Risk model validation is an emerging and important area of research, and has arisen because of Basel I and II. These regulatory initiatives require trading institutions and lending institutions to compute their reserve capital in a highly analytic way, based on the use of internal risk models. It is part of the regulatory structure that these risk models be validated both internally and externally, and there is a great shortage of information as to best practise. Editors Christodoulakis and Satchell collect papers that are beginning to appear by regulators, consultants, and academics, to provide the first collection that focuses on the quantitative side of model validation. The book covers the three main areas of risk: Credit Risk and Market and Operational Risk.*Risk model validation is a requirement of Basel I and II *The first collection of papers in this new and developing area of research *International authors cover model validation in credit, market, and operational risk

The risk of counterparty default in banking, insurance, institutional, and pension-fund portfolios is an area of ongoing and increasing importance for finance practitioners. It is, unfortunately, a topic with a high degree of technical complexity. Addressing this challenge, this book provides a comprehensive and attainable mathematical and statistical discussion of a broad range of existing default-risk models. Model description and derivation, however, is only part of the story. Through use of exhaustive practical examples and extensive code illustrations in the Python programming language, this work also explicitly shows the reader how these models are implemented. Bringing these complex approaches to life by combining the technical details with actual real-life Python code reduces the burden of model complexity and enhances accessibility to this decidedly specialized field of study. The entire work is also liberally supplemented with model-diagnostic, calibration, and parameter-estimation techniques to assist the quantitative analyst in day-to-day implementation as well as in mitigating model risk. Written by an active and experienced practitioner, it is an invaluable learning resource and reference text for financial-risk practitioners and an excellent source for advanced undergraduate and graduate students seeking to acquire knowledge of the key elements of this discipline.

Provides comprehensive coverage on recidivism risk/needs assessment tools Correctional and healthcare professionals around the world utilize structured instruments referred to as risk/needs assessment tools to predict the likelihood that an offender will recidivate. Such tools have been found to provide accurate and reliable evaluations and are widely used to assess, manage, and monitor offenders both institutionally as well as in the community. By identifying offenders in need of different levels of intervention, examining causal risk factors, and individualizing case management plans, risk/needs assessment tools have proven invaluable in addressing the public health issue of recidivism. Recidivism Risk/Needs Assessment Tools brings together the developers of the most commonly-used risk/needs assessment tools to provide a comprehensive overview of their development, peer-reviewed research literature, and practical application. Written by the leading professionals in the field of risk/needs assessment, the book provides chapters on: Recidivism Risk Assessment in the 21st Century; Performance of Recidivism Risk Assessment Instruments in Correctional Settings; Correctional Offender Management Profiles for Alternative Sanctions (COMPAS); the Federal Post-Conviction Risk Assessment Instrument; the Inventory of Offender Risks, Needs, and Strengths (IORNS); the Level of Service (LS) Instruments; the Ohio Risk Assessment System (ORAS); the Self-Appraisal Questionnaire (SAQ); the Service Planning Instrument (SPIn); the Static Risk Offender Needs Guide-Revised (STRONG-R); the Offender Group Reconviction Scale (OGRS); the Forensic Operationalized Therapy/Risk Evaluation System (FOTRES); the RisCanvi; and more. Systematically identifies currently-validated recidivism risk/needs assessment tools Reviews research on recidivism risk/needs assessment tools used internationally Each chapter presents sufficient detail to decide whether a given recidivism risk/needs assessment tool is right for your practice Recidivism Risk/Needs Assessment Tools is ideal for correctional, probation and parole, and behavioral health professionals.

A comprehensive look at the tools and techniques used in quantitative equity management Some books attempt to extend portfolio theory, but the real issue today relates to the practical implementation of the theory introduced by Harry Markowitz and others who followed. The purpose of this book is to close the implementation gap by presenting state-of-the art quantitative techniques and strategies for managing equity portfolios. Throughout these pages, Frank Fabozzi, Sergio Focardi, and Petter Kolm address the essential elements of this discipline, including financial model building, financial engineering, static and dynamic factor models, asset allocation, portfolio models, transaction costs, trading strategies, and much more. They also provide ample illustrations and thorough discussions of implementation issues facing those in the investment management business and include the necessary background material in probability, statistics, and econometrics to make the book self-contained. Written by a solid author team who has extensive financial experience in this area Presents state-of-the art quantitative strategies for managing equity portfolios Focuses on the implementation of quantitative equity asset management Outlines effective analysis, optimization methods, and risk models In today's financial environment, you have to have the skills to analyze, optimize and manage the risk of your quantitative equity investments. This guide offers you the best information available to achieve this goal.

Recently, considerable attention has been placed on the development and application of tools useful for the analysis of the high-dimensional and/or high-frequency datasets that now dominate the landscape. The purpose of this Special Issue is to collect both methodological and empirical papers that develop and utilize state-of-the-art econometric techniques for the analysis of such data.

The composition of portfolios is one of the most fundamental and important methods in financial engineering, used to control the risk of investments. This book provides a comprehensive overview of statistical inference for portfolios and their various applications. A variety of asset processes are introduced, including non-Gaussian stationary processes, nonlinear processes, non-stationary processes, and the book provides a framework for statistical inference using local asymptotic normality (LAN). The approach is generalized for portfolio estimation, so that many important problems can be covered. This book can primarily be used as a reference by researchers from statistics, mathematics, finance, econometrics, and genomics. It can also be used as a textbook by senior undergraduate and graduate students in these fields.