Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
71
result(s) for
"Financial risk management--Mathematical models"
Sort by:
Bayesian Risk Management
A risk measurement and management framework that takes model risk seriously
Most financial risk models assume the future will look like the past, but effective risk management depends on identifying fundamental changes in the marketplace as they occur. Bayesian Risk Management details a more flexible approach to risk management, and provides tools to measure financial risk in a dynamic market environment. This book opens discussion about uncertainty in model parameters, model specifications, and model-driven forecasts in a way that standard statistical risk measurement does not. And unlike current machine learning-based methods, the framework presented here allows you to measure risk in a fully-Bayesian setting without losing the structure afforded by parametric risk and asset-pricing models.
* Recognize the assumptions embodied in classical statistics
* Quantify model risk along multiple dimensions without backtesting
* Model time series without assuming stationarity
* Estimate state-space time series models online with simulation methods
* Uncover uncertainty in workhorse risk and asset-pricing models
* Embed Bayesian thinking about risk within a complex organization
Ignoring uncertainty in risk modeling creates an illusion of mastery and fosters erroneous decision-making. Firms who ignore the many dimensions of model risk measure too little risk, and end up taking on too much. Bayesian Risk Management provides a roadmap to better risk management through more circumspect measurement, with comprehensive treatment of model uncertainty.
eBook
Multi-asset risk modeling : techniques for a global economy in an electronic and algorithmic trading era
This title describes the latest and most advanced risk modeling techniques for equities, debt, fixed income, futures and derivatives, commodities, and foreign exchange, as well as advanced algorithmic and electronic risk management. Beginning with the fundamentals of risk mathematics and quantitative risk analysis, the book moves on to discuss the laws in standard models that contributed to the 2008 financial crisis and talks about current and future banking regulation.
Book
Future perspectives in risk models and finance
This book provides a perspective on a number of approaches to financial modelling and risk management. It examines both theoretical and practical issues. Theoretically, financial risks models are models of a real and a financial \"uncertainty\", based on both common and private information and economic theories defining the rules that financial markets comply to. Financial models are thus challenged by their definitions and by a changing financial system fueled by globalization, technology growth, complexity, regulation and the many factors that contribute to rendering financial processes to be continuously questioned and re-assessed. The underlying mathematical foundations of financial risks models provide future guidelines for risk modeling. The bookâءءs chapters provide selective insights and developments that can contribute to better understand the complexity of financial modelling and its ability to bridge financial theories and their practice.
Book
The basics of financial econometrics : tools, concepts, and asset management applications
An accessible guide to the growing field of financial econometrics
As finance and financial products have become more complex, financial econometrics has emerged as a fast-growing field and necessary foundation for anyone involved in quantitative finance. The techniques of financial econometrics facilitate the development and management of new financial instruments by providing models for pricing and risk assessment. In short, financial econometrics is an indispensable component to modern finance.
The Basics of Financial Econometrics covers the commonly used techniques in the field without using unnecessary mathematical/statistical analysis. It focuses on foundational ideas and how they are applied. Topics covered include: regression models, factor analysis, volatility estimations, and time series techniques.
* Covers the basics of financial econometrics—an important topic in quantitative finance
* Contains several chapters on topics typically not covered even in basic books on econometrics such as model selection, model risk, and mitigating model risk
Geared towards both practitioners and finance students who need to understand this dynamic discipline, but may not have advanced mathematical training, this book is a valuable resource on a topic of growing importance.
eBook
Bubble Value at Risk
Introduces a powerful new approach to financial risk modeling with proven strategies for its real-world applications
The 2008 credit crisis did much to debunk the much touted powers of Value at Risk (VaR) as a risk metric. Unlike most authors on VaR who focus on what it can do, in this book the author looks at what it cannot. In clear, accessible prose, finance practitioners, Max Wong, describes the VaR measure and what it was meant to do, then explores its various failures in the real world of crisis risk management. More importantly, he lays out a revolutionary new method of measuring risks, Bubble Value at Risk, that is countercyclical and offers a well-tested buffer against market crashes.
* Describes Bubble VaR, a more macro-prudential risk measure proven to avoid the limitations of VaR and by providing a more accurate risk exposure estimation over market cycles
* Makes a strong case that analysts and risk managers need to unlearn our existing \"science\" of risk measurement and discover more robust approaches to calculating risk capital
* Illustrates every key concept or formula with an abundance of practical, numerical examples, most of them provided in interactive Excel spreadsheets
* Features numerous real-world applications, throughout, based on the author's firsthand experience as a veteran financial risk analyst
eBook