD VOLATILITY MODELS DO PROVIDE ACCURATE FORECASTS*
A voluminous literature has emerged for modeling the temporal dependencies in financial market volatility using ARCH and stochastic volatility models. While most of these studies have documentedExpand
Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model
A multivariate time series model with time varying conditional variances and covariances, but constant conditional correlations is proposed. In a multivariate regression framework, the model isExpand
Modeling and Forecasting Realized Volatility
TLDR
A general framework for integration of high-frequency intraday data into the measurement, modeling, and forecasting of daily and lower frequency volatility and return distributions is provided and the links between the conditional covariance matrix and the concept of realized volatility are formally developed. Expand
Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility
A growing literature documents important gains in asset return volatility forecasting via use of realized variation measures constructed from high-frequency returns. We progress by using newlyExpand
Intraday periodicity and volatility persistence in financial markets
Abstract The pervasive intraday periodicity in the return volatility in foreign exchange and equity markets is shown to have a strong impact on the dynamic properties of high frequency returns. OnlyExpand
Fractionally integrated generalized autoregressive conditional heteroskedasticity
Abstract The new class of Fractionally Integrated Generalized AutoRegressive Conditionally Heteroskedastic (FIGARCH) processes is introduced. The conditional variance of the process implies a slowExpand
The distribution of realized stock return volatility
Abstract We examine “realized” daily equity return volatilities and correlations obtained from high-frequency intraday transaction prices on individual stocks in the Dow Jones Industrial Average. WeExpand
Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances
We study the properties of the quasi-maximum likelihood estimator (QMLE) and related test statistics in dynamic models that jointly parameterize conditional means and conditional covariances, when aExpand
A CONDITIONALLY HETEROSKEDASTIC TIME SERIES MODEL FOR SPECULATIVE PRICES AND RATES OF RETURN
The distribution of speculative price changes and rates of return data tend to be uncorrelated over time but characterized by volatile and tranquil periods. A simple time series model designed toExpand
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