Philippe du Jardin : Citation Profile


Are you Philippe du Jardin?

Groupe EDHEC (École de Hautes Études Commerciales du Nord)

7

H index

6

i10 index

187

Citations

RESEARCH PRODUCTION:

6

Articles

11

Papers

RESEARCH ACTIVITY:

   13 years (2008 - 2021). See details.
   Cites by year: 14
   Journals where Philippe du Jardin has often published
   Relations with other researchers
   Recent citing documents: 22.    Total self citations: 5 (2.6 %)

MORE DETAILS IN:
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   Permalink: http://citec.repec.org/pdu253
   Updated: 2024-04-18    RAS profile: 2022-07-11    
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Relations with other researchers


Works with:

Authors registered in RePEc who have co-authored more than one work in the last five years with Philippe du Jardin.

Is cited by:

BEN JABEUR, SAMI (4)

Restaino, Marialuisa (2)

Silva, Pedro (2)

Alam, Md. Mahmudul (2)

Gutiérrez-Nieto, Begoña (2)

PRUSAK, BŁAŻEJ (2)

Lee, King Fuei (2)

HENTATI KAFFEL, Rania (2)

Muga, Luis (2)

METAXAS, THEODORE (1)

Mirbagherijam, Mohammad (1)

Cites to:

Altman, Edward (33)

Ooghe, Hubert (8)

Lensberg, Terje (5)

Peel, Michael (3)

PSILLAKI, Maria (2)

Silva, Pedro (1)

Gaubert, Patrice (1)

Barth, James (1)

Bergstresser, Daniel (1)

Wu, Yanrui (1)

Chava, Sudheer (1)

Main data


Where Philippe du Jardin has published?


Journals with more than one article published# docs
European Journal of Operational Research4

Working Papers Series with more than one paper published# docs
MPRA Paper / University Library of Munich, Germany8
Post-Print / HAL3

Recent works citing Philippe du Jardin (2024 and 2023)


YearTitle of citing document
2023A transformer-based model for default prediction in mid-cap corporate markets. (2021). Bravo, Cristi'An ; Mues, Christophe ; Korangi, Kamesh. In: Papers. RePEc:arx:papers:2111.09902.

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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.

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2023.

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2023Extending business failure prediction models with textual website content using deep learning. (2023). de Weerdt, Jochen ; de Caigny, Arno ; Coussement, Kristof ; Borchert, Philipp. In: European Journal of Operational Research. RePEc:eee:ejores:v:306:y:2023:i:1:p:348-357.

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2023A transformer-based model for default prediction in mid-cap corporate markets. (2023). Bravo, Cristian ; Mues, Christophe ; Korangi, Kamesh. In: European Journal of Operational Research. RePEc:eee:ejores:v:308:y:2023:i:1:p:306-320.

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2023Predicting financial distress of Chinese listed companies using machine learning: To what extent does textual disclosure matter?. (2023). Ji, Yucheng ; Xu, Weijun ; Zhao, QI. In: International Review of Financial Analysis. RePEc:eee:finana:v:89:y:2023:i:c:s1057521923002867.

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2023Influence of earnings management on forecasting corporate failure. (2023). Chlibi, Souhir ; Severin, Eric ; Veganzones, David. In: International Journal of Forecasting. RePEc:eee:intfor:v:39:y:2023:i:1:p:123-143.

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2023Bankruptcy prediction using fuzzy convolutional neural networks. (2023). Serret, Vanessa ; ben Jabeur, Sami. In: Research in International Business and Finance. RePEc:eee:riibaf:v:64:y:2023:i:c:s0275531922002306.

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2023A Literature Review on the Financial Determinants of Hotel Default. (2023). METAXAS, THEODORE ; Romanopoulos, Athanasios. In: JRFM. RePEc:gam:jjrfmx:v:16:y:2023:i:7:p:323-:d:1188400.

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2023Domain Knowledge Features versus LASSO Features in Predicting Risk of Corporate Bankruptcy—DEA Approach. (2023). Horvathova, Jarmila ; Mokriova, Martina. In: Risks. RePEc:gam:jrisks:v:11:y:2023:i:11:p:199-:d:1280888.

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2023Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering. (2023). Carmona, Pedro ; Stef, Nicolae ; ben Jabeur, Sami. In: Computational Economics. RePEc:kap:compec:v:61:y:2023:i:2:d:10.1007_s10614-021-10227-1.

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2023Role of Comprehensive Income in Predicting Bankruptcy. (2023). Tsai, Chih-Fong ; Novitasari, Dinda ; Liang, Deron ; Lu, Hung-Yuan ; Rahmi, Asyrofa. In: Computational Economics. RePEc:kap:compec:v:62:y:2023:i:2:d:10.1007_s10614-022-10328-5.

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2023Bank failure prediction: corporate governance and financial indicators. (2023). Yazdifar, Hassan ; Eskandari, Rasol ; Alzayed, Noora. In: Review of Quantitative Finance and Accounting. RePEc:kap:rqfnac:v:61:y:2023:i:2:d:10.1007_s11156-023-01158-z.

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2023Növelhető-e a csőd-előrejelző modellek előre jelző képessége az új klasszifikációs módszerek nélkül?. (2014). Nyitrai, Tamas . In: Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences). RePEc:ksa:szemle:1480.

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2023Magyar vállalkozások felszámolásának előrejelzése pénzügyi mutatóik idősorai alapján. (2017). Virag, Miklos ; Nyitrai, Tamas . In: Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences). RePEc:ksa:szemle:1684.

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2023Designing topological data to forecast bankruptcy using convolutional neural networks. (2023). Jardin, Philippe. In: Annals of Operations Research. RePEc:spr:annopr:v:325:y:2023:i:2:d:10.1007_s10479-022-04780-7.

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2023A dynamic performance evaluation of distress prediction models. (2023). Tone, Kaoru ; Ouenniche, Jamal ; Mousavi, Mohammad Mahdi. In: Journal of Forecasting. RePEc:wly:jforec:v:42:y:2023:i:4:p:756-784.

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Works by Philippe du Jardin:


YearTitleTypeCited
2012Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time In: European Journal of Operational Research.
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article23
2012Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time.(2012) In: MPRA Paper.
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This paper has nother version. Agregated cites: 23
paper
2015Bankruptcy prediction using terminal failure processes In: European Journal of Operational Research.
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article35
2016A two-stage classification technique for bankruptcy prediction In: European Journal of Operational Research.
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article28
2021Forecasting corporate failure using ensemble of self-organizing neural networks In: European Journal of Operational Research.
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article3
2012Forecasting financial failure using a Kohonen map: a comparative study to improve bankruptcy model over time In: Post-Print.
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paper21
2011Predicting Corporate Bankruptcy Using Self-Organising map: An empirical study to Improve the Forecasting horizon of financial failure model In: Post-Print.
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paper18
2011Predicting corporate bankruptcy using a self-organizing map: An empirical study to improve the forecasting horizon of a financial failure model.(2011) In: MPRA Paper.
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This paper has nother version. Agregated cites: 18
paper
2011Dividend policy In: Post-Print.
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paper9
2011Dividend policy.(2011) In: MPRA Paper.
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This paper has nother version. Agregated cites: 9
paper
2019Forecasting Corporate Bankruptcy Using Accrual-Based Models In: Computational Economics.
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article6
2010Predicting bankruptcy using neural networks and other classification methods: the influence of variable selection techniques on model accuracy In: MPRA Paper.
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paper28
2010Dynamic analysis of the business failure process: A study of bankruptcy trajectories In: MPRA Paper.
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paper2
2009Bankruptcy prediction models: How to choose the most relevant variables? In: MPRA Paper.
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paper7
2012The influence of variable selection methods on the accuracy of bankruptcy prediction models In: MPRA Paper.
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paper3
2008Bankruptcy prediction and neural networks: The contribution of variable selection methods In: MPRA Paper.
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paper0
2021Forecasting bankruptcy using biclustering and neural network-based ensembles In: Annals of Operations Research.
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article4

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