Collaborative Research In Applied Statistics Decision Science And Quantitative Finance
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| Author | : Barbara Illowsky |
| Publisher | : Createspace Independent Publishing Platform |
| Total Pages | : 0 |
| Release | : 2015-02-18 |
| Genre | : |
| ISBN | : 9781508534136 |
Collaborative Stastistics is intended for introductory statistics courses being taken by students at two- and four-year colleges who are majoring in fields other than math or engineering. Intermediate algebra is the only prerequisite. The book focuses on applications of statistical knowledge rather than the theory behind it. Barbara Illowsky and Susan Dean are professors of mathematics and statistics at De Anza College in Cupertino, CA. They present nationally on integrating technology, distance learning, collaborative learning, and multiculturalism into the elementary statistics classroom.
| Author | : Chkoniya, Valentina |
| Publisher | : IGI Global |
| Total Pages | : 653 |
| Release | : 2021-06-25 |
| Genre | : Computers |
| ISBN | : 1799869865 |
The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.
| Author | : de Luna, Iviane Ramos |
| Publisher | : IGI Global |
| Total Pages | : 323 |
| Release | : 2019-09-20 |
| Genre | : Business & Economics |
| ISBN | : 1522599304 |
The introduction of new technology and technological services worldwide has ushered in a new wave of peer-to-peer and access-driven companies that are disrupting the most established business categories. The emergence of these new business models has upset the flow in contemporary society and transformed people's behavior towards sharing-based economies. Companies and entrepreneurs can see this significant change in people’s behavior as both an opportunity and a threat. Sharing Economy and the Impact of Collaborative Consumption provides emerging research on the impact that the sharing services are having on society as well as the importance of the sharing economy development in the coming years, dealing with relevant issues such as regulations, the technological aspects involved in these platforms, the impact in the tourism sector, and consumer behavior in relation to these services. Multidisciplinary in nature, this publication establishes links between economics, finance, marketing, consumer behavior, and IT, and covers topics that include e-commerce, consumer behavior, and peer economy. It is ideally designed for researchers, students, business professionals, and entrepreneurs seeking current research on the impact that this industry has on various economic, marketing, and societal aspects of different countries.
| Author | : Wolfgang Karl Härdle |
| Publisher | : Springer |
| Total Pages | : 369 |
| Release | : 2017-08-02 |
| Genre | : Business & Economics |
| ISBN | : 3662544865 |
This volume provides practical solutions and introduces recent theoretical developments in risk management, pricing of credit derivatives, quantification of volatility and copula modeling. This third edition is devoted to modern risk analysis based on quantitative methods and textual analytics to meet the current challenges in banking and finance. It includes 14 new contributions and presents a comprehensive, state-of-the-art treatment of cutting-edge methods and topics, such as collateralized debt obligations, the high-frequency analysis of market liquidity, and realized volatility. The book is divided into three parts: Part 1 revisits important market risk issues, while Part 2 introduces novel concepts in credit risk and its management along with updated quantitative methods. The third part discusses the dynamics of risk management and includes risk analysis of energy markets and for cryptocurrencies. Digital assets, such as blockchain-based currencies, have become popular b ut are theoretically challenging when based on conventional methods. Among others, it introduces a modern text-mining method called dynamic topic modeling in detail and applies it to the message board of Bitcoins. The unique synthesis of theory and practice supported by computational tools is reflected not only in the selection of topics, but also in the fine balance of scientific contributions on practical implementation and theoretical concepts. This link between theory and practice offers theoreticians insights into considerations of applicability and, vice versa, provides practitioners convenient access to new techniques in quantitative finance. Hence the book will appeal both to researchers, including master and PhD students, and practitioners, such as financial engineers. The results presented in the book are fully reproducible and all quantlets needed for calculations are provided on an accompanying website. The Quantlet platform quantlet.de, quantlet.com, quantlet.org is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web. QuantNet and the corresponding Data-Driven Documents-based visualization allows readers to reproduce the tables, pictures and calculations inside this Springer book.
| Author | : Jason Williamson |
| Publisher | : John Wiley & Sons |
| Total Pages | : 264 |
| Release | : 2014-12-31 |
| Genre | : Computers |
| ISBN | : 1118903404 |
Hone your analytic talents and become part of the next big thing Getting a Big Data Job For Dummies is the ultimate guide to landing a position in one of the fastest-growing fields in the modern economy. Learn exactly what "big data" means, why it's so important across all industries, and how you can obtain one of the most sought-after skill sets of the decade. This book walks you through the process of identifying your ideal big data job, shaping the perfect resume, and nailing the interview, all in one easy-to-read guide. Companies from all industries, including finance, technology, medicine, and defense, are harnessing massive amounts of data to reap a competitive advantage. The demand for big data professionals is growing every year, and experts forecast an estimated 1.9 million additional U.S. jobs in big data by 2015. Whether your niche is developing the technology, handling the data, or analyzing the results, turning your attention to a career in big data can lead to a more secure, more lucrative career path. Getting a Big Data Job For Dummies provides an overview of the big data career arc, and then shows you how to get your foot in the door with topics like: The education you need to succeed The range of big data career path options An overview of major big data employers A plan to develop your job-landing strategy Your analytic inclinations may be your ticket to long-lasting success. In a highly competitive job market, developing your data skills can create a situation where you pick your employer rather than the other way around. If you're ready to get in on the ground floor of the next big thing, Getting a Big Data Job For Dummies will teach you everything you need to know to get started today.
| Author | : Scott, Jacqueline L. Scott |
| Publisher | : |
| Total Pages | : 384 |
| Release | : 2012 |
| Genre | : Social sciences |
| ISBN | : |
| Author | : Daniel Rösch |
| Publisher | : John Wiley & Sons |
| Total Pages | : 464 |
| Release | : 2013-04-03 |
| Genre | : Business & Economics |
| ISBN | : 1119966043 |
A comprehensive resource providing extensive coverage of the state of the art in credit secruritisations, derivatives, and risk management Credit Securitisations and Derivatives is a one-stop resource presenting the very latest thinking and developments in the field of credit risk. Written by leading thinkers from academia, the industry, and the regulatory environment, the book tackles areas such as business cycles; correlation modelling and interactions between financial markets, institutions, and instruments in relation to securitisations and credit derivatives; credit portfolio risk; credit portfolio risk tranching; credit ratings for securitisations; counterparty credit risk and clearing of derivatives contracts and liquidity risk. As well as a thorough analysis of the existing models used in the industry, the book will also draw on real life cases to illustrate model performance under different parameters and the impact that using the wrong risk measures can have.
| Author | : Kosuke Imai |
| Publisher | : Princeton University Press |
| Total Pages | : 464 |
| Release | : 2021-03-16 |
| Genre | : Political Science |
| ISBN | : 0691191093 |
"Princeton University Press published Imai's textbook, Quantitative Social Science: An Introduction, an introduction to quantitative methods and data science for upper level undergrads and graduates in professional programs, in February 2017. What is distinct about the book is how it leads students through a series of applied examples of statistical methods, drawing on real examples from social science research. The original book was prepared with the statistical software R, which is freely available online and has gained in popularity in recent years. But many existing courses in statistics and data sciences, particularly in some subject areas like sociology and law, use STATA, another general purpose package that has been the market leader since the 1980s. We've had several requests for STATA versions of the text as many programs use it by default. This is a "translation" of the original text, keeping all the current pedagogical text but inserting the necessary code and outputs from STATA in their place"--
| Author | : Cheng-Few Lee |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 1700 |
| Release | : 2010-06-14 |
| Genre | : Business & Economics |
| ISBN | : 0387771174 |
Quantitative finance is a combination of economics, accounting, statistics, econometrics, mathematics, stochastic process, and computer science and technology. Increasingly, the tools of financial analysis are being applied to assess, monitor, and mitigate risk, especially in the context of globalization, market volatility, and economic crisis. This two-volume handbook, comprised of over 100 chapters, is the most comprehensive resource in the field to date, integrating the most current theory, methodology, policy, and practical applications. Showcasing contributions from an international array of experts, the Handbook of Quantitative Finance and Risk Management is unparalleled in the breadth and depth of its coverage. Volume 1 presents an overview of quantitative finance and risk management research, covering the essential theories, policies, and empirical methodologies used in the field. Chapters provide in-depth discussion of portfolio theory and investment analysis. Volume 2 covers options and option pricing theory and risk management. Volume 3 presents a wide variety of models and analytical tools. Throughout, the handbook offers illustrative case examples, worked equations, and extensive references; additional features include chapter abstracts, keywords, and author and subject indices. From "arbitrage" to "yield spreads," the Handbook of Quantitative Finance and Risk Management will serve as an essential resource for academics, educators, students, policymakers, and practitioners.
| Author | : Marco Corazza |
| Publisher | : World Scientific |
| Total Pages | : 429 |
| Release | : 2024-07-26 |
| Genre | : Computers |
| ISBN | : 1800615221 |
We wrote this book to help financial experts and investors to understand the state of the art of artificial intelligence and machine learning in finance. But first, what is artificial intelligence? The foundations of artificial intelligence lie in the human desire to automate. Often this desire has had foundations in grand civilization-defining visions or economic needs, such as the Antikythera mechanism, circa 200 BCE. Considered to be the oldest known example of an analog computer, it is thought that the mechanism automated the prediction of the positions of the sun, the moon, and the planets to assist in navigation.No matter the specific industry or application, AI has become a new engine of growth. Both finance and banking have been leveraging AI technologies and algorithms, applying them to automate routine tasks, procedures and forecasting, thereby improving overall customer experience.The topics covered in this book make it an invaluable resource for academics, researchers, policymakers, and practitioners alike who want to understand how AI has affected the banking and financial industries and how it will continue to change them in the years to come.
