Navigating Higher Rates Volatility And Liquidity Crises
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Navigating Higher Rates, Volatility, and Liquidity Crises
Author: Andreas Dombret
language: en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date: 2024-12-16
When central banks started raising interest rates in reaction to the spike in inflation which followed the COVID-19 epidemic, they put an end to a more than a decade of "low for longer" interest rates to which the financial sector had adjusted their balance sheets and business models. The resulting "new monetary order" has required all parts of the financial sector to make serious adjustments. The fate of the US and Swiss banks caught up in the March 2023 "bank turmoil" can be seen as a cautionary tale for those who do not adjust in a timely fashion. This book reviews how the financial sector evolved during "low for longer" and examines how monetary policy, financial regulation and supervision, the banking and the non-bank financial sectors can be expected to evolve under this new order.
Finance Essentials
Author: Scott Moeller
language: en
Publisher: Bloomsbury Publishing
Release Date: 2012-04-26
Collated by Scott Moeller of Cass Business School, this collection brings together the informative articles a budding finance practitioner needs to operate effectively in today's corporate environment. Bringing together core finance knowledge and cutting-edge research topics in an engaging and effective way, this text is the ideal companion for all practitioners and students of finance. You will find insights into the practical applications of theory in key areas such as balance sheets and cash flow, financial regulation and compliance, funding and investment, governance and ethics, mergers and acquisitions, and operations and performance. Contributors to this collection include some of the leading experts in their respective fields: Aswath Damodaran, Harold Bierman, Jr, Andreas Jobst, Frank J. Fabozzi, Ian Bremmer, Javier Estrada, Marc J. Epstein, Henrik Cronqvist, Daud Vicary Abdullah, Meziane Lasfer, Dean Karlan, Norman Marks, Seth Armitage, and many others. In this collection you will discover: * Over 80 best-practice articles, providing the best guidance on issues ranging from risk management and capital structure optimization through to market responses to M&A transactions and general corporate governance * Over 65 checklists forming step-by-step guides to essential tasks, from hedging interest rates to calculating your total economic capital * 55 carefully selected calculations and ratios to monitor firms' financial health * A fully featured business and finance dictionary with over 5,000 definitions
Liquidity Dynamics and Risk Modeling
Author: Mazin A. M. Al Janabi
language: en
Publisher: Springer Nature
Release Date: 2024-12-09
This book presents a high-quality contribution to the applications of modern financial algorithms for liquidity risk management and its practical uses and applications to investable portfolios and mutual funds. It brings together the latest thinking on the emerging topic of contemporary liquidity risk estimations and management and includes principles, reviews, examples, and concrete financial markets applications to trading and investment portfolios. Furthermore, it explores research directions of liquidity risk management using modified Liquidity-Adjusted Value-at-Risk (L-VaR) models with the application of machine learning optimization algorithms. The book presents specific self-contained use-cases throughout, showing practical applications of the concepts discussed and providing further directions for researchers and financial markets participants. The book draws practical insights from personal experiences and applies specific examples (with the use of real-world case studies and analysis) about how the modeling techniques and machine learning optimization algorithms could address specific theoretical and practical issues of liquidity risk management and coherent asset allocation in trading and investment portfolios. It will be of interest to researchers, students, and practitioners of risk management, portfolio management, and machine learning.