Marcin Chlebus : Citation Profile


Are you Marcin Chlebus?

Uniwersytet Warszawski

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Citations

RESEARCH PRODUCTION:

3

Articles

4

Papers

RESEARCH ACTIVITY:

   4 years (2014 - 2018). See details.
   Cites by year: 0
   Journals where Marcin Chlebus has often published
   Relations with other researchers
   Recent citing documents: 0.    Total self citations: 2 (0 %)

MORE DETAILS IN:
ABOUT THIS REPORT:

   Permalink: http://citec.repec.org/pch1469
   Updated: 2020-05-16    RAS profile: 2019-09-11    
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Relations with other researchers


Works with:

BuczyƄski, Mateusz (2)

Authors registered in RePEc who have co-authored more than one work in the last five years with Marcin Chlebus.

Is cited by:

Cites to:

Frankel, Jeffrey (5)

Rose, Andrew (5)

McAleer, Michael (4)

Jimenez-Martin, Juan (4)

Engle, Robert (4)

Angelidis, Timotheos (3)

Bollerslev, Tim (3)

Degiannakis, Stavros (3)

perez-amaral, teodosio (3)

Bussiere, Matthieu (2)

Reinhart, Carmen (2)

Main data


Where Marcin Chlebus has published?


Working Papers Series with more than one paper published# docs
Working Papers / Faculty of Economic Sciences, University of Warsaw4

Recent works citing Marcin Chlebus (2019 and 2018)


YearTitle of citing document

Works by Marcin Chlebus:


YearTitleTypeCited
2014One-day prediction of state of turbulence for financial instrument based on models for binary dependent variable In: Ekonomia journal.
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2018One-day-ahead forecast of state of turbulence based on todays economic situation In: Equilibrium. Quarterly Journal of Economics and Economic Policy.
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2017EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk In: Central European Economic Journal.
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2016EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk.(2016) In: Working Papers.
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This paper has another version. Agregated cites: 0
paper
2016One-Day Prediction of State of Turbulence for Portfolio. Models for Binary Dependent Variable In: Working Papers.
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2017Is CAViaR model really so good in Value at Risk forecasting? Evidence from evaluation of a quality of Value-at-Risk forecasts obtained based on the: GARCH(1,1), GARCH-t(1,1), GARCH-st(1,1), QML-GARCH( In: Working Papers.
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2019Old-fashioned parametric models are still the best. A comparison of Value-at-Risk approaches in several volatility states. In: Working Papers.
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