1
H index
0
i10 index
4
Citations
Uniwersytet Warszawski | 1 H index 0 i10 index 4 Citations RESEARCH PRODUCTION: 8 Articles 17 Papers 1 Chapters RESEARCH ACTIVITY:
MORE DETAILS IN: ABOUT THIS REPORT:
|
Works with: 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: |
Journals with more than one article published | # docs |
---|---|
Central European Economic Journal | 5 |
Working Papers Series with more than one paper published | # docs |
---|---|
Working Papers / Faculty of Economic Sciences, University of Warsaw | 16 |
Year | Title of citing document |
---|---|
2022 | Extreme weather events and high Colombian food prices: A non-stationary extreme value approach. (2022). Parra-Amado, Daniel ; Orozco-Vanegas, Camilo Andres ; Melo-Velandia, Luis Fernando. In: Borradores de Economia. RePEc:bdr:borrec:1189. Full description at Econpapers || Download paper |
2021 | A CBA of APC: analysing approaches to procyclicality reduction in CCP initial margin models. (2021). Murphy, David ; Vause, Nicholas. In: Bank of England working papers. RePEc:boe:boeewp:0950. Full description at Econpapers || Download paper |
Year | Title | Type | Cited |
---|---|---|---|
In: . [Full Text][Citation analysis] | chapter | 0 | |
2021 | Enabling Machine Learning Algorithms for Credit Scoring -- Explainable Artificial Intelligence (XAI) methods for clear understanding complex predictive models In: Papers. [Full Text][Citation analysis] | paper | 0 |
2014 | One-day prediction of state of turbulence for financial instrument based on models for binary dependent variable In: Ekonomia journal. [Full Text][Citation analysis] | article | 0 |
2018 | One-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] | article | 0 |
2017 | EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk In: Central European Economic Journal. [Full Text][Citation analysis] | article | 1 |
2016 | EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk.(2016) In: Working Papers. [Full Text][Citation analysis] This paper has another version. Agregated cites: 1 | paper | |
2019 | Comparison 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] | article | 1 |
2019 | Comparison 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 another version. Agregated cites: 1 | article | |
2020 | Ridesharing in the Polish Experience: A Study using Unified Theory of Acceptance and Use of Technology In: Central European Economic Journal. [Full Text][Citation analysis] | article | 0 |
2021 | Nvidias Stock Returns Prediction Using Machine Learning Techniques for Time Series Forecasting Problem In: Central European Economic Journal. [Full Text][Citation analysis] | article | 0 |
2020 | Nvidia’s stock returns prediction using machine learning techniques for time series forecasting problem.(2020) In: Working Papers. [Full Text][Citation analysis] This paper has another version. Agregated cites: 0 | paper | |
In: . [Full Text][Citation analysis] | article | 0 | |
2016 | One-Day Prediction of State of Turbulence for Portfolio. Models for Binary Dependent Variable In: Working Papers. [Full Text][Citation analysis] | paper | 1 |
2017 | Is 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] | paper | 0 |
2019 | Old-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] | paper | 1 |
2020 | Comparison of tree-based models performance in prediction of marketing campaign results using Explainable Artificial Intelligence tools In: Working Papers. [Full Text][Citation analysis] | paper | 0 |
2020 | So close and so far. Finding similar tendencies in econometrics and machine learning papers. Topic models comparison. In: Working Papers. [Full Text][Citation analysis] | paper | 0 |
2020 | Towards better understanding of complex machine learning models using Explainable Artificial Intelligence (XAI) - case of Credit Scoring modelling In: Working Papers. [Full Text][Citation analysis] | paper | 0 |
2020 | HRP performance comparison in portfolio optimization under various codependence and distance metrics In: Working Papers. [Full Text][Citation analysis] | paper | 0 |
2020 | Impact of using industry benchmark financial ratios on performance of bankruptcy prediction logistic regression model In: Working Papers. [Full Text][Citation analysis] | paper | 0 |
2021 | GARCHNet - Value-at-Risk forecasting with novel approach to GARCH models based on neural networks In: Working Papers. [Full Text][Citation analysis] | paper | 0 |
2021 | HCR & HCR-GARCH – novel statistical learning models for Value at Risk estimation In: Working Papers. [Full Text][Citation analysis] | paper | 0 |
2021 | Comparison of the accuracy in VaR forecasting for commodities using different methods of combining forecasts In: Working Papers. [Full Text][Citation analysis] | paper | 0 |
2021 | Machine learning in the prediction of flat horse racing results in Poland In: Working Papers. [Full Text][Citation analysis] | paper | 0 |
2021 | Predicting football outcomes from Spanish league using machine learning models In: Working Papers. [Full Text][Citation analysis] | paper | 0 |
2021 | The effectiveness of Value-at-Risk models in various volatility regimes In: Working Papers. [Full Text][Citation analysis] | paper | 0 |
CitEc is a RePEc service, providing citation data for Economics since 2001. Sponsored by INOMICS. Last updated April, 29 2023. Contact: CitEc Team