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Mathematical and Statistical Methods for Actuarial Sciences and Finance
This volume gathers selected peer-reviewed papers presented at the international conference "MAF 2016 – Mathematical and Statistical Methods for Actuarial Sciences and Finance”, held in Paris (France) at the Université Paris-Dauphine from March 30 to April 1, 2016. The contributions highlight new ideas on mathematical and statistical methods in actuarial sciences and finance. The cooperation between mathematicians and statisticians working in insurance and finance is a very fruitful field, one that yields unique theoretical models and practical applications, as well as new insights in the discussion of problems of national and international interest. This volume is addressed to academicians, researchers, Ph.D. students and professionals.
Recent Advances In Stochastic Modeling And Data Analysis
This volume presents the most recent applied and methodological issues in stochastic modeling and data analysis. The contributions cover various fields such as stochastic processes and applications, data analysis methods and techniques, Bayesian methods, biostatistics, econometrics, sampling, linear and nonlinear models, networks and queues, survival analysis, and time series. The volume presents new results with potential for solving real-life problems and provides novel methods for solving these problems by analyzing the relevant data. The use of recent advances in different fields is emphasized, especially new optimization and statistical methods, data warehouse, data mining and knowledge systems, neural computing, and bioinformatics.
Mathematical Foundations of Data Science Using R
The aim of the book is to help students become data scientists. Since this requires a series of courses over a considerable period of time, the book intends to accompany students from the beginning to an advanced understanding of the knowledge and skills that define a modern data scientist. The book presents a comprehensive overview of the mathematical foundations of the programming language R and of its applications to data science.
An Examination of the Pearl
An Examination of the Pearl is a study of the doctrine and history of Conservative Laestadianism, a small, exclusivist Christian group that is organized in Finland and North America as the SRK and the LLC, respectively. The book also looks at the teachings of Martin Luther, early Christianity, Christian fundamentalism and sectarianism, and the Bible.
An Introduction to Computational Risk Management of Equity-Linked Insurance
The quantitative modeling of complex systems of interacting risks is a fairly recent development in the financial and insurance industries. Over the past decades, there has been tremendous innovation and development in the actuarial field. In addition to undertaking mortality and longevity risks in traditional life and annuity products, insurers face unprecedented financial risks since the introduction of equity-linking insurance in 1960s. As the industry moves into the new territory of managing many intertwined financial and insurance risks, non-traditional problems and challenges arise, presenting great opportunities for technology development. Today's computational power and technology ma...
Elements of Data Science, Machine Learning, and Artificial Intelligence Using R
The textbook provides students with tools they need to analyze complex data using methods from data science, machine learning and artificial intelligence. The authors include both the presentation of methods along with applications using the programming language R, which is the gold standard for analyzing data. The authors cover all three main components of data science: computer science; mathematics and statistics; and domain knowledge. The book presents methods and implementations in R side-by-side, allowing the immediate practical application of the learning concepts. Furthermore, this teaches computational thinking in a natural way. The book includes exercises, case studies, Q&A and examples.
Web Engineering
This book constitutes the proceedings of the 24th International Conference, ICWE 2024, held in Tampere, Finland, during June 17-20, 2024. The 16 full papers and 8 short papers included in this volume were carefully reviewed and selected from 66 submissions. This volume includes all the accepted papers across various conference tracks. The ICWE 2024 theme, "Ethical and Human-Centric Web Engineering: Balancing Innovation and Responsibility," invited discussions on creating Web technologies that are not only innovative but also ethical, transparent, privacy-focused, trustworthy, and inclusive, putting human needs and well-being at the core.
The Future of Business Journalism
Foreword / David Callaway -- A Symbiotic Relationship -- The Business Model Failure -- The Dominators -- The Public Relations Factor -- The CEO Can Do Better -- Societal Changes and Economic Forces -- Political Polarization -- The Stock Market Is Overcovered -- Failing Employees and Consumers -- Health Care Coverage Is Sick -- Solutions to the Problem -- Using Technology to Improve Coverage -- The Education Imperative -- Fixing Business Journalism -- Appendix: Timeline.
High-Performance Computing in Finance
High-Performance Computing (HPC) delivers higher computational performance to solve problems in science, engineering and finance. There are various HPC resources available for different needs, ranging from cloud computing– that can be used without much expertise and expense – to more tailored hardware, such as Field-Programmable Gate Arrays (FPGAs) or D-Wave’s quantum computer systems. High-Performance Computing in Finance is the first book that provides a state-of-the-art introduction to HPC for finance, capturing both academically and practically relevant problems.
Financial Data Engineering
Today, investment in financial technology and digital transformation is reshaping the financial landscape and generating many opportunities. Too often, however, engineers and professionals in financial institutions lack a practical and comprehensive understanding of the concepts, problems, techniques, and technologies necessary to build a modern, reliable, and scalable financial data infrastructure. This is where financial data engineering is needed. A data engineer developing a data infrastructure for a financial product possesses not only technical data engineering skills but also a solid understanding of financial domain-specific challenges, methodologies, data ecosystems, providers, form...
