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| Author | : Juan Pablo Pardo-Guerra |
| Publisher | : Cambridge University Press |
| Total Pages | : 375 |
| Release | : 2019-05-16 |
| Genre | : Business & Economics |
| ISBN | : 1108496423 |
Explains how stock markets became automated through the work of invisible technologists, redefining the fabric of finance for the twenty-first century.
| Author | : Ruben Lee |
| Publisher | : OUP Oxford |
| Total Pages | : 429 |
| Release | : 1998-11-12 |
| Genre | : Business & Economics |
| ISBN | : 0191584126 |
New technology has revolutionized the nature and threatened the existence of traditional stock and futures exchanges. This book analyses how they have responded to developments in automation,
| Author | : Aaron Benanav |
| Publisher | : Verso Books |
| Total Pages | : 161 |
| Release | : 2022-04-19 |
| Genre | : Social Science |
| ISBN | : 1839761326 |
A consensus-shattering account of automation technologies and their effect on workplaces and the labor market In this consensus-shattering account of automation technologies, Aaron Benanav investigates the economic trends that will shape our working lives far into the future. Silicon Valley titans, politicians, techno-futurists, and social critics have united in arguing that we are on the cusp of an era of rapid technological automation, heralding the end of work as we know it. But does the muchdiscussed “rise of the robots” really explain the long-term decline in the demand for labor? Automation and the Future of Work uncovers the deep weaknesses of twenty-first-century capitalism and the reasons why the engine of economic growth keeps stalling. Equally important, Benanav goes on to salvage from automation discourse its utopian content: the positive vision of a world without work. What social movements, he asks, are required to propel us into post-scarcity if technological innovation alone can’t deliver it? In response to calls for a permanent universal basic income that would maintain a growing army of redundant workers, he offers a groundbreaking counterproposal.
| Author | : Ajay Agrawal |
| Publisher | : University of Chicago Press |
| Total Pages | : 172 |
| Release | : 2024-03-05 |
| Genre | : Business & Economics |
| ISBN | : 0226833127 |
A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.
| Author | : Timothy Ferriss |
| Publisher | : Random House |
| Total Pages | : 418 |
| Release | : 2011 |
| Genre | : Business & Economics |
| ISBN | : 0091929113 |
How to reconstruct your life? Whether your dream is experiencing high-end world travel, earning a monthly five-figure income with zero management, or just living more and working less, this book teaches you how to double your income, and how to outsource your life to overseas virtual assistants for $5 per hour and do whatever you want.
| Author | : Wesley R. Gray |
| Publisher | : John Wiley & Sons |
| Total Pages | : 293 |
| Release | : 2012-12-26 |
| Genre | : Business & Economics |
| ISBN | : 1118328078 |
A must-read book on the quantitative value investment strategy Warren Buffett and Ed Thorp represent two spectrums of investing: one value driven, one quantitative. Where they align is in their belief that the market is beatable. This book seeks to take the best aspects of value investing and quantitative investing as disciplines and apply them to a completely unique approach to stock selection. Such an approach has several advantages over pure value or pure quantitative investing. This new investing strategy framed by the book is known as quantitative value, a superior, market-beating method to investing in stocks. Quantitative Value provides practical insights into an investment strategy that links the fundamental value investing philosophy of Warren Buffett with the quantitative value approach of Ed Thorp. It skillfully combines the best of Buffett and Ed Thorp—weaving their investment philosophies into a winning, market-beating investment strategy. First book to outline quantitative value strategies as they are practiced by actual market practitioners of the discipline Melds the probabilities and statistics used by quants such as Ed Thorp with the fundamental approaches to value investing as practiced by Warren Buffett and other leading value investors A companion Website contains supplementary material that allows you to learn in a hands-on fashion long after closing the book If you're looking to make the most of your time in today's markets, look no further than Quantitative Value.
| Author | : Yves Hilpisch |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 720 |
| Release | : 2018-12-05 |
| Genre | : Computers |
| ISBN | : 1492024295 |
The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks.
| Author | : Mario Smeets |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2021 |
| Genre | : |
| ISBN | : 9783658329754 |
The book provides its readers with an overview of the technology and its potential and helps them to place RPA in the context of process management. The readers receive concrete instructions for the implementation of an RPA with all necessary steps, such as adequate process selection, process preparation and many more. Application examples - many of them from the banking industry, but easily transferable to other industries - provide readers with valuable experience and offer support in the successful introduction and application of the technology. This book is a translation of the original German 1st edition Robotic Process Automation (RPA) in der Finanzwirtschaft by Mario Smeets, published by Springer Fachmedien Wiesbaden GmbH, part of Springer Nature in 2019. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation. Springer Nature works continuously to further the development of tools for the production of books and on the related technologies to support the authors. The book is intended for future or already experienced users of RPA and for anyone interested in the technology. Process or technology managers at all hierarchical levels of IT and organizational areas, as well as users and managers in the business departments - across all industries. The Content Application areas and examples of RPA in the financial industry Technological Background RPA market overview and software solutions Execution of RPA implementations Setting up and introducing RPA governance RPA success factors Special cases and further developments of the RPA technology The authors Mario Smeets is a management consultant for banks, insurance companies and financial service providers. One of his consulting focuses lies in the area of process management and automation. Ralph Erhard is founder of DCP Deutsche Consulting Partner. His consulting focuses include strategic and organizational issues for banks, insurance companies and service providers. Thomas Kaußler is founder of DCP Deutsche Consulting Partner. His consulting focuses include implementation and migration projects for banks, insurance companies, service providers and system providers in the capital market business.
| Author | : Matthew F. Dixon |
| Publisher | : Springer Nature |
| Total Pages | : 565 |
| Release | : 2020-07-01 |
| Genre | : Business & Economics |
| ISBN | : 3030410684 |
This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.
| Author | : Christian Langmann |
| Publisher | : Springer Nature |
| Total Pages | : 143 |
| Release | : 2023-01-16 |
| Genre | : Business & Economics |
| ISBN | : 3658386924 |
This book provides a practice-oriented overview of the necessary prerequisites, the mode of operation, and the individual steps for the successful introduction of Robotic Process Automation (RPA). In addition to theoretical basics, practical examples from controlling and accounting illustrate the enormous potential of this technology....
