Machine Learning for Financial Risk Management with Python

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

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems

Praise for Enterprise Risk Management and COSO: A Guide for Directors, Executives, and Practitioners "Enterprise Risk Management and COSO is a comprehensive reference book that presents core manageme

The great financial crisis of the first decade of the 21st century is due in large part to a failure of the common conceptual understanding of financial markets and modern risk management, suggests We

Former Federal Reserve chair Greenspan recently said that the risk management paradigm is broken; thus our understanding of financial regulation no longer makes sense. More generally, the current fina

Defining the fundamentals of building a risk management plan, Applied Risk Management in Agriculture uses strategic management to organize the process of risk management. A time-tested procedure insid

Corporate Financial Analysis with MicrosoftR ExcelR visualizes spreadsheets as an effective management tool both for financial analysis and for coordinating its results and actions with marketing, sal

Confused about financial management? Problem solved. Schaum's Outline of Financial Management provides a succinct review of all financial management concepts in topics such as financial forecasting, p

An introduction to machine learning methods and their applications to problems in bioinformatics Machine learning techniques are increasingly being used to address problems in computational biology a

Written for enterprise risk management (ERM) practitioners who recognize ERM?s value to their organization, Enterprise Risk Management: A Methodology for Achieving Strategic Objectives thoroughly exam

Praise for Fair Lending ComplianceIntelligence and Implications for Credit Risk Management "Brilliant and informative. An in-depth look at innovative approaches to credit risk management written by

Forensic Assessment of Violence Risk: A Guide for Risk Assessment and Risk Management provides both a summary of research to date and an integrated model for mental health professionals conducting ris

You don’t need to be a financial wizard to ensure the future success of your design firm! An accessible guide to financial management, Financial Management for Design Professionals is written f

Suicide Risk Management: A Manual for Health Professionals provides health professionals with the tools to recognize, assess, and manage the suicidal or potentially suicidal patient and presents impor

The first book to comprehensively discuss both governmental and nonprofit financial management! Governmental and Nonprofit Financial Management makes it easy for both nonprofit and governmental manage

Risk Management for Agriculture addresses the issue of price risk as a management function versus a marketing function. Price risks impact not only the marketing of a product but the cash flow and t

Julia Graham and David Kaye, two globally recognized risk management experts with experience in 50 countries, were among the first to recognize the interrelationship of Risk Management and Business Co

Risk management is no longer confined solely to risk management specialists. Stakeholders ranging from employees to investors must understand how to quantify the tradeoffs of risk against the potentia

"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

The implementation of sound quantitative risk models is a vital concern for all financial institutions, and this trend has accelerated in recent years with regulatory processes such as Basel II. This

The market for credit derivatives--financial instruments designed to transfer credit risk from one party to another--has grown exponentially in recent years, with volume expected to reach more than $4

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems

During the last decade, financial models based on jump processes have acquired increasing popularity in risk management and option pricing. Much has been published on the subject, but the technical n

Machine Learning: Discriminative and Generative covers the main contemporary themes and tools in machine learning ranging from Bayesian probabilistic models to discriminative support-vector machines.

Credit risk evaluation is as old as commerce itself. Processes have been refined over centuries based on cumulative experience, judgment and learning. The rapid development of financial markets howe

The WHO CVD-Risk Management package contains a variety of components to guide healthcare providers and health systems, even those with very minimal resources, to more effective CVD risk management thr

This concise but well-developed book covers financial management with an international focus. Noted corporate finance specialist Jack Broyles here assists operating managers in attaining the financial

In an age where companies and financial institutions are keenly focused on managing the financial risk of their operations, the implementation of quantitative methods and models has been of tremendous

Risk and Value Management, the fifth release in the Construction Companion series, offers an introductory toolbox of techniques for managing risk and value in construction projects for architects and

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.

Forest management typically deals with the challenges of uncertainty and multiple risk, but application of risk analysis in this field is not commonplace. Included here are concepts, methods, and case

Operational risk is emerging as the third leg of an institutional risk strategy for financial institutions. Now recognized as a potential source of financial waste, operational risk has become the sub

Bank Valuation & Value-Based Management provides bankers, bank regulators, auditors, and risk managers with foundational concepts and practical tools for effectively managing a bank. An expert i