Machine Learning for Financial Risk Management with Python

The importance of proper assessment and management of counterparty risk became apparent during the recent financial crisis. This book provides a theoretically sound presentation of advanced mathematic

Agrawal's Information Security and Risk Management, with a technical rather than managerial focus, gives readers the knowledge and skills needed to compete for and succeed in information security role

This volume provides an introduction for flood risk management practitioners, up-to-date methods for analysis of uncertainty and its use in risk-based decision making. It addresses decision making fo

Praise for Energy and Power Risk Management "Energy and Power Risk Management identifies and addresses the key issues in the development of the turbulent energy industry and the challenges it poses

The book adopts a tutorial-based approach to introduce the user to Scikit-learn. If you are a programmer who wants to explore machine learning and data-based methods to build intelligent applications

A 'handbook' for anyone with a professional interest in the regulation of chemicals Provides a practical guide and overview to chemicals risk assessment and risk management Explains the scientific

"Multinational Financial Management, 10th Edition provides corporate managers with a conceptual framework within which the key financial decisions of the multinational firm can be analyzed. It contain

The field of Corporate Finance has developed into a fairly complex one from its origins focussed on a company's business and financial needs (financing, risk management, capitalization and budgeting).

An easy to implement, practical, and proven risk management methodology for project managers and decision makersDrawing from the author's work with several major and mega capital projects for Royal Du

The Handbook on Systemic Risk, written by experts in the field, provides researchers with an introduction to the multifaceted aspects of systemic risks facing the global financial markets. The Handbook explores the multidisciplinary approaches to analyzing this risk, the data requirements for further research, and the recommendations being made to avert financial crisis. The Handbook is designed to encourage new researchers to investigate a topic with immense societal implications as well as to provide, for those already actively involved within their own academic discipline, an introduction to the research being undertaken in other disciplines. Each chapter in the Handbook will provide researchers with a superior introduction to the field and with references to more advanced research articles. It is the hope of the editors that this Handbook will stimulate greater interdisciplinary academic research on the critically important topic of systemic risk in the global financial markets.

A comprehensive guide to risk management for fund managers and investorsIdeally, all investors attempt to maximize expected returns while minimizing risk. But in the real world, many lack the strate

If you’ve been tasked with building a team to handle risk management for online payments (RMP), this practical introduction provides a framework for choosing the technologies and personnel you need. A

Decision Support Systems for Risk-Based Management of Contaminated Sites addresses decision making in environmental risk management for contaminated sites, focusing on the potential role of decision s

The "Top 25 Risk Management KPIs of 2011-2012" report provides insights into the state of risk management performance measurement today by listing and analyzing the most visited KPIs for this industry

Machine learning is a novel discipline concerned with the analysis of large and multiple variables data. It involves computationally intensive methods, like factor analysis, cluster analysis, and disc

Management of the Patient at High Risk for Breast Cancer provides a state-of-the art review of patients who are at high risk for breast cancer, how to identify them, the tools available for risk asses

A comprehensive guide to credit risk management The Handbook of Credit Risk Management presents a comprehensive overview of the practice of credit risk management for a large institution. It is a guid

Create your own natural language training corpus for machine learning. Whether you’re working with English, Chinese, or any other natural language, this hands-on book guides you through a proven annot

As one of the most comprehensive machine learning texts around, this book does justice to the field's incredible richness, but without losing sight of the unifying principles. Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook.

As one of the most comprehensive machine learning texts around, this book does justice to the field's incredible richness, but without losing sight of the unifying principles. Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook.

For undergraduate and graduate students enrolled in an international finance course. An approach that blends theory and practice with real-world data analysis. International Financial Management seam

Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn. This book introduces theories, methods and applications of density ratio estimation, which is a newly emerging paradigm in the machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier detection, dimensionality reduction, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation of probability density ratios. The authors offer a comprehensive introduction of various density ratio estimators including methods via density estimation, moment matching, probabilistic classification, density fitting and density ratio fitting, as well as describing how these can be applied to machine learning. The book provides mathematical theories for density ratio estimation including parametric and non-parametric conve

“Practical Applications of Evolutionary Computation to Financial Engineering” presents the state of the art techniques in Financial Engineering using recent results in Machine Learning and Evolutionar

This book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms. Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset sizes, in others by model complexity or by real-time performance requirements. Making task-appropriate algorithm and platform choices for large-scale machine learning requires understanding the benefits, trade-offs and constraints of the available options. Solutions presented in the book cover a range of parallelization platforms from FPGAs and GPUs to multi-core systems and commodity clusters, concurrent programming frameworks including CUDA, MPI, MapReduce and DryadLINQ, and learning settings (supervised, unsupervised, semi-supervised and online learning). Extensive coverage of parallelization of boosted trees, SVMs, spectral clustering, belief propagation and other popular learning algo

"Machine Learning and Data Mining for Computer Security" provides an overview of the current state of research in machine learning and data mining as it applies to problems in computer security. This

In machine learning applications, practitioners must take into account the cost associated with the algorithm. These costs include: Cost of acquiring training dataCost of data annotation/labeling and

An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning

The Operational Risk Handbook for Financial Companies is a groundbreaking new book. It seeks to apply for the first time a range of proven operational risk techniques from other industries and discipl

The aim of the book is to provide an overview of risk management in life insurance companies. The focus is twofold: (1) to provide a broad view of the different topics needed for risk management and (

With the world's financial architecture having been revealed in the 2008 financial meltdown as insufficient for safely managing risk and the world's regulators as failing to have recognized or address

Gain a focused understanding of today?s corporate finance and financial management with the market-leading approach in Brigham/Houston?s FUNDAMENTALS OF FINANCIAL MANAGEMENT, CONCISE EDITION, 7E. Thi

Activate learning with Warren/Reeve/Duchac's Corporate Financial Accounting, 11e! Corporate Financial Accounting offers students clear guidance to complete homework with an efficient presentation for

Once you've come to grips with the core Python language, learning how to build Python applications presents a far more interesting challenge. Many critics consider this classic book, now updated for P

Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in r

Taking into account the standards of the Basel Accord, Operational Risk Modelling and Management presents a simulation model for generating the loss distribution of operational risk. It also examines

Continuing its superiority in the health care risk management field, this sixth edition of The Risk Management Handbook for Health Care Organizations is written by the key practitioners and consultan

The use of derivative products in risk management has spread from commodities, stocks and fixed income items, to such virtual commodities as energy, weather and bandwidth. All this can give rise to so-called volatility and there has been a consequent development in formal risk management techniques to cover all types of risk: market, credit, liquidity, etc. One of these techniques, Value at Risk, was developed specifically to help manage market risk over short periods. Its success led, somewhat controversially, to its take up and extension to credit risk over longer time-scales. This extension, ultimately not successful, led to the collapse of a number of institutions. The present book, which was originally published in 2002, by some of the leading figures in risk management, examines the complex issues that concern the stability of the global financial system by presenting a mix of theory and practice.

Gain an understanding of the financial theory that is essential for developing and implementing effective financial strategies in business today. FINANCIAL MANAGEMENT: THEORY AND PRACTICE, 13E strike

Essential insights on the various aspects of enterprise risk management If you want to understand enterprise risk management from some of the leading academics and practitioners of this exciting new m

Decision Support Systems for Risk-Based Management of Contaminated Sites addresses decision making in environmental risk management for contaminated sites, focusing on the potential role of decision s