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Details about Tamas Kiss

Homepage:https://sites.google.com/site/kisstamaass
Phone:00 46 19 30 03 26
Workplace:Handelshögskolan (Business School), Örebro Universitet (Örebro University), (more information at EDIRC)

Access statistics for papers by Tamas Kiss.

Last updated 2024-11-08. Update your information in the RePEc Author Service.

Short-id: pki585


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Working Papers

2024

  1. US Interest Rates: Are Relations Stable?
    Working Papers, Örebro University, School of Business Downloads
  2. VAR Models with Fat Tails and Dynamic Asymmetry
    Working Papers, Örebro University, School of Business Downloads

2023

  1. Market Participants or the Random Walk – Who Forecasts Better? Evidence from Micro Level Survey Data
    Working Papers, Örebro University, School of Business Downloads
    See also Journal Article Market participants or the random walk – who forecasts better? Evidence from micro-level survey data, Finance Research Letters, Elsevier (2023) Downloads (2023)

2022

  1. Modelling Okun’s Law – Does non-Gaussianity Matter?
    Working Papers, Örebro University, School of Business Downloads
    See also Journal Article Modelling Okun’s law: Does non-Gaussianity matter?, Empirical Economics, Springer (2023) Downloads (2023)
  2. Varför har arbetstagar- och arbetsgivarorganisationer olika förväntningar om lönetillväxt?
    Working Papers, Örebro University, School of Business Downloads

2021

  1. Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances
    Working Papers, Örebro University, School of Business Downloads
    See also Journal Article Modeling the relation between the US real economy and the corporate bond‐yield spread in Bayesian VARs with non‐Gaussian innovations, Journal of Forecasting, John Wiley & Sons, Ltd. (2023) Downloads (2023)
  2. Predicting returns and dividend growth - the role of non-Gaussian innovations
    Working Papers, Örebro University, School of Business Downloads
    See also Journal Article Predicting returns and dividend growth — The role of non-Gaussian innovations, Finance Research Letters, Elsevier (2022) Downloads View citations (1) (2022)

2020

  1. Corona, Crisis and Conditional Heteroscedasticity
    Working Papers, Örebro University, School of Business Downloads
    See also Journal Article Corona, crisis and conditional heteroscedasticity, Applied Economics Letters, Taylor & Francis Journals (2021) Downloads View citations (1) (2021)
  2. Modelling Returns in US Housing Prices – You’re the One for Me, Fat Tails
    Working Papers, Örebro University, School of Business Downloads
    See also Journal Article Modelling Returns in US Housing Prices—You’re the One for Me, Fat Tails, JRFM, MDPI (2021) Downloads (2021)

2019

  1. Testing Return Predictability with the Dividend-Growth Equation: An Anatomy of the Dog
    Working Papers in Economics, University of Gothenburg, Department of Economics Downloads

Journal Articles

2023

  1. Market participants or the random walk – who forecasts better? Evidence from micro-level survey data
    Finance Research Letters, 2023, 54, (C) Downloads
    See also Working Paper Market Participants or the Random Walk – Who Forecasts Better? Evidence from Micro Level Survey Data, Working Papers (2023) Downloads (2023)
  2. Modeling the relation between the US real economy and the corporate bond‐yield spread in Bayesian VARs with non‐Gaussian innovations
    Journal of Forecasting, 2023, 42, (2), 347-368 Downloads
    See also Working Paper Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances, Working Papers (2021) Downloads (2021)
  3. Modelling Okun’s law: Does non-Gaussianity matter?
    Empirical Economics, 2023, 64, (5), 2183-2213 Downloads
    See also Working Paper Modelling Okun’s Law – Does non-Gaussianity Matter?, Working Papers (2022) Downloads (2022)

2022

  1. Long‐run predictability tests are even worse than you thought
    Journal of Applied Econometrics, 2022, 37, (7), 1334-1355 Downloads View citations (1)
  2. Performance analysis of nowcasting of GDP growth when allowing for conditional heteroscedasticity and non-Gaussianity
    Applied Economics, 2022, 54, (58), 6669-6686 Downloads
  3. Predicting returns and dividend growth — The role of non-Gaussian innovations
    Finance Research Letters, 2022, 46, (PA) Downloads View citations (1)
    See also Working Paper Predicting returns and dividend growth - the role of non-Gaussian innovations, Working Papers (2021) Downloads (2021)
  4. The Relation between the High-Yield Bond Spread and the Unemployment Rate in the Euro Area
    Finance Research Letters, 2022, 46, (PA) Downloads

2021

  1. Corona, crisis and conditional heteroscedasticity
    Applied Economics Letters, 2021, 28, (9), 755-759 Downloads View citations (1)
    See also Working Paper Corona, Crisis and Conditional Heteroscedasticity, Working Papers (2020) Downloads (2020)
  2. Modelling Returns in US Housing Prices—You’re the One for Me, Fat Tails
    JRFM, 2021, 14, (11), 1-17 Downloads
    See also Working Paper Modelling Returns in US Housing Prices – You’re the One for Me, Fat Tails, Working Papers (2020) Downloads (2020)

2020

  1. Fat tails in leading indicators
    Economics Letters, 2020, 193, (C) Downloads View citations (9)

2013

  1. Developments in public debt in Hungary between 1998 and 2012: trends, reasons and effects
    MNB Bulletin (discontinued), 2013, 8, (Special), 14-22 Downloads View citations (2)
 
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