Petr Hajek – författare

This book introduces machine learning in finance and illustrates how we can use computational tools in numerical finance in real-world context. These computational techniques are particularly useful in financial risk management, corporate bankruptcy prediction, stock price prediction, and portfolio management. The book also offers practical and managerial implications of financial and managerial decision support systems and how these systems capture vast amount of financial data.Business risk and uncertainty are two of the toughest challenges in the financial industry. This book will be a useful guide to the use of machine learning in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.

This book introduces machine learning in finance and illustrates how we can use computational tools in numerical finance in real-world context. These computational techniques are particularly useful in financial risk management, corporate bankruptcy prediction, stock price prediction, and portfolio management. The book also offers practical and managerial implications of financial and managerial decision support systems and how these systems capture vast amount of financial data.Business risk and uncertainty are two of the toughest challenges in the financial industry. This book will be a useful guide to the use of machine learning in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.

One of the fundamental questions of Banach space theory is whether every Banach space has a basis. A space with a basis gives us a sense of familiarity and concreteness, and perhaps a chance to attempt the classification of all Banach spaces and other problems.The main goals of this book are to: -introduce the reader to some of the basic concepts, results and applications of biorthogonal systems in infinite dimensional geometry of Banach spaces, and in topology and nonlinear analysis in Banach spaces, -aim the text at graduate students and researchers who have a foundation in Banach space theory, - expose the reader to some current avenues of research in biorthogonal systems in Banach spaces, -provide notes and exercises related to the topic, suggest open problems and possible new directions of research.Numerous exercises are included, and the only prerequisites are a basic background in functional analysis.

This text introduces readers to the basic principles of functional analysis and to areas of Banach space theory. In the first part, the book develops the classical theory, including weak topologies, locally convex spaces, Schauder bases, and compact operator theory. The second part covers topics in convexity and smoothness, finite representability, and variational. The text can be used in graduate courses or for independent study. It includes exercises of different levels and is aimed at young researchers in functional analysis. It can also serve as a reference book.

This text presents a systematic treatment of deductive aspects and structures of fuzzy logic understood as many valued logic sui generis. Some important systems of real-valued propositional and predicate calculus are defined and investigated. The aim is to show that fuzzy logic as a logic of imprecise (vague) propositions does have well-developed formal foundations and that most things usually named "fuzzy inference" can be naturally understood as logical deduction.

To cope with the competitive worldwide marketplace, organizations rely on business intelligence to an increasing extent. Cyber security is an inevitable practice to protect the entire business sector and its customer. This book presents the significance and application of cyber security for safeguarding organizations, individuals’ personal information, and government.The book provides both practical and managerial implications of cyber security that also supports business intelligence and discusses the latest innovations in cyber security. It offers a roadmap to master degree students and PhD researchers for cyber security analysis in order to minimize the cyber security risk and protect customers from cyber-attack. The book also introduces the most advanced and novel machine learning techniques including, but not limited to, Support Vector Machine, Neural Networks, Extreme Learning Machine, Ensemble Learning, and Deep Learning Approaches, with a goal to apply those to cyber risk management datasets. It will also leverage real-world financial instances to practise business product modelling and data analysis.The contents of this book will be useful for a wide audience who are involved in managing network systems, data security, data forecasting, cyber risk modelling, fraudulent credit risk detection, portfolio management, and data regulatory bodies. It will be particularly beneficial to academics as well as practitioners who are looking to protect their IT system, and reduce data breaches and cyber-attack vulnerabilities.

To cope with the competitive worldwide marketplace, organizations rely on business intelligence to an increasing extent. Cyber security is an inevitable practice to protect the entire business sector and its customer. This book presents the significance and application of cyber security for safeguarding organizations, individuals’ personal information, and government.The book provides both practical and managerial implications of cyber security that also supports business intelligence and discusses the latest innovations in cyber security. It offers a roadmap to master degree students and PhD researchers for cyber security analysis in order to minimize the cyber security risk and protect customers from cyber-attack. The book also introduces the most advanced and novel machine learning techniques including, but not limited to, Support Vector Machine, Neural Networks, Extreme Learning Machine, Ensemble Learning, and Deep Learning Approaches, with a goal to apply those to cyber risk management datasets. It will also leverage real-world financial instances to practise business product modelling and data analysis.The contents of this book will be useful for a wide audience who are involved in managing network systems, data security, data forecasting, cyber risk modelling, fraudulent credit risk detection, portfolio management, and data regulatory bodies. It will be particularly beneficial to academics as well as practitioners who are looking to protect their IT system, and reduce data breaches and cyber-attack vulnerabilities.

This book presents a systematic treatment of deductive aspects and structures of fuzzy logic understood as many valued logic sui generis. Some important systems of real-valued propositional and predicate calculus are defined and investigated. The aim is to show that fuzzy logic as a logic of imprecise (vague) propositions does have well-developed formal foundations and that most things usually named `fuzzy inference' can be naturally understood as logical deduction.

One of the fundamental questions of Banach space theory is whether every Banach space has a basis. A space with a basis gives us a sense of familiarity and concreteness, and perhaps a chance to attempt the classification of all Banach spaces and other problems.The main goals of this book are to: -introduce the reader to some of the basic concepts, results and applications of biorthogonal systems in infinite dimensional geometry of Banach spaces, and in topology and nonlinear analysis in Banach spaces, -aim the text at graduate students and researchers who have a foundation in Banach space theory, - expose the reader to some current avenues of research in biorthogonal systems in Banach spaces, -provide notes and exercises related to the topic, suggest open problems and possible new directions of research.Numerous exercises are included, and the only prerequisites are a basic background in functional analysis.

This book introduces the basic principles of functional analysis and areas of Banach space theory that are close to nonlinear analysis and topology. The text can be used in graduate courses or for independent study. It includes a large number of exercises of different levels of difficulty, accompanied by hints.

Banach spaces provide a framework for linear and nonlinear functional analysis, operator theory, abstract analysis, probability, optimization and other branches of mathematics. This book introduces the reader to linear functional analysis and to related parts of infinite-dimensional Banach space theory.Key Features: - Develops classical theory, including weak topologies, locally convex space, Schauder bases and compact operator theory - Covers Radon-Nikodým property, finite-dimensional spaces and local theory on tensor products - Contains sections on uniform homeomorphisms and non-linear theory, Rosenthal's L1 theorem, fixed points, and more- Includes information about further topics and directions of research and some open problems at the end of each chapter - Provides numerous exercises for practice The text is suitable for graduate courses or for independent study. Prerequisites include basic courses in calculus and linear. Researchers in functional analysis will also benefit for this book as it can serve as a reference book.

Banach spaces provide a framework for linear and nonlinear functional analysis, operator theory, abstract analysis, probability, optimization and other branches of mathematics. This book introduces the reader to linear functional analysis and to related parts of infinite-dimensional Banach space theory.Key Features: - Develops classical theory, including weak topologies, locally convex space, Schauder bases and compact operator theory - Covers Radon-Nikodým property, finite-dimensional spaces and local theory on tensor products - Contains sections on uniform homeomorphisms and non-linear theory, Rosenthal's L1 theorem, fixed points, and more- Includes information about further topics and directions of research and some open problems at the end of each chapter - Provides numerous exercises for practice The text is suitable for graduate courses or for independent study. Prerequisites include basic courses in calculus and linear. Researchers in functional analysis will also benefit for this book as it can serve as a reference book.

This book provides an assessment of the evolution and dynamics of regional innovation systems (RISs) and the economic and social impact of resulting knowledge spillovers, presenting comparative case studies on the regions of several Central and Eastern European (CEE) countries (Czech Republic, Poland, Hungary, Slovakia, Lithuania and Estonia).It analyses RISs on the basis of several dimensions, such as absorption capacity and intellectual capital, and using several methods such as data envelopment analysis, patent network analysis, and weighted sum approach.Further, by looking at the economic and social impact of knowledge spillovers in RISs and networking, it identifies key distinguishing factors, including foreign direct investments, still prevalent centralized decision-making, EU-driven innovation policies and public financing of innovations. Sectoral case studies, e.g. from the automobile, chemical and other hi-tech manufacturing industries, are presented to help readers understand the different types of knowledge spillovers in CEE countries and the evolution and dynamics of RISs, and provide a multifaceted overview of the CEE regions.

This book presents the state-of-the-art applications of machine learning in the finance domain with a focus on financial product modeling, which aims to advance the model performance and minimize risk and uncertainty.

This book presents the state-of-the-art applications of machine learning in the finance domain with a focus on financial product modeling, which aims to advance the model performance and minimize risk and uncertainty.

This book is about the subject of higher smoothness in separable real Banach spaces. It brings together several angles of view on polynomials, both in finite and infinite setting. Also a rather thorough and systematic view of the more recent results, and the authors work is given. The book revolves around two main broad questions: What is the best smoothness of a given Banach space, and its structural consequences? How large is a supply of smooth functions in the sense of approximating continuous functions in the uniform topology, i.e. how does the Stone-Weierstrass theorem generalize into infinite dimension where measure and compactness are not available?The subject of infinite dimensional real higher smoothness is treated here for the first time in full detail, therefore this book may also serve as a reference book.

This book provides an assessment of the evolution and dynamics of regional innovation systems (RISs) and the economic and social impact of resulting knowledge spillovers, presenting comparative case studies on the regions of several Central and Eastern European (CEE) countries (Czech Republic, Poland, Hungary, Slovakia, Lithuania and Estonia).It analyses RISs on the basis of several dimensions, such as absorption capacity and intellectual capital, and using several methods such as data envelopment analysis, patent network analysis, and weighted sum approach.Further, by looking at the economic and social impact of knowledge spillovers in RISs and networking, it identifies key distinguishing factors, including foreign direct investments, still prevalent centralized decision-making, EU-driven innovation policies and public financing of innovations. Sectoral case studies, e.g. from the automobile, chemical and other hi-tech manufacturing industries, are presented to help readers understand the different types of knowledge spillovers in CEE countries and the evolution and dynamics of RISs, and provide a multifaceted overview of the CEE regions.

This book presents the proceedings of the 20th International Symposium on Mathematical Foundations of Computer Science, MFCS'95, held in Prague, Czech Republic in August/September 1995.The book contains eight invited papers and two abstracts of invited talks by outstanding scientists as well as 44 revised full research papers selected from a total of 104 submissions. All relevant aspects of theoretical computer science are addressed, particularly the mathematical foundations; the papers are organized in sections on structural complexity, algorithms, complexity theory, graphs in models of computation, lower bounds, formal languages, unification, rewriting and type theory, distributed computation, concurrency, semantics, model checking, and formal calculi.