Описание: 'Dennis Buchanan (TM)s text clearly shows how an understanding of the complementary disciplines of geoscience, conventional engineering and advanced financial engineering is essential to making the right decisions concerning how to appraise a resource or project and how to structure the funding of natural resources assets in order to mitigate technical and financial risk and to maximise value for owners. Crucially, the book also looks at how other sources of capital, such as limited recourse lenders, appraise metals and energy assets. Such an understanding is essential to optimising the capital structure and valuation of natural resources assets ... The advanced methodologies revealed in Dennis Buchanan (TM)s book will have great value to those working in the technical and financial functions, or to those spanning both functions, of the natural resources industry. 'Mineral EconomicsGiven the design component it involves, financial engineering should be considered equal to conventional engineering. By adopting this complementary approach, financial models can be used to identify how and why timing is critical in optimizing return on investment and to demonstrate how financial engineering can enhance returns to investors. Metals and Energy Finance capitalizes on this approach, and identifies and examines the investment opportunities offered across the extractive industry's cycle, from exploration through evaluation, pre-production development, development and production. The textbook also addresses the similarities of a range of natural resource projects, whether minerals or petroleum, while at the same time identifying their key differences.This new edition has been comprehensively revised with a new chapter on Quantitative Finance and three additional case studies. Contemporary themes in the revised edition include the current focus on the transition from open pit to underground mining as well as the role of real option valuations applied to marginal projects that may have value in the future.This innovative textbook is clear and concise in its approach. Both authors have extensive experience within the academic environment at a senior level as well as track records of hands-on participation in projects within the natural resources and financial services sectors. Metals and Energy Finance will be invaluable to both professionals and graduate students working in the field of mineral and petroleum business management.
Автор: Marcos Lopez de Prado Название: Machine Learning for Asset Managers ISBN: 1108792898 ISBN-13(EAN): 9781108792899 Издательство: Cambridge Academ Рейтинг: Цена: 2851.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The purpose of this Element is to introduce machine learning (ML) tools that can help asset managers discover economic and financial theories. ML is not a black box, and it does not necessarily overfit. ML tools complement rather than replace the classical statistical methods.
Автор: McNeil Alexander J. Название: Quantitative Risk Management ISBN: 0691166277 ISBN-13(EAN): 9780691166278 Издательство: Wiley Рейтинг: Цена: 15840.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book provides the most comprehensive treatment of the theoretical concepts and modelling techniques of quantitative risk management. Whether you are a financial risk analyst, actuary, regulator or student of quantitative finance, Quantitative Risk Management gives you the practical tools you need to solve real-world problems.
Describing the latest advances in the field, Quantitative Risk Management covers the methods for market, credit and operational risk modelling. It places standard industry approaches on a more formal footing and explores key concepts such as loss distributions, risk measures and risk aggregation and allocation principles. The book's methodology draws on diverse quantitative disciplines, from mathematical finance and statistics to econometrics and actuarial mathematics. A primary theme throughout is the need to satisfactorily address extreme outcomes and the dependence of key risk drivers. Proven in the classroom, the book also covers advanced topics like credit derivatives.
Fully revised and expanded to reflect developments in the field since the financial crisis
Features shorter chapters to facilitate teaching and learning
Provides enhanced coverage of Solvency II and insurance risk management and extended treatment of credit risk, including counterparty credit risk and CDO pricing
Includes a new chapter on market risk and new material on risk measures and risk aggregation
Автор: Crispoldi Christian Название: SABR and SABR LIBOR Market Models in Practice ISBN: 1137378638 ISBN-13(EAN): 9781137378637 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A hands-on guide to interest rate modelling, including the SABR model, the market standard for vanilla products, and the LIBOR market model, the most commonly used model for exotic products. This accessible book also provides an explanation of the extended SABR LIBOR market model.
Автор: Brockhaus Oliver Название: Equity Derivatives and Hybrids ISBN: 1137349484 ISBN-13(EAN): 9781137349484 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: this book provides an up-to-date account of equity and equity-hybrid (equity-rates, equity-credit, equity-foreign exchange) derivatives modeling from a practitioner`s perspective.
Автор: Lichters Roland Название: Modern Derivatives Pricing and Credit Exposure Analysis ISBN: 1137494832 ISBN-13(EAN): 9781137494832 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a comprehensive guide for modern derivatives pricing and credit analysis. Written to provide sound theoretical detail but practical implication, it provides readers with everything they need to know to price modern financial derivatives and analyze the credit exposure of a financial instrument in today`s markets.
Автор: Guangxi Yu, Hao Ni, Jinsong Zheng, Xin Dong Название: An introduction to machine learning in quantitative finance ISBN: 1786349647 ISBN-13(EAN): 9781786349644 Издательство: World Scientific Publishing Рейтинг: Цена: 7128.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In today`s world, we are increasingly exposed to the words "machine learning" (ML), a term which sounds like a panacea designed to cure all problems ranging from image recognition to machine language translation.
Автор: Watsham, Terry J. Parramore, Keith Название: Quantitative methods in finance ISBN: 186152367X ISBN-13(EAN): 9781861523679 Издательство: Cengage Learning Рейтинг: Цена: 13304.00 р. Наличие на складе: Нет в наличии.
Описание: This text explains the mathematical and statistical applications relevant to modern financial instruments and risk management techniques. It progresses at a comfortable pace for those with less mathematical expertise yet reaches a high level of analysis for the more experienced.
Автор: Stephen Satchell Название: Forecasting Volatility in the Financial Markets, ISBN: 075066942X ISBN-13(EAN): 9780750669429 Издательство: Elsevier Science Рейтинг: Цена: 13109.00 р. Наличие на складе: Нет в наличии.
Описание: Forecasting Volatility in the Financial Markets, Third Editionassumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting-edge modelling and forecasting techniques. It provides a survey of ways to measure risk and define the different models of volatility and return. Editors John Knight and Stephen Satchell have brought together an impressive array of contributors who present research from their area of specialization related to volatility forecasting. Readers with an understanding of volatility measures and risk management strategies will benefit from this collection of up-to-date chapters on the latest techniques in forecasting volatility. Chapters new to this third edition:* What good is a volatility model? Engle and Patton* Applications for portfolio variety Dan diBartolomeo* A comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices Rob Cornish* Volatility modeling and forecasting in finance Xiao and Aydemir* An investigation of the relative performance of GARCH models versus simple rules in forecasting volatility Thomas A. Silvey
Автор: Paul Wilmott Название: Paul Wilmott Introduces Quantitative Finance ISBN: 0471498629 ISBN-13(EAN): 9780471498629 Издательство: Wiley Цена: 5542.00 р. Наличие на складе: Поставка под заказ.
Описание: In this student edition the author gives a comprehensive introduction to theory and practice of financial engineering in a manner designed to be accessible to students and those who are new to the financial markets. It is presented in a unique and accessible style with illustrations, graphs and side-bars with explanations working through the maths. The author's style from his previous book of providing the reader with answers to the problems has been maintained throughout this expanded work.
Название: Quantitative Energy Finance ISBN: 1461472474 ISBN-13(EAN): 9781461472476 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book also confronts the challenges in energy markets from a quantitative point of view, as well as the recent advances in solving these problems using advanced mathematical, statistical and numerical methods.
Автор: Nico van der Wijst Название: Finance: A Quantitative Introduction ISBN: 1107029228 ISBN-13(EAN): 9781107029224 Издательство: Cambridge Academ Рейтинг: Цена: 8078.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: By providing a solid theoretical basis in finance this textbook introduces modern finance to readers, with emphasis on investments in real assets and the real options attached to them, including students in science and technology, who have a good foundation in quantitative skills.
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