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Active Credit Portfolio Management in Practice
State-of-the-art techniques and tools needed to facilitate effective credit portfolio management and robust quantitative credit analysis Filled with in-depth insights and expert advice, Active Credit Portfolio Management in Practice serves as a comprehensive introduction to both the theory and real-world practice of credit portfolio management. The authors have written a text that is technical enough both in terms of background and implementation to cover what practitioners and researchers need for actually applying these types of risk management tools in large organizations but which at the same time, avoids technical proofs in favor of real applications. Throughout this book, readers will ...
Credit Risk Management
The importance of managing credit and credit risks carefully and appropriately cannot be overestimated. The very success or failure of a bank and the banking industry in general may well depend on how credit risk is handled. Banking professionals must be fully versed in the risks associated with credit operations and how to manage those risks. This up-to-date volume is an invaluable reference and study tool that delves deep into issues associated with credit risk management. Credit Risk Management from the Hong Kong Institute of Bankers (HKIB)discusses the various ways through which banks manage risks. Essential for candidates studying for the HKIB Associateship Examination, it can also help those who want to acquire a deeper understanding of how and why banks make decisions and set up processes that lower their risk. Topics covered in this book include: Active credit portfolio management Risk management, pricing, and capital adequacy Capital requirements for banks Approaches to credit risk management Structural models and probability of default Techniques to determine loss given default Derivatives and structured products
Healthcare Finance
Why healthcare finance? -- From the laboratory to the patient -- Present value relations -- Evaluating business opportunities -- Valuing bonds -- Valuing stocks -- Portfolio management and the cost of capital -- Therapeutic development and clinical trials -- Decision trees and real options -- Monte Carlo simulation -- Healthcare analytics -- Biotech venture capital -- Securitizing biomedical assets -- Pricing, value, and ethics -- Epilogue : a case study pf royalty pharma.
Credit Securitisations and Derivatives
A comprehensive resource providing extensive coverage of the state of the art in credit secruritisations, derivatives, and risk management Credit Securitisations and Derivatives is a one-stop resource presenting the very latest thinking and developments in the field of credit risk. Written by leading thinkers from academia, the industry, and the regulatory environment, the book tackles areas such as business cycles; correlation modelling and interactions between financial markets, institutions, and instruments in relation to securitisations and credit derivatives; credit portfolio risk; credit portfolio risk tranching; credit ratings for securitisations; counterparty credit risk and clearing of derivatives contracts and liquidity risk. As well as a thorough analysis of the existing models used in the industry, the book will also draw on real life cases to illustrate model performance under different parameters and the impact that using the wrong risk measures can have.
Annual Report
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Signal Processing and Machine Learning for Biomedical Big Data
Within the healthcare domain, big data is defined as any ``high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to large cohorts, in relation to their health and wellness status, at one or several time points.'' Such data is crucial because within it lies vast amounts of invaluable information that could potentially change a patient's life, opening doors to alternate therapies, drugs, and diagnostic tools. Signal Processing and Machine Learning for Biomedical Big Data thus discusses modalities; the numerous ways in which this data is captured via sensors; and various sample rates and dimensionalities. Capturing, analyzin...
