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Year of publication
Subject
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Mustererkennung 307 Pattern recognition 307 Theorie 106 Theory 105 Forecasting model 87 Prognoseverfahren 87 pattern recognition 58 USA 56 United States 56 Kreditwürdigkeit 51 Credit rating 49 Neural networks 38 Neuronale Netze 34 Insolvenz 33 Data mining 32 Insolvency 32 Data Mining 31 Künstliche Intelligenz 25 Artificial intelligence 22 Pattern Recognition 19 support vector machine 18 Classification 17 Estimation 17 Klassifikation 17 Schätzung 17 Support vector machine 17 machine learning 17 Deutschland 14 Germany 14 Cluster analysis 13 Clusteranalyse 13 Algorithmus 12 Learning 12 Algorithm 11 Credit risk 11 Evolutionary algorithm 11 Evolutionärer Algorithmus 11 Kreditrisiko 11 Regression analysis 11 Regressionsanalyse 11
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Online availability
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Undetermined 135 Free 106
Type of publication
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Article 276 Book / Working Paper 154 Other 2 Journal 1
Type of publication (narrower categories)
All
Article in journal 168 Aufsatz in Zeitschrift 168 Working Paper 45 Graue Literatur 44 Non-commercial literature 44 Arbeitspapier 41 Aufsatz im Buch 38 Book section 38 Hochschulschrift 23 Thesis 17 Konferenzschrift 8 Article 6 Dissertation u.a. Prüfungsschriften 5 Case study 3 Collection of articles of several authors 3 Collection of articles written by one author 3 Conference paper 3 Fallstudie 3 Konferenzbeitrag 3 Sammelwerk 3 Sammlung 3 Guidebook 2 Ratgeber 2 Aufsatzsammlung 1 Congress Report 1 Interview 1 Konferenzschrift/Kongressbericht 1 Report 1
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Language
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English 315 Undetermined 73 German 44 Italian 1 Romanian 1 Spanish 1
Author
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Härdle, Wolfgang 17 Schäfer, Dorothea 9 Papadimitriou, Theophilos 8 Gkonkas, Periklēs 6 Moro, Rouslan 6 Vojtek, Martin 6 Härdle, Wolfgang K. 5 Moro, Rouslan A. 5 Brighton, Henry 4 Chen, Shiyi 4 Lee, Yuh-Jye 4 León, Carlos 4 Plakandaras, Vasilios 4 Yeh, Yi-Ren 4 Abedin, Mohammad Zoynul 3 Bioch, Jan C. 3 Bruno, Odemir M. 3 Chi, Guotai 3 Farhat, Daniel 3 Gao, Guangyuan 3 Groenen, Patrick J. F. 3 Hoffmann, Linda 3 Jeong, Kiho 3 Lange, Tatjana 3 Mosler, Karl 3 Moula, Fahmida E. 3 Mozharovskyi, Pavlo 3 Schaefer, Dorothea 3 Spiliopoulos, Leonidas 3 Wüthrich, Mario V. 3 Acero, Oscar 2 Adebiyi, Kazeem Adekunle 2 Aguiar, Javier M. 2 Aliakbari, Saeideh 2 Atichat, Tanawat 2 Auria, Laura 2 Bai, Junjie 2 Baladrón, Carlos 2 Barucca, Paolo 2 Berg, Kristi 2
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Institution
All
Deutsche Arbeitsgemeinschaft für Mustererkennung 3 Department of Economics, University of Victoria 2 CESifo 1 Christian-Albrechts-Universität zu Kiel 1 Department of Economics and Business, Universitat Pompeu Fabra 1 Deutsche Bundesbank 1 Deutsches Institut für Wirtschaftsforschung 1 Dr. Rainer Hampp <Firma> 1 Fachbereich Rechts- und Wirtschaftswissenschaften, Technische Universität Darmstadt 1 Faculteit Economie en Bedrijfskunde, Universiteit Gent 1 Fraunhofer IRB-Verlag 1 Fraunhofer-Institut für Experimentelles Software Engineering 1 Gesellschaft für Informatik 1 IGI Global 1 International Symposium on Synergetics <1979, Elmau> 1 Joint Workshop on Pattern Recognition and Artificial Intelligence <1976, Hyannis, Mass.> 1 Kassel University Press GmbH 1 Konjunkturinstitutet, Government of Sweden 1 National Centre for Econometric Research (NCER) 1 Provozně ekonomická fakulta, Mendelova Univerzita v Brnĕ 1 Seminar für Wirtschafts- und Sozialstatistik, Wirtschafts- und Sozialwissenschaftliche Fakultät 1 Springer International Publishing 1 Universität Bremen 1 Verband der Wissenschaftlichen Gesellschaften Österreichs 1 Verlag C.H. Beck 1 Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München 1 William Davidson Institute, University of Michigan 1 Würzburg University Press 1 Österreichische Computer-Gesellschaft / Arbeitskreis für Mustererkennung 1
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Published in...
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Physica A: Statistical Mechanics and its Applications 13 SFB 649 discussion paper 10 European journal of operational research : EJOR 7 International journal of production research 7 Journal of forecasting 6 Knowledge and information systems : an international journal 6 Computational economics 5 Mathematics and Computers in Simulation (MATCOM) 5 Technical report / Sonderforschungsbereich 475 Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund 5 Applied optimization and data mining : dedicated to Dr. Panos Pardalos on the occasion of his 60th birthday 4 Decision support systems : DSS ; the international journal 4 Informatik-Fachberichte 4 DIW-Wochenbericht : Wirtschaft, Politik, Wissenschaft 3 Discussion papers / Deutsches Institut für Wirtschaftsforschung 3 Econometric Institute research papers 3 Fuzzy optimization and decision making : a journal of modeling and computation under uncertainty 3 International journal of business information systems : IJBIS 3 International journal of economics and finance 3 International journal of production economics 3 Journal of Classification 3 Journal of risk and financial management : JRFM 3 4OR : quarterly journal of the Belgian, French and Italian Operations Research Societies 2 Advances in knowledge acquisition, transfer, and management (AKATM) book series 2 Betriebswirtschaftliche Schriften zur Unternehmensführung 2 Classification - the ubiquitous challenge : proceedings of the 28th annual conference of the Gesellschaft für Klassifikation e.V., University of Dortmund, March 9 - 11, 2004 ; with 108 tables 2 Communication and cybernetics 2 Computational Management Science : CMS 2 Computers & operations research : and their applications to problems of world concern ; an international journal 2 Darmstadt Discussion Papers in Economics 2 Decision Analytics 2 Dissertationen der Johannes-Kepler-Universität Linz 2 E-technologies: transformation in a connected world : 5th international conference, MCETECH 2011, Les Diablerets, Switzerland, January 23 - 26, 2011 ; revised selected papers 2 Econometrics Working Papers 2 Economics discussion papers 2 Electronic commerce research and applications 2 Emerging markets finance & trade : a journal of the Society for the Study of Emerging Markets 2 Energy economics 2 Enterprise information systems : 12th International Conference, ICEIS 2010, Funchal-Madeira, Portugal, June 8-12, 2010, Revised Selected Papers 2 Faculty & research / Insead : working paper series 2 Financial innovation : FIN 2
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Source
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ECONIS (ZBW) 301 RePEc 62 USB Cologne (EcoSocSci) 39 Other ZBW resources 13 EconStor 10 BASE 8
Showing 1 - 50 of 433
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The applications of artificial neural networks, support vector machines, and long-short term memory for stock market prediction
Chhajer, Parshv; Shah, Manan; Kshirsagar, Ameya - In: Decision analytics journal 2 (2022)
The future is unknown and uncertain, but there are ways to predict future events and reap the rewards safely. One such opportunity is the application of machine learning and artificial intelligence for stock market prediction. The stock market is turbulent, yet using artificial intelligence to...
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Bankruptcy prediction using machine learning techniques
Shetty, Shekar; Musa, Mohamed; Brédart, Xavier - In: Journal of risk and financial management : JRFM 15 (2022) 1, pp. 1-10
In this study, we apply several advanced machine learning techniques including extreme gradient boosting (XGBoost), support vector machine (SVM), and a deep neural network to predict bankruptcy using easily obtainable financial data of 3728 Belgian Small and Medium Enterprises (SME’s) during...
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Explainable Artificial Intelligence: Analyse und Visualisierung des Lernprozesses eines Convolutional Neural Network zur Erkennung deutscher Straßenverkehrsschilder
Maasjosthusmann, Robin; Lehrbass, Frank - 2021
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Bankruptcy prediction of small- and medium-sized enterprises in Poland based on the LDA and SVM methods
Ptak-Chmielewska, Aneta - In: Statistics in transition : an international journal of … 22 (2021) 1, pp. 179-195
The impact the last financial crisis had on the small- and medium-sized enterprises (SMEs) sector varied across countries, affecting them on different levels and to a different extent. The economic situation in Poland during and after the financial crisis was quite stable compared to other EU...
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Analytical comparison of clustering techniques for the recognition of communication patterns
Kaya, Muhammed; Schoop, Mareike - In: Group decision and negotiation 31 (2022) 3, pp. 555-589
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Statistical foundations of ecological rationality
Brighton, Henry - In: Economics: The Open-Access, Open-Assessment E-Journal 14 (2020) 2020-2, pp. 1-32
If we reassess the rationality question under the assumption that the uncertainty of the natural world is largely unquantifiable, where do we end up? In this article the author argues that we arrive at a statistical, normative, and cognitive theory of ecological rationality. The main casualty of...
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Pattern recognition of financial institutions' payment behavior
León, Carlos; Barucca, Paolo; Acero, Oscar; Gage, Gerardo - In: Latin American journal of central banking : LAJCB 1 (2020) 1/4, pp. 1-14
We present a general supervised machine-learning methodology to represent the payment behavior of financial institutions starting from a database of transactions in the Colombian large-value payment system. The methodology learns a feedforward artificial neural network parameterization to...
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MLP, CNN, LSTM and Hybrid SVM for Stock Index Forecasting Task to INDU and FTSE100
Zong, Xiangyu - 2020
The aim of this paper is to investigate the Support Vector Machine (SVM), the Binary Gravity Search Algorithm combined Support Vector Machine (BGSA-SVM), the Multi-layer Perceptron (MLP), the Convolution Neural Network (CNN) and the Long Short-Term Memory (LSTM) neural network, when applied to...
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Screening for light crude oil and market comovements
Faseli, Omid - In: International Journal of Research in Business and … 9 (2020) 7, pp. 123-129
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The predictability of the exchange rate when combining machine learning and fundamental models
Zhang, Yuchen; Hamori, Shigeyuki - In: Journal of risk and financial management : JRFM 13 (2020) 3/48, pp. 1-16
In 1983, Meese and Rogoff showed that traditional economic models developed since the 1970s do not perform better than the random walk in predicting out-of-sample exchange rates when using data obtained after the beginning of the floating rate system. Subsequently, whether traditional economical...
Persistent link: https://ebtypo.dmz1.zbw/10012174126
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User preferences on cloud computing and open innovation : a case study for university employees in Greece
Gkika, Eleni C.; Anagnostopoulos, Theodoros; Ntanos, … - In: Journal of open innovation : technology, market, and … 6 (2020) 2/41, pp. 1-21
Cloud computing hastens technology driven innovation by taking advantage of the speed, the cost-effectiveness, the efficiency and the security that such applications offer. By using cloud computing, public organizations can exploit the economies of scale and innovate both efficiency and rapidly....
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Support vector machine methods and artificial neural networks used for the development of bankruptcy prediction models and their comparison
Horák, Jakub; Vrbka, Jaromir; Suler, Petr - In: Journal of risk and financial management : JRFM 13 (2020) 3/60, pp. 1-15
Bankruptcy prediction is always a topical issue. The activities of all business entities are directly or indirectly affected by various external and internal factors that may influence a company in insolvency and lead to bankruptcy. It is important to find a suitable tool to assess the future...
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Pattern recognition of financial institutions' payment behavior
León, Carlos; Barucca, Paolo; Acero, Oscar; Gage, Gerardo - 2020
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Forecasting credit ratings of EU banks
Plakandaras, Vasilios; Gkonkas, Periklēs; … - In: International Journal of Financial Studies : open … 8 (2020) 3/49, pp. 1-15
The aim of this study is to forecast credit ratings of E.U. banking institutions, as dictated by Credit Rating Agencies (CRAs). To do so, we developed alternative forecasting models that determine the non-disclosed criteria used in rating. We compiled a sample of 112 E.U. banking institutions,...
Persistent link: https://ebtypo.dmz1.zbw/10012291875
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Bankruptcy prediction and stress quantification using support vector machine : evidence from Indian banks
Shrivastava, Santosh Kumar; Ramudu, P. Janaki - In: Risks : open access journal 8 (2020) 2/52, pp. 1-22
Banks play a vital role in strengthening the financial system of a country; hence, their survival is decisive for the stability of national economies. Therefore, analyzing the survival probability of the banks is an essential and continuing research activity. However, the current literature...
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A mixed integer linear programming support vector machine for cost-effective group feature selection : branch-cut-and-price approach
Lee, In Gyu; Yoon, Sang Won; Won, Daehan - In: European journal of operational research : EJOR 299 (2022) 3, pp. 1055-1068
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Unleashing analytics to reduce electricity consumption using incremental clustering algorithm
Chaudhari, Archana Yashodip; Mulay, Preeti - In: International journal of energy sector management 16 (2022) 2, pp. 357-371
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Forecasting unemployment in the euro area with machine learning
Gkonkas, Periklēs; Papadimitriou, Theophilos; … - In: Journal of forecasting 41 (2022) 3, pp. 551-566
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Beyond quantified ignorance: Rebuilding rationality without the bias bias
Brighton, Henry - 2019
If we reassess the rationality question under the assumption that the uncertainty of the natural world is largely unquantifiable, where do we end up? In this article the author argues that we arrive at a statistical, normative, and cognitive theory of ecological rationality. The main casualty of...
Persistent link: https://ebtypo.dmz1.zbw/10011991248
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Stock market analysis: A review and taxonomy of prediction techniques
Shah, Dev; Isah, Haruna; Zulkernine, Farhana - In: International Journal of Financial Studies 7 (2019) 2, pp. 1-22
Stock market prediction has always caught the attention of many analysts and researchers. Popular theories suggest that stock markets are essentially a random walk and it is a fool's game to try and predict them. Predicting stock prices is a challenging problem in itself because of the number of...
Persistent link: https://ebtypo.dmz1.zbw/10013200204
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Convolutional neural network classification of telematics car driving data
Gao, Guangyuan; Wüthrich, Mario V. - In: Risks 7 (2019) 1, pp. 1-18
The aim of this project is to analyze high-frequency GPS location data (second per second) of individual car drivers (and trips). We extract feature information about speeds, acceleration, deceleration, and changes of direction from this high-frequency GPS location data. Time series of this...
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Convolutional neural network classification of telematics car driving data
Gao, Guangyuan; Wüthrich, Mario V. - In: Risks : open access journal 7 (2019) 1/6, pp. 1-18
The aim of this project is to analyze high-frequency GPS location data (second per second) of individual car drivers (and trips). We extract feature information about speeds, acceleration, deceleration, and changes of direction from this high-frequency GPS location data. Time series of this...
Persistent link: https://ebtypo.dmz1.zbw/10012018697
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Beyond quantified ignorance : rebuilding rationality without the bias bias
Brighton, Henry - 2019
If we reassess the rationality question under the assumption that the uncertainty of the natural world is largely unquantifiable, where do we end up? In this article the author argues that we arrive at a statistical, normative, and cognitive theory of ecological rationality. The main casualty of...
Persistent link: https://ebtypo.dmz1.zbw/10011990913
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Stock market analysis : a review and taxonomy of prediction techniques
Shah, Dev; Isah, Haruna; Zulkernine, Farhana - In: International Journal of Financial Studies : open … 7 (2019) 2/26, pp. 1-22
Stock market prediction has always caught the attention of many analysts and researchers. Popular theories suggest that stock markets are essentially a random walk and it is a fool’s game to try and predict them. Predicting stock prices is a challenging problem in itself because of the number...
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Detección de patrones en señales temporales
Lance, Gabriel Pérez - 2019
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Deep Haar scattering network in unidimensional pattern recognition problems
Fernandes Neto, Fernando; Garcia, Claudio; De-Losso, Rodrigo - 2019
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Muster : Theorie der digitalen Gesellschaft
Nassehi, Armin - 2019
„Wir glauben, der Siegeszug der digitalen Technik habe innerhalb weniger Jahre alles revolutioniert: unsere Beziehungen, unsere Arbeit, die Demokratie. Aber jetzt dreht der Soziologe Armin Nassehi den Spieß um und zeigt, dass es immer schon technische Revolutionen gab. Nicht die...
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A new efficient learning approach E-PDLA in assessing the knowledge of breast cancer dataset
Mehfooza, M.; Pattabiraman, V. - In: International journal of services and operations … 38 (2021) 2, pp. 153-160
Persistent link: https://ebtypo.dmz1.zbw/10012522324
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Support vector frontiers : a new approach for estimating production functions through support vector machines
Valero-Carreras, Daniel; Aparicio, Juan; Guerrero, Nadia M. - In: Omega : the international journal of management science 104 (2021), pp. 1-19
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Gold against the machine
Plakandaras, Vasilios; Gkonkas, Periklēs; … - In: Computational economics 57 (2021) 1, pp. 5-28
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A novel grey-fuzzy-Markov and pattern recognition model for industrial accident forecasting
Edem, Inyeneobong Ekoi; Oke, Sunday Ayoola; Adebiyi, … - In: Journal of Industrial Engineering International 14 (2018) 3, pp. 455-489
Industrial forecasting is a top-echelon research domain, which has over the past several years experienced highly provocative research discussions. The scope of this research domain continues to expand due to the continuous knowledge ignition motivated by scholars in the area. So, more...
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Machine learning indices, political institutions, and economic development
Gründler, Klaus; Krieger, Tommy - 2018
We present a new aggregation method - called SVM algorithm - and use this technique to produce novel measures of democracy (186 countries, 1960-2014). The method takes its name from a machine learning technique for pattern recognition and has three notable features: it makes functional...
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Forecasting Electricity Price Spikes Using Support Vector Machines
Stathakis, Efthymios - 2018
Electricity markets are considered to be, the most volatile amongst commodity markets. The non-storability of electricity and the need for instantaneous balancing of demand and supply can often cause extreme short-lived fluctuations in electricity prices. These fluctuations are termed price...
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A novel grey-fuzzy-Markov and pattern recognition model for industrial accident forecasting
Edem, Inyeneobong Ekoi; Oke, Sunday Ayoola; Adebiyi, … - In: Journal of industrial engineering international 14 (2018) 3, pp. 455-489
Industrial forecasting is a top-echelon research domain, which has over the past several years experienced highly provocative research discussions. The scope of this research domain continues to expand due to the continuous knowledge ignition motivated by scholars in the area. So, more...
Persistent link: https://ebtypo.dmz1.zbw/10011887881
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Generating buy/sell signals for an equity share using machine learning
Erkartal, Bugra; Ozdamar, Linet - In: Eurasian journal of business and economics : EJBE 11 (2018) 22, pp. 83-103
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A comparative analysis of data mining techniques for prediction of postprandial blood glucose : a cohort study
Chang, Huan-Cheng; Chang, Pin-Hsiang; Tseng, Sung-Chin; … - In: International journal of management, economics and … 7 (2018), pp. 132-141
The use of advanced predictive techniques and reasoning models has greatly assisted clinicians in improving the diagnosis, prognosis, and treatment of diabetes. Although numerous studies have focused on the relationship between abnormal blood glucose levels and diabetes, few have focused on the...
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When do auditors use specialists' work to improve problem representations of and judgments about complex estimates?
Griffith, Emily E. - In: The accounting review : a publication of the American … 93 (2018) 4, pp. 177-202
Persistent link: https://ebtypo.dmz1.zbw/10011906606
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Statistical foundations of ecological rationality
Brighton, Henry - 2020
If we reassess the rationality question under the assumption that the uncertainty of the natural world is largely unquantifiable, where do we end up? In this article the author argues that we arrive at a statistical, normative, and cognitive theory of ecological rationality. The main casualty of...
Persistent link: https://ebtypo.dmz1.zbw/10012159880
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A comparative study of forecasting corporate credit ratings using neural networks, support vector machines, and decision trees
Golbayani, Parisa; Florescu, Ionuţ; Chatterjee, Rupak - In: The North American journal of economics and finance : a … 54 (2020), pp. 1-16
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Artificial Neural Networks as a quality loss function for Six Sigma
Uluskan, Meryem - In: Total quality management & business excellence 31 (2020) 15/16, pp. 1811-1828
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Predicting bank insolvencies using machine learning techniques
Petropoulos, Anastasios; Siakoulis, Vasilis; … - In: International journal of forecasting 36 (2020) 3, pp. 1092-1113
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A simplified variable analysis of credit ratings for small Chinese enterprises based on support vector machine
Chen, Ying; Guo, Yangkai; Wu, Maoguo - In: International journal of economics and finance 12 (2020) 6, pp. 45-56
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Tightening big Ms in integer programming formulations for support vector machines with ramp loss
Baldomero-Naranjo, Marta; Martínez-Merino, Luisa I.; … - In: European journal of operational research : EJOR 286 (2020) 1, pp. 84-100
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Real-time detection of buzzes in online social networks
Jansen, Nora - 2020
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Day-of-the-week returns and mood: an exterior template approach
Zilca, Shlomo - In: Financial Innovation 3 (2017) 30, pp. 1-21
Rule- and template-based pattern-recognition methods are alternative ways to identify various patterns in stock prices alongside more traditional econometric tools. In this study, we generate an exterior template of mood scores from two perplexingly similar samples of mood scores 50 years apart....
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An intelligent system for business data mining
Huang, Shian-Chang; Wu, Tung-Kuang; Wang, Nan-Yu - In: Global business and finance review 22 (2017) 2, pp. 1-7
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Whose Balance Sheet is This? Neural Networks for Banks’ Pattern Recognition
León, Carlos - 2017
The balance sheet is a snapshot that portraits the financial position of a firm at a specific point of time. Under the reasonable assumption that the financial position of a firm is unique and representative, we use a basic artificial neural network pattern recognition method on Colombian banks'...
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Predicting Bankruptcy with Support Vector Machines
Härdle, Wolfgang K. - 2017
The purpose of this work is to introduce one of the most promising among recently developed statistical techniques – the support vector machine (SVM) – to corporate bankruptcy analysis. An SVM is implemented for analysing such predictors as financial ratios. A method of adapting it to...
Persistent link: https://ebtypo.dmz1.zbw/10012966212
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Estimation of Default Probabilities with Support Vector Machines
Chen, Shiyi - 2017
Predicting default probabilities is important for firms and banks to operate successfully and to estimate their specific risks. There are many reasons to use nonlinear techniques for predicting bankruptcy from financial ratios. Here we propose the so called Support Vector Machine (SVM) to...
Persistent link: https://ebtypo.dmz1.zbw/10012966238
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The Default Risk of Firms Examined with Smooth Support Vector Machines
Härdle, Wolfgang K. - 2017
In the era of Basel II a powerful tool for bankruptcy prognosis is vital for banks. The tool must be precise but also easily adaptable to the bank's objections regarding the relation of false acceptances (Type I error) and false rejections (Type II error). We explore the suitability of Smooth...
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