An advanced method for financial institutions to optimize Asset Liability Management for maximized return and minimized risk Financial institutions today are facing daunting regulatory and economic challenges. As they manage bank regulation and competition, institutions are also optimizing their Asset Liability Management (ALM) operations. The function of the ALM unit today goes beyond risk management related to the banking book into managing regulatory capital and positioning the balance sheet to maximize profit. Asset Liability Management Optimization: A Practitioner's Guide to Balance Sheet Management and Remodelling offers a step-by-step process for modeling and reshaping a bank's balance sheet. Based on the author's extensive research, it describes how to apply a quantifiable optimization method to help maximize asset return and minimize funding cost in the banking book. ALM ranks as a key component of any financial institution's overall operating strategy. Now, financial professionals can use an advanced solution for optimizing ALM. This book takes a closer look at the evolving role of the ALM function and the target position of the banking book. It provides strategies for active management, structuring, and hedging of a bank balance sheet, while also exploring additional topics related to ALM. A description of the Funds Transfer Pricing (FTP) process related to a bank’s target position Detailed examinations of interest rate risk in the banking book (IRRBB) Discussion of Basel III regulatory requirements and maturity gap analysis Overview of customer behavior, along with its impact on interest rate and liquidity risk Practical spreadsheet models (NII sensitivity and EVE volatility IRRBB model, simplified optimization model for minimization of average funding cost for a bank and an example of behavioral model for Non-Maturing Deposits) Explorations of model risk, sensitivity analysis, and case studies The optimization techniques found in Asset Liability Management Optimization can prove vital to financial professionals who are tasked with maximizing asset return and reducing funding costs as a critical part of business objectives.

Introduces practical approaches for optimizing management and hedging of Interest Rate Risk in the Banking Book (IRRBB) driven by fast evolving regulatory landscape and market expectations. Interest rate risk in the banking book (IRRBB) gained its importance through the regulatory requirements that have been growing and guiding the banking industry for the last couple of years. The importance of IRRBB is shifting for banks, away from ‘just’ a regulatory requirement to having an impact on the overall profitability of a financial institution. Interest Rate Risk in the Banking Book sheds light on the best practices for managing this importance risk category and provides detailed analysis of the hedging strategies, practical examples, and case studies based on the author’s experience. This handbook is rich in practical insights on methodological approach and contents of ALCO report, IRRBB policy, ICAAP, Risk Appetite Statement (RAS) and model documentation. It is intended for the Treasury, Risk and Finance department and is helpful in improving and optimizing their IRRBB framework and strategy. By the end of this IRRBB journey, the reader will be equipped with all the necessary tools to build a proactive and compliant framework within a financial institution. Gain an updated understanding of the evolving regulatory landscape for IRRBB Learn to apply maturity gap analysis, sensitivity analysis, and the hedging strategy in banking contexts • Understand how customer behavior impacts interest rate risk and how to manage the consequences Examine case studies illustrating key IRRBB exposures and their implications Written by London market risk expert Beata Lubinska, Interest Rate Risk in the Banking Book is the authoritative resource on this evolving topic.

Recent years have shown an increase in development and acceptance of quantitative methods for asset and liability management strategies. This book presents state of the art quantitative decision models for three sectors: pension funds, insurance companies and banks, taking into account new regulations and the industries risks.

Banks are a vital part of the global economy, and the essence of banking is asset-liability management (ALM). This book is a comprehensive treatment of an important financial market discipline. A reference text for all those involved in banking and the debt capital markets, it describes the techniques, products and art of ALM. Subjects covered include bank capital, money market trading, risk management, regulatory capital and yield curve analysis. Highlights of the book include detailed coverage of: Liquidity, gap and funding risk management Hedging using interest-rate derivatives and credit derivatives Impact of Basel II Securitisation and balance sheet management Structured finance products including asset-backed commercial paper, mortgage-backed securities, collateralised debt obligations and structured investment vehicles, and their role in ALM Treasury operations and group transfer pricing. Concepts and techniques are illustrated with case studies and worked examples. Written in accessible style, this book is essential reading for market practitioners, bank regulators, and graduate students in banking and finance. Companion website features online access to software on applications described in the book, including a yield curve model, cubic spline spreadsheet calculator and CDO waterfall model.

Asset-Liability and Liquidity Management distils the author’s extensive experience in the financial industry, and ALM in particular, into concise and comprehensive lessons. Each of the topics are covered with a focus on real-world applications, based on the author’s own experience in the industry. The author is the Vice President of Treasury Modeling and Analytics at American Express. He is also an adjunct Professor at New York University, teaching a variety of analytical courses. Learn from the best as Dr. Farahvash takes you through basic and advanced topics, including: The fundamentals of analytical finance Detailed explanations of financial valuation models for a variety of products The principle of economic value of equity and value-at-risk The principle of net interest income and earnings-at-risk Liquidity risk Funds transfer pricing A detailed Appendix at the end of the book helps novice users with basic probability and statistics concepts used in financial analytics.

In spite of theoretical benefits, Markowitz mean-variance (MV) optimized portfolios often fail to meet practical investment goals of marketability, usability, and performance, prompting many investors to seek simpler alternatives. Financial experts Richard and Robert Michaud demonstrate that the limitations of MV optimization are not the result of conceptual flaws in Markowitz theory but unrealistic representation of investment information. What is missing is a realistic treatment of estimation error in the optimization and rebalancing process. The text provides a non-technical review of classical Markowitz optimization and traditional objections. The authors demonstrate that in practice the single most important limitation of MV optimization is oversensitivity to estimation error. Portfolio optimization requires a modern statistical perspective. Efficient Asset Management, Second Edition uses Monte Carlo resampling to address information uncertainty and define Resampled Efficiency (RE) technology. RE optimized portfolios represent a new definition of portfolio optimality that is more investment intuitive, robust, and provably investment effective. RE rebalancing provides the first rigorous portfolio trading, monitoring, and asset importance rules, avoiding widespread ad hoc methods in current practice. The Second Edition resolves several open issues and misunderstandings that have emerged since the original edition. The new edition includes new proofs of effectiveness, substantial revisions of statistical estimation, extensive discussion of long-short optimization, and new tools for dealing with estimation error in applications and enhancing computational efficiency. RE optimization is shown to be a Bayesian-based generalization and enhancement of Markowitz's solution. RE technology corrects many current practices that may adversely impact the investment value of trillions of dollars under current asset management. RE optimization technology may also be useful in other financial optimizations and more generally in multivariate estimation contexts of information uncertainty with Bayesian linear constraints. Michaud and Michaud's new book includes numerous additional proposals to enhance investment value including Stein and Bayesian methods for improved input estimation, the use of portfolio priors, and an economic perspective for asset-liability optimization. Applications include investment policy, asset allocation, and equity portfolio optimization. A simple global asset allocation problem illustrates portfolio optimization techniques. A final chapter includes practical advice for avoiding simple portfolio design errors. With its important implications for investment practice, Efficient Asset Management 's highly intuitive yet rigorous approach to defining optimal portfolios will appeal to investment management executives, consultants, brokers, and anyone seeking to stay abreast of current investment technology. Through practical examples and illustrations, Michaud and Michaud update the practice of optimization for modern investment management.

This book introduces ALM in the context of banks and insurance companies. Although this strategy has a core of fundamental frameworks, models may vary between banks and insurance companies because of the different risks and goals involved. The authors compare and contrast these methodologies to draw parallels between the commonalities and divergences of these two services and thereby provide a deeper understanding of ALM in general.