Suchergebnisse

1. A Survey of Machine Learning Methodologies for Loan Evaluation in Peer-to-peer (P2P) Lending -- 2. Explainable Machine Learning Models for Credit Risk Analysis: A Survey -- 3. Data Analytics Incorporated with Machine Learning Approaches in Finance -- 4. Estimation and Inference in Financial Volatility Networks -- 5. Multiresolution Data Analytics for Financial Time Series Using MATLAB -- 6.A Risk-Based Trading System using Algorithmic Trading and Deep Learning Models -- 7. Financial Contagion During COVID-19: Intraday Analysis with VAR-VECM Models -- 8. Nonlinear ARDL Analysis of Real Effective Exchange Rate's Asymmetric Impact on FDI Inflows in Tunisia -- 9. Evaluating Turkish Banks' Complaint Management Performance using Multi-Criteria Decision Analysis -- 10. Financial Cycle, Stress, and Policy Roles in Small Open Economy: Spillover Index Approach -- 11. Performance of Cryptocurrencies under a Sentiment Analysis Approach in the Time of COVID-19 -- 12. Determinants of Non-Performing Loans: Evidence from Indian Banks -- 13. Natural Resources, Conflicts, Terrorism, and Finance: Insights from a Descriptive Data Analysis -- 14. Determinants of Profitability in Islamic Banks: The Kingdom of Saudi Arabia Market -- 15. Trading Rules and Value at Risk: Is there a linkage?

This volume gathers peer-reviewed contributions that address a wide range of recent developments in the methodology and applications of data analysis and classification tools in micro and macroeconomic problems. The papers were originally presented at the 29th Conference of the Section on Classification and Data Analysis of the Polish Statistical Association, SKAD 2020, held in Sopot, Poland, September 7–9, 2020. Providing a balance between methodological contributions and empirical papers, the book is divided into five parts focusing on methodology, finance, economics, social issues and applications dealing with COVID-19 data. It is aimed at a wide audience, including researchers at universities and research institutions, graduate and doctoral students, practitioners, data scientists and employees in public statistical institutions.

Intro -- Inhaltsverzeichnis -- Abbildungsverzeichnis -- Tabellenverzeichnis -- Abkürzungsverzeichnis -- 1 Einleitung und Aufgabenstellung -- 2 Analyse des Traktorenmarktes -- 2.1 Marktstruktur der Agrartechnikbranche -- 2.2 Struktur und Entwicklung der Nachfrager -- 3 Empirie und Theorie zum landwirtschaftlichen Beschaffungsverhalten -- 3.1 Traktorenkauf zwischen Konsumentenkauf- und industriellem Beschaffungsverhalten -- 3.2 Theorien und Empirie zum industriellen Beschaffungsverhalten -- 3.3 Beschaffungsverhalten von Landwirten -- 4 Konzeptioneller Forschungsrahmen der Arbeit -- 5 Qualitative Forschung zu den Beschaffungsentscheidungen beim Erwerb eines Großtraktors -- 5.1 Material und Methodik -- 5.2 Ergebnisse und Diskussion -- 5.3 Handlungempfehlungen für Käufer und Verkäufer von Großtraktoren -- 5.4 Kritische Würdigung der Studie und Forschungsperspektiven -- 5.5 Fazit -- 6 Quantitative Forschung zu den Beschaffungsentscheidungen beim Erwerb eines Großtraktors -- 6.1 Material und Methodik -- 6.2 Ergebnisse und Diskussion -- 6.3 Handlungsempfehlungen für Käufer und Verkäfer von Großtraktoren -- 6.4 Kritische Würdigung und Forschungsperspektiven -- 6.5 Fazit -- 7 Schlussbetrachtung -- Anhang -- A: Leitfaden der qualitativen Forschung -- B. Kodierleitfaden -- C. Forschungshypothesen der quantitativen Forschung -- D. Fragebogen der quantitativen Forschung -- E. Deskriptive Ergebnisse -- F. Ergebnisse der binär logistischen Regression -- G. Ergebnisse des Strukturgleichungsmodells.

Preface -- Methods -- Comparison of proposals of transformation of nominants into stimulants on the example of financial ratios of companies listed on the Warsaw Stock Exchange -- Silhouette index as clustering evaluation tool -- The Role of Discretization of Continuous Variables in SocioEconomic Classification Models on the Example of Logistic Regression Models and Artificial Neural Networks -- Intuitionistic fuzzy synthetic measure for ordinal data -- Improving Classification Accuracy of Ensemble Learning for Symbolic Data Trough Neural Networks' Feature Extraction -- Applications in Finance -- Inequality restricted least squares (IRLS) model of real estate prices -- Application of Hill estimator to assess extreme risks in the metals market -- Segmentation of Enterprises on the Basis of Their Duration Using Survival Trees. Results of an Analysis for Legal Persons and Organizational Entities without Legal Personality in the Łódzkie Voivodship -- Corporate Bankruptcy Prediction with the Use of the Logit Leaf Model -- The impact of longevity on a valuation of long-term investments returns: the case of selected European countries -- Applications in Economics.-Sustainable Development and Green Economy in the European Union Countries – statistical analysis -- The review of indicators of data quality in intra-Community trade in goods. The choice of an indicator and its effect on the ranking of countries -- Development of ICT in Poland in Comparison with the European Union Countries – Multivariate Statistical Analysis -- Sensitivity Analysis in Causal Mediation Effects for TAM Model -- Applications in Social Problems -- Prentice-Williams-Peterson models in the assessment of the influence of the characteristics of the unemployed on the intensity of subsequent registrations in the labour office -- Right-skewed distribution of features and the identification problem of the financial autonomy of local administrative units -- Multi-Criteria Rankings with Interdependent Criteria: Case of EU Countries on Their Way to Healthy Lives and Well-Being -- The comparison of income distributions for women and men in the European Union countries -- Common stochastic mortality trends for multiple European populations -- Impact of the selected factors on the men and women wages in Poland in 2014. The conjoint analysis application.

Big Data: Principles and Paradigmscaptures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data. The book identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications.To help realize Big Data's full potential, the book addresses numerous challenges, offering the conceptual and technological solutions for tackling them. These challenges include life-cycle data management, large-scale storage, flexible processing infrastructure, data modeling, scalable machine learning, data analysis algorithms, sampling techniques, and privacy and ethical issues.Covers computational platforms supporting Big Data applicationsAddresses key principles underlying Big Data computingExamines key developments supporting next generation Big Data platformsExplores the challenges in Big Data computing and ways to overcome themContains expert contributors from both academia and industry

Was wie ein Dan-Brown-Titel klingt, ist eine Reportage über die Arbeit der Datensammler, meist Mathematiker, die mithilfe raffinierter Algorithmen die Spuren auswerten, die wir beim Surfen im Internet hinterlassen. Natürlich ist erschreckend, wie exakt heute Profile unseres Verhaltens erstellt werden können, wobei der Gebrauch für Produktwerbung noch eher harmlos erscheint. Nun ist die Illusion vom Internet als Ort der Freiheit längst verflogen und so ist es auch nicht überraschend, dass alle gesellschaftlichen Akteure es für ihre Zwecke nutzen möchten. Wie in der populären US-amerikanischen Sachliteratur üblich, werden uns von Kapitel zu Kapitel neue Experten vorgestellt, was auf die Dauer etwas ermüdet und nicht wirklich erhellend ist. Das Buch wird schon aufgrund des reißerischen Titels Leser finden. Vergleichbar der etwas ältere Titel "Die Überwachungsmafia" von Pär Ström. (BA 6/05). (2)