D. Dijk

发表

Timing of Vote Decision in First and Second Order Dutch Elections 1978–1995: Evidence from Artificial Neural Networks

R. Eisinga, P. Franses, D. Dijk, 1998, Political Analysis.

Short patches of outliers, ARCH and volatility modelling

P. Franses, D. Dijk, A. Lucas, 2004 .

Forecasting stock market volatility using (non‐linear) Garch models

P. Franses, D. Dijk, 1996 .

Measuring volatility with the realized range

D. Dijk, M. Martens, 2006 .

Cointegration in a historical perspective

P. Franses, D. Dijk, D. Dijkvan, 2009 .

Panel Smooth Transition Regression Models

Yukai Yang, Timo Teräsvirta, Dick van Dijk, 2005 .

Forecasting the Yield Curve in a Data-Rich Environment Using the Factor-Augmented Nelson-Siegel Model: Yield Curve Forecasting using the Factor-Augmented Nelson-Siegel Model

P. Groenen, D. Dijk, Peter Exterkate, 2013 .

Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination

M. Medeiros, D. Dijk, T. Teräsvirta, 2005 .

The Loupe: tangible augmented reality for learning to look at Ancient Greek art

E. Hornecker, D. Dijk, I. Ruthven, 2016 .

Optimal Portfolios with Minimum Capital Requirements

F. Nogales, D. Dijk, E. Ruiz, 2010 .

Macroeconomic forecasting with matched principal components

P. Groenen, D. Dijk, C. Heij, 2008 .

Out-of-Sample Comparison of Copula Specifications in Multivariate Density Forecasts

D. Dijk, Dick J. C. van Dijk, C. Diks, 2008 .

A comparison of biased simulation schemes for stochastic volatility models

D. Dijk, R. Lord, R. Koekkoek, 2008 .

Forecasting Day-Ahead Electricity Prices: Utilizing Hourly Prices

D. Dijk, Dick J. C. van Dijk, Eran Raviv, 2013 .

The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production

Philip Hans Franses, Dick van Dijk, P. Franses, 2001 .

Nonlinear Time Series Analysis of Business Cycles (Contributions to Economic Analysis 276)

D. Dijk, C. Milas, P. Rothman, 2006 .

Forecasting returns and risk in financial markets using linear and nonlinear models

Michael P. Clements, Dick van Dijk, Costas Milas, 2009 .

The European directive on energy performance of buildings (EPBD)- The EPBD Building Platform

D. van Dijk, D. Dijk, 2008 .

Bayesian forecasting of federal funds target rate decisions

D. Dijk, R. Paap, Sjoerd van den Hauwe, 2013 .

A nonlinear long memory model, with an application to US unemployment ☆

Philip Hans Franses, Richard Paap, Dick van Dijk, 2002 .

Measuring and Predicting Heterogeneous Recessions

D. Dijk, Dick J. C. van Dijk, R. Paap, 2011 .

Nonlinear Time Series Models in Empirical Finance: Frontmatter

Philip Hans Franses, Dick van Dijk, P. Franses, 2000 .

Methanol from Natural Gas: Conceptual Design & Comparison of Processes

Dick van Dijk, H. C. van de Hulst, D. Dijk, 1995 .

Changes in International Business Cycle Affiliations

D. Osborn, D. Dijk, M. Sensier, 2009 .

Structural Breaks in the International Transmission of Inflation

D. Osborn, D. Dijk, M. Sensier, 2009 .

Forecasting Value-at-Risk under Temporal and Portfolio Aggregation*

A. Opschoor, D. Dijk, Thijs D. Markwat, 2017 .

Nonlinear forecasting with many predictors using kernel ridge regression

P. Groenen, D. Dijk, Peter Exterkate, 2016 .

Testing for changes in volatility in heteroskedastic time series - a further examination

D. Dijk, M. D. Pooter, 2004 .

Getting the most out of macroeconomic information for predicting excess stock returns

D. Dijk, C. Çakmaklı, 2016 .

Forecasting with Many Predictors: Allowing for Non-Linearity

D. Dijk, Eran Raviv, 2014 .

2 Changes in International Business Cycle Affiliations

D. Osborn, D. Dijk, M. Sensier, 2009 .

Quantitative Finance Out of Sample Performance of Factor Copulas

D. Dijk, Connor Cole, 2014 .

Forecasting the Business Cycle

D. Dijk, L. Ferrara, 2014 .

Macroeconomic forecasting with real-time data: an empirical comparison

Christiaan Heij, Dick van Dijk, Patrick J. F. Groenen, 2009 .

Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails

D. Dijk, C. Diks, V. Panchenko, 2008 .

A nonlinear long memory model for US unemployment

Philip Hans Franses, Richard Paap, Dick van Dijk, 2000 .

Does Africa grow slower than Asia, Latin America and the Middle East? Evidence from a new data-based classification method

P. Franses, D. Dijk, R. Paap, 2005 .

Does Africa grow slower than Asia and Latin America

Philip Hans Franses, Richard Paap, Dick van Dijk, 2003 .

Time Series Models for Business and Economic Forecasting

Philip Hans Franses, Dick van Dijk, Anne Opschoor, 1998 .

Smooth transition autoregressive models - A survey of recent developments

Timo Teräsvirta, Dick van Dijk, Philip Hans Franses, 2000 .

Smooth transition autoregressions , neural networks , and linear models in forecasting macroeconomic time series : A re-examination

Timo Teräsvirta, Marcelo C. Medeiros, Dick van Dijk, 2003 .

Sample size, lag order and critical values of seasonal unit root tests

Dick van Dijk, David I. Harvey, D. Dijk, 2006, Comput. Stat. Data Anal..

On the Effects of Private Information on Volatility

A. Opschoor, D. Dijk, N. Taylor, 2011 .

The Efiects of Central Bank Communications on Financial Markets

D. Dijk, B. Bierut, Milinha van Bleijswijk, 2007 .

Modeling asymmetric volatility in weekly Dutch temperature data

Philip Hans Franses, Dick van Dijk, Jack Neele, 1998, Environ. Model. Softw..

Do We Often Find ARCH Because Of Neglected Outliers

P. Franses, D. Dijk, 1997 .

Testing for ARCH in the presence of additive outliers

Andre Lucas, P. Franses, D. Dijk, 1999 .

Likelihood-based scoring rules for comparing density forecasts in tails

Dick van Dijk, Cees Diks, Valentyn Panchenko, 2011 .

Forecasting S&P 500 volatility: Long memory, level shifts, leverage effects, day-of-the-week seasonality, and macroeconomic announcements

Dick van Dijk, Michiel De Pooter, D. Dijk, 2009 .

Testing for Volatility Changes in U.S. Macroeconomic Time Series

Dick van Dijk, Marianne Sensier, D. Dijk, 2004, Review of Economics and Statistics.

The University of Manchester Discussion Paper Series Testing for Volatility Changes in US Macroeconomic Time Series

D. Dijk, M. Sensier, 2003 .

Changes in variability of the business cycle in the G7 countries

Dick van Dijk, Marianne Sensier, Denise R. Osborn, 2002 .

Short-term Volatility Versus Long-term Growth: Evidence in US Macroeconomic Time Series

D. Dijk, M. Sensier, 2001 .

Predicting the Daily Covariance Matrix for S&P 100 Stocks Using Intraday Data—But Which Frequency to Use?

D. Dijk, M. Martens, M. D. Pooter, 2008 .

Macroeconomic Crisis and Individual Firm Performance

D. Dijk, J. Spronk, K. Watkins, 2004 .

The euro introduction and noneuro currencies

D. Dijk, C. Hafner, Haris Munandar, 2011 .

Y 8 TZ Semi-Parametric Modelling of Correlation Dynamics

P. Franses, D. Dijk, C. Hafner, 2005 .

Integrating material and digital: a new way for cultural heritage

Albrecht Schmidt, Daniela Petrelli, Eva Hornecker, 2013, INTR.

Chapter 15 Bayesian Model Averaging in the Presence of Structural Breaks

P. Franses, D. Dijk, F. Ravazzolo, 2008 .

Does the absence of cointegration explain the typical findings in long horizon regressions

D. Dijk, R. Berben, 1998 .

Unit root tests and asymmetric adjustment - A reassessment

D. Dijk, R. Berben, 1999 .

Selecting a Nonlinear Time Series Model using Weighted Tests of Equal Forecast Accuracy

Philip Hans Franses, Dick van Dijk, P. Franses, 2003 .

GARCH, Outliers, and Forecasting Volatility

P. Franses, D. Dijk, 2011 .

Outlier detection in the GARCH (1,1) model

P. Franses, D. Dijk, 1999 .

Forecasting with Leading Indicators by means of the Principal Covariate Index

P. Groenen, D. Dijk, C. Heij, 2011 .

The Success Of Stock Selection Strategies In Emerging Markets: Is It Risk Or Behavioral Bias?

D. Dijk, G. Zwart, J. V. D. Hart, 2005 .

Stock Selection Strategies in Emerging Markets

Dick van Dijk, D. Dijk, Jaap van der Hart, 2003 .

Predictability of Stock Return and Volatility : A Factor Based Approach

D. Dijk, C. Çakmaklı, 2007 .

Weighted Likelihood Ratio Scores for Evaluating Density Forecasts in Tails ∗

D. Dijk, C. Diks, V. Panchenko, 2007 .

Weighted likelihood ratio scores for evaluating forecast densities in tails

D. Dijk, C. Diks, V. Panchenko, 2007 .

Financial Development and Convergence Clubs

D. Dijk, R. Paap, N. Basturk, 2010 .

Forecasting volatility with switching persistence GARCH models

P. Franses, D. Dijk, Jack Neele, 1998 .

Forecasting Day-Ahead Electricity Prices

Dick van Dijk, Eran Raviv, D. Dijk, 2013 .

How to Identify and Predict Bull and Bear Markets

D. Dijk, E. Kole, 2010 .

Statistical Research Unit Goteborg University Sweden Monitoring macroeconomic volatility

P. Franses, D. Dijk, D. Bock, 2011 .

Monitoring macroeconomic volatility

David Bock, Philip Hans Franses, Dick van Dijk, 2004 .

EN ISO 52016-1: The New International Standard To Calculate Building Energy Needs for Heating And Cooling, Internal Temperatures And Heating And Cooling Load

D. Dijk, 2019 .

The new EN ISO 52000 family of standards to assess the energy performance of buildings put in practice

Dick van Dijk, Jaap Hogeling, D. Dijk, 2019, E3S Web of Conferences.

Combining expert‐adjusted forecasts

Philip Hans Franses, Dick van Dijk, P. Franses, 2019, Journal of Forecasting.

Corporate Governance and Performance during the Aftermath of the 1994 Mexican Crisis

D. Dijk, J. Spronk, K. Watkins, 2006 .

Corporate governance and performance during normal and crisis periods: evidence from an emerging market perspective

D. Dijk, J. Spronk, K. Watkins, 2009 .

SMOOTH TRANSITION AUTOREGRESSIVE MODELS — A SURVEY OF RECENT DEVELOPMENTS

P. Franses, D. Dijk, T. Teräsvirta, 2002 .

Absorption of shocks in nonlinear autoregressive models

Philip Hans Franses, Dick van Dijk, H. P. Boswijk, 2007, Comput. Stat. Data Anal..

A multi‐level panel STAR model for US manufacturing sectors

Dennis Fok, Philip Hans Franses, Dick van Dijk, 2005 .

Forecasting aggregates using panels of nonlinear time series

Dennis Fok, Philip Hans Franses, Dick van Dijk, 2004 .

Forecasting industrial production with linear, nonlinear, and structural change models

Dick van Dijk, Boriss Siliverstovs, D. Dijk, 2003 .

Panel Smooth Transition Regression model and an application to investment under credit constraints

Dick van Dijk, D. Dijk, 2004 .

A multi-level panel smooth transition autoregression for US sectoral production

Dennis Fok, Philip Hans Franses, Dick van Dijk, 2003 .

SETS, arbitrage activity, and stock price dynamics

P. Franses, D. Dijk, A. Lucas, 2000 .

A Multivariate STAR Analysis of the Relationship Between Money and Output

Philip Hans Franses, Dick van Dijk, P. Franses, 1999 .

Modeling Multiple Regimes in the Business Cycle

Philip Hans Franses, Dick van Dijk, P. Franses, 1999, Macroeconomic Dynamics.

Nonlinear Error-Correction Models for Interest Rates in The Netherlands

P. Franses, D. Dijk, 1997 .

Testing for Smooth Transition Nonlinearity in the Presence of Outliers

Philip Hans Franses, Dick van Dijk, Andre Lucas, 1996 .

Erasmus University Erasmus School of Economics Pension De-Risking A Partial Buy-Out Solution

D. Dijk, Pension De-Risking, Tomas Reinders, 2017 .

Articulating Co-Design in Museums: Reflections on Two Participatory Processes

Nick Dulake, Mark T. Marshall, Gabriela Avram, 2016, CSCW.

Paul D. McNelis, Neural networks in finance—gaining predictive edge in the market

Dick van Dijk, D. Dijk, 2006 .

Forecasting Volatility with Copula-Based Time Series Models

D. Dijk, Oleg Sokolinskiy, 2011 .

Forecasting US Output Growth With Mixed Frequency Data

P. Franses, D. Dijk, Y. Ee, 2016 .

Range-based covariance estimation using high-frequency data: The realized co-range

Dick van Dijk, Karim Bannouh, D. Dijk, 2008 .

Realized Factor Models for Vast Dimensional Covariance Estimation

Dick van Dijk, Roel C. A. Oomen, Karim BannouhMartin Martens, 2009 .

Comparing the accuracy of multivariate density forecasts in selected regions of the copula support

D. Dijk, C. Diks, Oleg Sokolinskiy, 2014 .

MULTIVARIATE STAR ANALYSIS OF MONEY–OUTPUT RELATIONSHIP

Dick van Dijk, Philip Rothman, D. Dijk, 2001, Macroeconomic Dynamics.

Do private equity investors take firms private for different reasons

D. Dijk, J. Fidrmuc, Peter Roosenboom, 2006 .

Designing value to enable chronic disease management through information and communication technology: the People Value Canvas

D. Dijk, S. Wildevuur, A. Äyväri, 2016 .

Predicting Covariance Matrices with Financial Conditions Indexes

A. Opschoor, D. Dijk, M. V. D. Wel, 2013 .

Application of model combination to forecast the implied volatility surface

D. Dijk, W. Tham, 2016 .

Predicting growth regimes for European countries

D. Osborn, D. Dijk, M. Sensier, 2005 .

ON THE DYNAMICS OF BUSINESS CYCLE ANALYSIS: EDITORS' INTRODUCTION

H. V. Dijk, P. Franses, D. Dijk, 2005 .

Predicting Growth Cycle Regimes for European Countries

D. Osborn, D. Dijk, M. Sensier, 2003 .

Forecast comparison of principal component regression and principal covariate regression

Dick van Dijk, Patrick J. F. Groenen, Christiaan Heij, 2005, Comput. Stat. Data Anal..

Forthcoming in the Review of Economics and Statistics Structural Breaks in the International Dynamics of Inflation

D. Dijk, M. Sensier, Erdenebat Bataa, 2011 .

The Inefficient Use of Macroeconomic Information in Analysts' Earnings Forecasts in Emerging Markets

D. Dijk, G. Zwart, 2008 .

High-Frequency Activity on NASDAQ

D. Dijk, Martin L. Scholtus, 2015 .