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Comprehensive Time-Series Regression Models Using Gretl — U.S. GDP and Government Consumption Expenditures & Gross Investment from 1980 to 2013
Shi, Juehui - 2019
Using Gretl, I apply ARMA, Vector ARMA, VAR, state-space model with a Kalman filter, transfer-function and intervention models, unit root tests, cointegration test, volatility models (ARCH, GARCH, ARCH-M, GARCH-M, Taylor-Schwert GARCH, GJR, TARCH, NARCH, APARCH, EGARCH) to analyze quarterly time...
Persistent link: https://www.econbiz.de/10012904559
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Realized copula
Fengler, Matthias R.; Okhrin, Ostap - 2012
We introduce the notion of realized copula. Based on assumptions of the marginal distributions of daily stock returns and a copula family, realized copula is defined as the copula structure materialized in realized covariance estimated from within-day high-frequency data. Copula parameters are...
Persistent link: https://www.econbiz.de/10010318779
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Realized copula
Fengler, Matthias R.; Okhrin, Ostap - 2012
We introduce the notion of realized copula. Based on assumptions of the marginal distributions of daily stock returns and a copula family, realized copula is defined as the copula structure materialized in realized covariance estimated from within-day high-frequency data. Copula parameters are...
Persistent link: https://www.econbiz.de/10009537332
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Penalized Adaptive Forecasting With Large Information Sets and Structural Changes
Zboňáková, Lenka - 2018
In the present paper we propose a new method, the Penalized Adaptive Method (PAM), for a data driven detection of structural changes in sparse linear models. The method is able to allocate the longest homogeneous intervals over the data sample and simultaneously choose the most proper variables...
Persistent link: https://www.econbiz.de/10012912415
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Time Series Properties of Arch Processes with Persistent Covariates
Han, Heejoon; Park, Joon - 2006
We consider ARCH processes with persistent covariates and provide asymptotic theories that explain how such covariates affect various characteristics of volatility. Specifically, we propose and study a volatility model, named ARCH-NNH model, that is an ARCH(1) process with a nonlinear function...
Persistent link: https://www.econbiz.de/10014054279
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Dynamics of Consumption and Dividends Over the Business Cycle
Pidkuyko, Myroslav - 2015
We examine a trivariate time series model that is subject to a regime switch, where the shifts are governed by an unobserved, two-state variable that follows a Markov process. The analysis is performed in a Bayesian framework developed by Albert and Chib (1993), where the unobserved states are...
Persistent link: https://www.econbiz.de/10013031069
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A persistence‐based Wold‐type decomposition for stationary time series
Ortu, Fulvio; Severino, Federico; Tamoni, Andrea; … - In: Quantitative economics : QE ; journal of the … 11 (2020) 1, pp. 203-230
This paper shows how to decompose weakly stationary time series into the sum, across time scales, of uncorrelated components associated with different degrees of persistence. In particular, we provide an Extended Wold Decomposition based on an isometric scaling operator that makes averages of...
Persistent link: https://www.econbiz.de/10012202240
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Automatic time series modeling and forecasting: a replication case study of forecasting real GDP, the unemployment rate and the impact of leading economic indicators
Guerard, John Baynard; Thomakos, Dimitrios D.; Kyriazi, … - In: Cogent economics & finance 8 (2020) 1, pp. 1-20
We test and report on time series modelling and forecasting using several US. Leading economic indicators (LEI) as an … input to forecasting real US. GDP and the unemployment rate. These time series have been addressed before, but our results … unemployment rate series. We tested the forecasting ability of best univariate and best bivariate models over 60- and 120-period …
Persistent link: https://www.econbiz.de/10012214684
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Toward a theory of evaluating predictive accuracy
Kunst, Robert M.; Jumah, Adusei - 2004
We suggest a theoretical basis for the comparative evaluation of forecasts. Instead of the general assumption that the data is generated from a stochastic model, we classify three stages of prediction experiments: pure non-stochastic prediction of given data, stochastic prediction of given data,...
Persistent link: https://www.econbiz.de/10010293709
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Google-haut Suomen asuntojen hintojen ennustajana
Widgrén, Joona - 2016
This report examines whether Google search queries can be used to predict the present and the near future house prices in Finland. Compared to a simple benchmark model, Google searches improve the prediction of the present house price index by 7.5 % measured by mean absolute error. In addition,...
Persistent link: https://www.econbiz.de/10012037683