Machine Learning for Financial Risk Management with Python

Handbook of Computational Intelligence in Biomedical Engineering and Healthcare helps readers analyze and conduct advanced research in specialty healthcare applications surrounding oncology, genomics and genetic data, ontologies construction, bio-memetic systems, biomedical electronics, protein structure prediction, and biomedical data analysis. The book provides the reader with a comprehensive guide to advanced computational intelligence, spanning deep learning, fuzzy logic, connectionist systems, evolutionary computation, cellular automata, self-organizing systems, soft computing, and hybrid intelligent systems in biomedical and healthcare applications. Sections focus on important biomedical engineering applications, including biosensors, enzyme immobilization techniques, immuno-assays, and nanomaterials for biosensors and other biomedical techniques.Other sections cover gene-based solutions and applications through computational intelligence techniques and the impact of nonlinear/un

We often hear that AI is revolutionising the financial sector, like no other technology has done before. This book looks beyond these clich s and explores all aspects of this transformation at a deep level. It spells out a vision for the future and answers many questions that are routinely ignored.What do we mean by Artificial Intelligence in finance? How do we move past the myths and misconceptions to reveal the key driving forces?What are the industry trends that align with this transformation? Is it the explosion of digital touchpoints in retail, the reduced risk taking by investment banks, or the ascent of passive funds in asset management?How do we develop concrete use cases from idea generation to production? How do we engineer systems to make accurate predictions, offer recommendations to clients, or analyse unstructured news data?How do we build a successful data-driven organisation? What are the key pitfalls to avoid? Is it about culture, data governance, or management vision?

Dealing with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed matter physics and statistical mechanics, this book provides an introduction to computer simulations in physics. The 5th edition contains extensive new material describing numerous powerful algorithms and methods that represent recent developments in the field. New topics such as active matter and machine learning are also introduced. Throughout, there are many applications, examples, recipes, case studies, and exercises to help the reader fully comprehend the material. This book is ideal for graduate students and researchers, both in academia and industry, who want to learn techniques that have become a third tool of physical science, complementing experiment and analytical theory.

Inclusive Business Models talks about organizations that employ principles of business to address the needs of the poor. It takes an analytical approach to derive insights about business models by comparison with other inclusive models seen within the same sector and through comparisons with models from a different sector. This cross sector comparison, especially with a number of case studies, would enable readers to cumulate their learning, and act as a guide to management students, practicing managers and entrepreneurs for understanding and analyzing any business model that intends or claims to be inclusive. This book is beneficial for students of entrepreneurship, social enterprises and human resource management. Sections of this book would be relevant for courses on social enterprises, developmental economics and inclusive business models taught globally, given that India today has emerged as a hotbed of experiments and innovations to deal with the problems of poverty and inequalit

Inclusive Business Models talks about organizations that employ principles of business to address the needs of the poor. It takes an analytical approach to derive insights about business models by comparison with other inclusive models seen within the same sector and through comparisons with models from a different sector. This cross sector comparison, especially with a number of case studies, would enable readers to cumulate their learning, and act as a guide to management students, practicing managers and entrepreneurs for understanding and analyzing any business model that intends or claims to be inclusive. This book is beneficial for students of entrepreneurship, social enterprises and human resource management. Sections of this book would be relevant for courses on social enterprises, developmental economics and inclusive business models taught globally, given that India today has emerged as a hotbed of experiments and innovations to deal with the problems of poverty and inequalit

Striking the right balance between public health priorities and health innovation is a critical policy challenge for India given their mutually conflicting nature and interests. India has a huge burden of diseases implicated by a gamut of health problems including the uneven distribution of demographic and epidemiological transition, threat of new infectious disease pandemic like COVID 19, increasing privatisation of healthcare, low affordability to life saving medicines and most importantly the escalating healthcare expenditure coupled with poor financial risk protection. The central question that the book addresses is whether health innovation in India is sensitive to the public health needs and priorities. It unearths the overriding issues related to responsiveness and equity in India's health innovation. The book highlights the need for a responsible innovation framework for India that balances the priorities of public health and the industry goals.

The real world is perceived and broken down as data, models and algorithms in the eyes of physicists and engineers. Data is noisy by nature and classical statistical tools have so far been successful in dealing with relatively smaller levels of randomness. The recent emergence of Big Data and the required computing power to analyse them have rendered classical tools outdated and insufficient. Tools such as random matrix theory and the study of large sample covariance matrices can efficiently process these big data sets and help make sense of modern, deep learning algorithms. Presenting an introductory calculus course for random matrices, the book focusses on modern concepts in matrix theory, generalising the standard concept of probabilistic independence to non-commuting random variables. Concretely worked out examples and applications to financial engineering and portfolio construction make this unique book an essential tool for physicists, engineers, data analysts, and economists.

Harriman Classics with a new foreword by James P. O'ShaughnessyIf you want to get rich, no matter how inexperienced you are in investment, this book can help you. Its message is that you must not avoid risk, nor court it foolhardily, but learn how to manage it – and enjoy it too.The 12 major and 16 minor Zurich Axioms contained in this book are a set of principles providing a practical philosophy for the realistic management of risk, which can be followed successfully by anyone, not merely the 'experts'. Several of the Axioms fly right in the face of the traditional wisdom of the investment advice business – yet the enterprising Swiss speculators who devised them became rich, while many investors who follow the conventional path do not. Max Gunther, whose father was one of the original speculators who devised the Axioms, made his first capital gain on the stock market at the age of 13 and never looked back.Now the rest of us can follow in his footsteps. Startlingly straightforward, the

Using numerous examples with real data, this textbook closely integrates the learning of statistics with the learning of R. It is suitable for introductory-level learners, allows for curriculum flexibility, and includes, as an online resource, R-code script files for all examples and figures included in each chapter, for students to learn from and adapt and use in their future data analytic work. Other unique features created specifically for this textbook include an online R tutorial that introduces readers to data frames and other basic elements of the R architecture, and a CRAN library of datasets and functions that is used throughout the book. Essential topics often overlooked in other introductory texts, such as data management, are covered. The textbook includes online solutions to all end-of-chapter exercises and PowerPoint slides for all chapters as additional resources, and is suitable for those who do not have a strong background in mathematics.

Decision-making in the face of uncertainty is a significant challenge in machine learning, and the multi-armed bandit model is a commonly used framework to address it. This comprehensive and rigorous introduction to the multi-armed bandit problem examines all the major settings, including stochastic, adversarial, and Bayesian frameworks. A focus on both mathematical intuition and carefully worked proofs makes this an excellent reference for established researchers and a helpful resource for graduate students in computer science, engineering, statistics, applied mathematics and economics. Linear bandits receive special attention as one of the most useful models in applications, while other chapters are dedicated to combinatorial bandits, ranking, non-stationary problems, Thompson sampling and pure exploration. The book ends with a peek into the world beyond bandits with an introduction to partial monitoring and learning in Markov decision processes.

The one bad apple spoiling the whole barrel has become a common metaphor used with reference to risk culture in organisations. This “inside-out” perspective begins with the individual as the unit of analysis and follows with inferences to the broader environment. Since the Global Financial Crisis (GFC) of 2008, risk culture for many has become the explanation for shortcomings, poor decisions, and moral failures in organisations. This volume presents an institutional perspective of the forces that shape risk culture, and culture more generally, in organisations through a multi-disciplinary examination from a variety of leading academics and subject specialists. The authors demonstrate that firms play a role as manufacturers and managers of risk and they challenge common conceptions that attribute risk to chance circumstances or rogue behaviours. The foundational concepts needed for an institutional view of risk culture are highlighted with subsequent links to significant developments wi

The one bad apple spoiling the whole barrel has become a common metaphor used with reference to risk culture in organisations. This “inside-out” perspective begins with the individual as the unit of analysis and follows with inferences to the broader environment. Since the Global Financial Crisis (GFC) of 2008, risk culture for many has become the explanation for shortcomings, poor decisions, and moral failures in organisations. This volume presents an institutional perspective of the forces that shape risk culture, and culture more generally, in organisations through a multi-disciplinary examination from a variety of leading academics and subject specialists. The authors demonstrate that firms play a role as manufacturers and managers of risk and they challenge common conceptions that attribute risk to chance circumstances or rogue behaviours. The foundational concepts needed for an institutional view of risk culture are highlighted with subsequent links to significant developments wi

The Art of Child and Adolescent Psychiatry is an engaging and authoritative account of the essential skills required to practice child and adolescent psychiatry for all those working in children's mental health, from trainees to experienced professionals in paediatrics, psychiatry, psychology, and psychotherapy. The practical tasks of meeting the child and family, planning treatments, and working with colleagues are all covered, building on existing texts that mainly focus on diagnostic criteria, protocols, and laws. This book respects the evidence base, while also pointing out its limitations, and suggests ways in which to deal with these. Psychiatry is placed within broader frameworks including strategy, learning, management, philosophy, ethics, and interpersonal relations. With over 200 educational vignettes of the authors' vast experience in the field, the book is also highly illustrated. The Art of Child and Adolescent Psychiatry is an indispensable guide to thoughtful practice in

Algorithms permeate our lives in numerous ways, performing tasks that until recently could only be carried out by humans. Artificial Intelligence (AI) technologies, based on machine learning algorithms and big-data-powered systems, can perform sophisticated tasks such as driving cars, analyzing medical data, and evaluating and executing complex financial transactions - often without active human control or supervision. Algorithms also play an important role in determining retail pricing, online advertising, loan qualification, and airport security. In this work, Martin Ebers and Susana Navas bring together a group of scholars and practitioners from across Europe and the US to analyze how this shift from human actors to computers presents both practical and conceptual challenges for legal and regulatory systems. This book should be read by anyone interested in the intersection between computer science and law, how the law can better regulate algorithmic design, and the legal ramificatio

This book integrates philosophy of science, data acquisition methods, and statistical modeling techniques to present readers with a forward-thinking perspective on clinical science. It reviews modern research practices in clinical psychology that support the goals of psychological science, study designs that promote good research, and quantitative methods that can test specific scientific questions. It covers new themes in research including intensive longitudinal designs, neurobiology, developmental psychopathology, and advanced computational methods such as machine learning. Core chapters examine significant statistical topics, for example missing data, causality, meta-analysis, latent variable analysis, and dyadic data analysis. A balanced overview of observational and experimental designs is also supplied, including preclinical research and intervention science. This is a foundational resource that supports the methodological training of the current and future generations of clinic

This book integrates philosophy of science, data acquisition methods, and statistical modeling techniques to present readers with a forward-thinking perspective on clinical science. It reviews modern research practices in clinical psychology that support the goals of psychological science, study designs that promote good research, and quantitative methods that can test specific scientific questions. It covers new themes in research including intensive longitudinal designs, neurobiology, developmental psychopathology, and advanced computational methods such as machine learning. Core chapters examine significant statistical topics, for example missing data, causality, meta-analysis, latent variable analysis, and dyadic data analysis. A balanced overview of observational and experimental designs is also supplied, including preclinical research and intervention science. This is a foundational resource that supports the methodological training of the current and future generations of clinic

During the 1820s, British society saw transformations in technology, mobility, and consumerism that accelerated the spread of information. This timely study reveals how bestselling literature, popular theatre, and periodical journalism self-consciously experimented with new media. It presents an age preoccupied with improvisation and speculation – a mode of behaviour that dominated financial and literary markets, generating reflections on risk, agency, and the importance of public opinion. Print and Performance in the 1820s interprets a rich constellation of fictional texts and theatrical productions that gained popularity among middle-class metropolitan audiences through experiments with intersecting fantasy worlds and acutely described real worlds. Providing new contexts for figures such as Byron and Scott, and recovering the work of lesser-known contemporaries including Charles Mathews' character impersonations and the performances of celebrity improvvisatore Tommaso Sgricci, Angela

Networks are everywhere: networks of friends, transportation networks and the Web. Neurons in our brains and proteins within our bodies form networks that determine our intelligence and survival. This modern, accessible textbook introduces the basics of network science for a wide range of job sectors from management to marketing, from biology to engineering, and from neuroscience to the social sciences. Students will develop important, practical skills and learn to write code for using networks in their areas of interest - even as they are just learning to program with Python. Extensive sets of tutorials and homework problems provide plenty of hands-on practice and longer programming tutorials online further enhance students' programming skills. This intuitive and direct approach makes the book ideal for a first course, aimed at a wide audience without a strong background in mathematics or computing but with a desire to learn the fundamentals and applications of network science.

Learn about the state-of-the-art at the interface between information theory and data science with this first unified treatment of the subject. Written by leading experts in a clear, tutorial style, and using consistent notation and definitions throughout, it shows how information-theoretic methods are being used in data acquisition, data representation, data analysis, and statistics and machine learning. Coverage is broad, with chapters on signal acquisition, data compression, compressive sensing, data communication, representation learning, emerging topics in statistics, and much more. Each chapter includes a topic overview, definition of the key problems, emerging and open problems, and an extensive reference list, allowing readers to develop in-depth knowledge and understanding. Providing a thorough survey of the current research area and cutting-edge trends, this is essential reading for graduate students and researchers working in information theory, signal processing, machine le

Before the financial crisis, fiscal policy often played a secondary role to monetary policy, with the manipulation of interest rates to hit inflation targets being the main instrument of macroeconomic management. However, after the financial crisis and the subsequent euro crisis, fiscal policy has been brought back to the fore. In the past, the limited understanding of the effects of fiscal policy, neglect of monetary-fiscal interactions, faulty institutional set ups or ignorance of market expectations often led to bad policies. This book, written by a team of leading economists, seeks to address the current oversight of fiscal policy and to upgrade our understanding and conduct of fiscal policy, presenting a well-balanced diagnosis and offering several important lessons for future fiscal analysis and policymaking. It is an essential read for academics and graduate students focused on the current debate over fiscal policy, as well as policymakers working on day-to-day policy issues.

With this groundbreaking text, discover how wireless artificial intelligence (AI) can be used to determine position at centimeter level, sense motion and vital signs, and identify events and people. Using a highly innovative approach that employs existing wireless equipment and signal processing techniques to turn multipaths into virtual antennas, combined with the physical principle of time reversal and machine learning, it covers fundamental theory, extensive experimental results, and real practical use cases developed for products and applications. Topics explored include indoor positioning and tracking, wireless sensing and analytics, wireless power transfer and energy efficiency, 5G and next-generation communications, and the connection of large numbers of heterogeneous IoT devices of various bandwidths and capabilities. Demo videos accompanying the book online enhance understanding of these topics. Providing a unified framework for wireless AI, this is an excellent text for gradu

This friendly guide is the companion you need to convert pure mathematics into understanding and facility with a host of probabilistic tools. The book provides a high-level view of probability and its most powerful applications. It begins with the basic rules of probability and quickly progresses to some of the most sophisticated modern techniques in use, including Kalman filters, Monte Carlo techniques, machine learning methods, Bayesian inference and stochastic processes. It draws on thirty years of experience in applying probabilistic methods to problems in computational science and engineering, and numerous practical examples illustrate where these techniques are used in the real world. Topics of discussion range from carbon dating to Wasserstein GANs, one of the most recent developments in Deep Learning. The underlying mathematics is presented in full, but clarity takes priority over complete rigour, making this text a starting reference source for researchers and a readable overv

This friendly guide is the companion you need to convert pure mathematics into understanding and facility with a host of probabilistic tools. The book provides a high-level view of probability and its most powerful applications. It begins with the basic rules of probability and quickly progresses to some of the most sophisticated modern techniques in use, including Kalman filters, Monte Carlo techniques, machine learning methods, Bayesian inference and stochastic processes. It draws on thirty years of experience in applying probabilistic methods to problems in computational science and engineering, and numerous practical examples illustrate where these techniques are used in the real world. Topics of discussion range from carbon dating to Wasserstein GANs, one of the most recent developments in Deep Learning. The underlying mathematics is presented in full, but clarity takes priority over complete rigour, making this text a starting reference source for researchers and a readable overv

Trauma is a leading cause of death and disability around the world, and the leading cause of death in those aged under forty-five years. Conditions such as airway obstruction, hemorrhage, pneumothorax, tamponade, bowel rupture, vascular injury, and pelvic fracture can cause death if not appropriately diagnosed and managed. This essential book provides emergency physicians with an easy-to-use reference and source for traumatic injury evaluation and management in the emergency department. It covers approaches to common, life-threatening, and traumatic diseases in the emergency department, for use on shift and as a reference for further learning. Each chapter includes a succinct overview of common traumatic injuries, with evaluation and management pearls and pitfalls. Highly illustrated with images from one of the busiest trauma centers in the US, and featuring expert contributions from a diverse set of attending physicians, this is an essential text for all emergency medicine practitione

The tenth edition of Operating System Concepts has been revised to keep it fresh and up-to-date with contemporary examples of how operating systems function, and to improve learning and the student's experience with the material. It combines instruction on concepts with real-world applications so that students can understand the practical usage of the content. End-of-chapter practice exercises help to further reinforce important concepts.Each chapter also includes homework exercises and additional suggested readings on core topics. The text provides several example programs written in C and Java for use in several programming environments and a Linux Virtual Machine that can be run on Windows 10, Linux, or macOS.

Water resources are of enormous societal and ecological importance. In coastal areas, they are under ever greater pressure due to population growth, more affluent lifestyles, food production and the growing tourism industry. Changes to the coastal landscape, through urbanisation and land reclamation, and by natural processes such as climate change and sea level rise, modify the interaction between seawater and groundwater and put water resources at risk. This comprehensive volume covers both theory and practice of coastal hydrogeology. It discusses hydrochemistry; submarine groundwater discharge; groundwater management; palaeo-hydrology; land reclamation; climate change and sea level rise; and mathematical models of variable-density flow. With its up-to-date coverage and numerous case studies that illustrate practical implications, it is perfect for students, practitioners, managers and researchers who wish to develop an in-depth understanding of topics relevant to sustainably managing

The complex healthcare needs of pregnant patients, where care is tailored to not one but two patients, pose specific challenges to anesthesiologists. This book provides concise, case-based discussion on the clinical scenarios and challenges faced in the provision of anesthesia and pain relief for expectant mothers. In the style of problem-based learning, each case is presented as a short scenario, followed by discussion of the causes, risk factors, management and controversies involved. The textbook features a wide range of cases, from common clinical scenarios that are experienced in day-to-day practice to the rare but significant pathologies less familiar to most clinicians. With a global base of contributors, the book is relevant to practice across the world. The concise format supports both trainee anesthesiologists in their initial experiences of obstetrics and exam preparation, and experienced clinicians in need of a reliable, quick-reference text.

This textbook presents key theoretical approaches to understanding issues of sustainability and environmental management, perfectly bridging the gap between engineering and environmental science. It begins with the fundamentals of environmental modelling and toxicology, which are then used to discuss qualitative and quantitative risk assessment methods, and environmental assessments of product design. It discusses how business and government can work towards sustainability, focusing on managerial and legal tools, before considering ethics and how decisions on environmental management can be made. Students will learn quantitative methods while also gaining an understanding of qualitative, legal, and ethical aspects of sustainability. Practical applications are included throughout, and there are study questions at the end of each chapter. PowerPoint slides and jpegs of all the figures in the book are provided online. This is the perfect textbook on environmental studies for engineering a

Recent years have witnessed an explosion in the volume and variety of data collected in all scientific disciplines and industrial settings. Such massive data sets present a number of challenges to researchers in statistics and machine learning. This book provides a self-contained introduction to the area of high-dimensional statistics, aimed at the first-year graduate level. It includes chapters that are focused on core methodology and theory - including tail bounds, concentration inequalities, uniform laws and empirical process, and random matrices - as well as chapters devoted to in-depth exploration of particular model classes - including sparse linear models, matrix models with rank constraints, graphical models, and various types of non-parametric models. With hundreds of worked examples and exercises, this text is intended both for courses and for self-study by graduate students and researchers in statistics, machine learning, and related fields who must understand, apply, and ad

This textbook presents key theoretical approaches to understanding issues of sustainability and environmental management, perfectly bridging the gap between engineering and environmental science. It begins with the fundamentals of environmental modelling and toxicology, which are then used to discuss qualitative and quantitative risk assessment methods, and environmental assessments of product design. It discusses how business and government can work towards sustainability, focusing on managerial and legal tools, before considering ethics and how decisions on environmental management can be made. Students will learn quantitative methods while also gaining an understanding of qualitative, legal, and ethical aspects of sustainability. Practical applications are included throughout, and there are study questions at the end of each chapter. PowerPoint slides and jpegs of all the figures in the book are provided online. This is the perfect textbook on environmental studies for engineering a

With the increasing public interest in artificial intelligence (AI), there is also increasing interest in learning about the benefits that AI can deliver to society. This book focuses on research advances in AI that benefit the conservation of wildlife, forests, coral reefs, rivers, and other natural resources. It presents how the joint efforts of researchers in computer science, ecology, economics, and psychology help address the goals of the United Nations' 2030 Agenda for Sustainable Development. Written at a level accessible to conservation professionals and AI researchers, the book offers both an overview of the field and an in-depth view of how AI is being used to understand patterns in wildlife poaching and enhance patrol efforts in response, covering research advances, field tests and real-world deployments. The book also features efforts in other major conservation directions, including protecting natural resources, ecosystem monitoring, and bio-invasion management through the

If you’re a developer familiar with AI, machine learning, and computer vision, this practical book provides you with a foundational understanding of augmented and virtual reality functions. AR a