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Factor GARCH-ITO Models for High-Frequency Data with Application to Large Volatility Matrix Prediction

Kim, Donggyu - 2017

Several novel large volatility matrix estimation methods have been developed based on the high-frequency financial data … matrix and facilitates estimation of large volatility matrices. However, for predicting future volatility matrices, these … a quasi-maximum likelihood estimation method for the parameter of the factor GARCH-Ito model. We also apply it to …

Persistent link: https://www.econbiz.de/10012941598

Forecasting Limit Order Book Liquidity Supply-Demand Curves with Functional Autoregressive Dynamics

Chen, Ying - 2017

in-sample estimation and 98.2 percent in out-of-sample forecast experiments. It produces accurate 5-, 25- and 50-$minute …

Persistent link: https://www.econbiz.de/10012968564

Model Averaging in Markov-Switching Models : Predicting National Recessions with Regional Data

Guerin, Pierre - 2015

This paper introduces new weighting schemes for model averaging when one is interested in combining discrete forecasts from competing Markov-switching models. In particular, we extend two existing classes of combination schemes – Bayesian (static) model averaging and dynamic model averaging...

Persistent link: https://www.econbiz.de/10013011832

Forecasting Stock Returns with Large Dimensional Factor Models

Giovannelli, Alessandro - 2020

We study equity premium out-of-sample predictability by extracting the information contained in a high number of macroeconomic predictors via large dimensional factor models. We compare the well known factor model with a static representation of the common components with a more general model...

Persistent link: https://www.econbiz.de/10012854353

Forecasting Random Walks under Drift Instability

Pesaran, M. Hashem - 2011

This paper considers forecast averaging when the same model is used but estimation is carried out over different … estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or … more structural breaks. It is shown that compared to using forecasts based on a single estimation window, averaging over …

Persistent link: https://www.econbiz.de/10012714199

Time Series Approach to the Evolution of Networks : Prediction and Estimation

Bykhovskaya, Anna - 2021

and techniques for estimation of the parameters of the model and for prediction of its future values.Natural applications …

Persistent link: https://www.econbiz.de/10013216722

Forecasting Random Walks Under Drift Instability

Pesaran, M. Hashem - 2011

Persistent link: https://www.econbiz.de/10012756639

Tracking economic activity with alternative high-frequency data

Eckert, Florian; Kronenberg, Philipp; Mikosch, Heiner; … - 2020

Most macroeconomic indicators failed to capture the sharp economic fluctuations during the Corona crisis in a timely manner. Instead, alternative high-frequency data have been used, aiming to monitor the economic situation. However, these data are often only loosely related to the business cycle...

Persistent link: https://www.econbiz.de/10012395297

Daily news sentiment and monthly surveys : a mixed-frequencydynamic factor model for nowcasting consumer confidence

Algaba, Andres; Borms, Samuel; Boudt, Kris; Verbeken, Brecht - 2021

model framework uses a novel covariance matrix specification. Model estimation and real-time filtering of the latent …

Persistent link: https://www.econbiz.de/10012437743

Forecasting exchange rates : the time-varying relationship between exchange rates and Taylor rule fundamentals

Haskamp, Ulrich - 2017

There is empirical evidence for a time-varying relationship between exchange rates and fundamentals. Such a relationship with time-varying coefficients can be estimated by a Kalman filter model. A Kalman filter estimates the coefficients recursively depending on the prediction error of the...

Persistent link: https://www.econbiz.de/10011700704