Marcin Chlebus : Citation Profile

Are you Marcin Chlebus?

Uniwersytet Warszawski

2

H index

0

i10 index

9

Citations

RESEARCH PRODUCTION:

8

Articles

17

Papers

1

Chapters

RESEARCH ACTIVITY:

   7 years (2014 - 2021). See details.
   Cites by year: 1
   Journals where Marcin Chlebus has often published
   Relations with other researchers
   Recent citing documents: 4.    Total self citations: 6 (40 %)

MORE DETAILS IN:
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   Permalink: http://citec.repec.org/pch1469
   Updated: 2024-01-16    RAS profile: 2022-12-05    
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Relations with other researchers

Works with:

Woźniak, Michał (3)

Buczyński, 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:

Ślepaczuk, Robert (2)

Parra-Amado, Daniel (1)

Murphy, David (1)

Melo-Velandia, Luis (1)

Bee, Marco (1)

Cites to:

Engle, Robert (25)

Jimenez-Martin, Juan (16)

Bollerslev, Tim (15)

Manganelli, Simone (12)

Pérez-Amaral, Teodosio (12)

Degiannakis, Stavros (11)

Angelidis, Timotheos (7)

Kupiec, Paul (6)

Rose, Andrew (5)

Frankel, Jeffrey (5)

Alexander, Carol (4)

Main data

Where Marcin Chlebus has published?

Journals with more than one article published# docs
Central European Economic Journal5

Working Papers Series with more than one paper published# docs
Working Papers / Faculty of Economic Sciences, University of Warsaw16

Recent works citing Marcin Chlebus (2024 and 2023)

YearTitle of citing document
2023A Comprehensive Survey on Enterprise Financial Risk Analysis: Problems, Methods, Spotlights and Applications. (2022). Du, Huaming ; Zhao, YU. In: Papers. RePEc:arx:papers:2211.14997.

Full description at Econpapers || Download paper

2023Forecasting Value-at-Risk using functional volatility incorporating an exogenous effect. (2023). Bee, Marco ; Tafakori, Laleh ; Pourkhanali, Armin. In: International Review of Financial Analysis. RePEc:eee:finana:v:89:y:2023:i:c:s1057521923003198.

Full description at Econpapers || Download paper

2023The performance of time series forecasting based on classical and machine learning methods for S&P 500 index. (2023). Lepaczuk, Robert ; Uzzal, Maudud Hassan. In: Working Papers. RePEc:war:wpaper:2023-05.

Full description at Econpapers || Download paper

2023Ensembled LSTM with Walk Forward Optimization in Algorithmic Trading. (2023). Ślepaczuk, Robert ; Chojnacki, Karol. In: Working Papers. RePEc:war:wpaper:2023-15.

Full description at Econpapers || Download paper

Works by Marcin Chlebus:

YearTitleTypeCited
In: .
[Full Text][Citation analysis]		chapter0
2021Enabling Machine Learning Algorithms for Credit Scoring -- Explainable Artificial Intelligence (XAI) methods for clear understanding complex predictive models In: Papers.
[Full Text][Citation analysis]		paper2
2014One-day prediction of state of turbulence for financial instrument based on models for binary dependent variable In: Ekonomia journal.
[Full Text][Citation analysis]		article0
2018One-day-ahead forecast of state of turbulence based on todays economic situation In: Equilibrium. Quarterly Journal of Economics and Economic Policy.
[Full Text][Citation analysis]		article0
2017EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk In: Central European Economic Journal.
[Full Text][Citation analysis]		article1
2016EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk.(2016) In: Working Papers.
[Full Text][Citation analysis]
This paper has nother version. Agregated cites: 1		paper
2019Comparison of Block Maxima and Peaks Over Threshold Value-at-Risk models for market risk in various economic conditions In: Central European Economic Journal.
[Full Text][Citation analysis]		article1
2019Comparison of Block Maxima and Peaks Over Threshold Value-at-Risk models for market risk in various economic conditions.(2019) In: Central European Economic Journal.
[Full Text][Citation analysis]
This paper has nother version. Agregated cites: 1		article
2020Ridesharing in the Polish Experience: A Study using Unified Theory of Acceptance and Use of Technology In: Central European Economic Journal.
[Full Text][Citation analysis]		article0
2021Nvidias Stock Returns Prediction Using Machine Learning Techniques for Time Series Forecasting Problem In: Central European Economic Journal.
[Full Text][Citation analysis]		article2
2020Nvidia’s stock returns prediction using machine learning techniques for time series forecasting problem.(2020) In: Working Papers.
[Full Text][Citation analysis]
This paper has nother version. Agregated cites: 2		paper
In: .
[Full Text][Citation analysis]		article0
2016One-Day Prediction of State of Turbulence for Portfolio. Models for Binary Dependent Variable In: Working Papers.
[Full Text][Citation analysis]		paper1
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.
[Full Text][Citation analysis]		paper0
2019Old-fashioned parametric models are still the best. A comparison of Value-at-Risk approaches in several volatility states. In: Working Papers.
[Full Text][Citation analysis]		paper1
2020Comparison of tree-based models performance in prediction of marketing campaign results using Explainable Artificial Intelligence tools In: Working Papers.
[Full Text][Citation analysis]		paper0
2020So close and so far. Finding similar tendencies in econometrics and machine learning papers. Topic models comparison. In: Working Papers.
[Full Text][Citation analysis]		paper0
2020Towards better understanding of complex machine learning models using Explainable Artificial Intelligence (XAI) - case of Credit Scoring modelling In: Working Papers.
[Full Text][Citation analysis]		paper0
2020HRP performance comparison in portfolio optimization under various codependence and distance metrics In: Working Papers.
[Full Text][Citation analysis]		paper0
2020Impact of using industry benchmark financial ratios on performance of bankruptcy prediction logistic regression model In: Working Papers.
[Full Text][Citation analysis]		paper0
2021GARCHNet - Value-at-Risk forecasting with novel approach to GARCH models based on neural networks In: Working Papers.
[Full Text][Citation analysis]		paper0
2021HCR & HCR-GARCH – novel statistical learning models for Value at Risk estimation In: Working Papers.
[Full Text][Citation analysis]		paper0
2021Comparison of the accuracy in VaR forecasting for commodities using different methods of combining forecasts In: Working Papers.
[Full Text][Citation analysis]		paper0
2021Machine learning in the prediction of flat horse racing results in Poland In: Working Papers.
[Full Text][Citation analysis]		paper0
2021Predicting football outcomes from Spanish league using machine learning models In: Working Papers.
[Full Text][Citation analysis]		paper0
2021The effectiveness of Value-at-Risk models in various volatility regimes In: Working Papers.
[Full Text][Citation analysis]		paper1

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