Author: Damien P.G. Lynch
Publisher:
ISBN:
Category :
Languages : en
Pages : 61
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Book Description
The statistics that summarise the probability distributions implied from option prices can be used to assess market expectations about future uncertainty, asymmetry and the probability of extreme movements in asset prices. This paper considers implied pdfs with a constant horizon of three months for Samp;P 500, FTSE 100, eurodollar and short-sterling. A time series analysis of the summary statistics provides some stylised facts about the behaviour of different elements of market expectations, their historical distribution and the relationships between them. The distributions of these measures provide information on past revisions to market expectations including the relative likelihood of upward rather than downward revisions and the extent to which these revisions were large. The similarity and relative stability of alternative measures for each element of market expectations is assessed to select a subset of summary statistics that can sufficiently reflect the information contained in the implied pdfs. Relationships between implied pdf summary statistics and movements in underlying assets are considered. Cross asset and cross country comparisons between the summary statistics series are also useful in revealing relations and/or associations between market participants' expectations about equity price and interest rate movements. Finally the information content of the implied pdfs for future macroeconomic and financial variables is assessed.
Author: Damien Lynch
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Damien P.G. Lynch
Publisher:
ISBN:
Category :
Languages : en
Pages : 57
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Book Description
The statistics that summarise the probability distributions implied from option prices can be used to assess market expectations about future uncertainty, asymmetry and the probability of extreme movements in asset prices. This paper considers implied pdfs with a constant horizon of three months for Samp;P 500, FTSE 100, eurodollar and short-sterling. A time series analysis of the summary statistics provides some stylised facts about the behaviour of different elements of market expectations, their historical distribution and the relationships between them. The distributions of these measures provide information on past revisions to market expectations including the relative likelihood of upward rather than downward revisions and the extent to which these revisions were large. The similarity and relative stability of alternative measures for each element of market expectations is assessed to select a subset of summary statistics that can sufficiently reflect the information contained in the implied pdfs. Relationships between implied pdf summary statistics and movements in underlying assets are considered. Cross asset and cross country comparisons between the summary statistics series are also useful in revealing relations and/or associations between market participants' expectations about equity price and interest rate movements. Finally the information content of the implied pdfs for future macroeconomic and financial variables is assessed.
Author: Robert R. Bliss
Publisher:
ISBN:
Category : Derivative securities
Languages : en
Pages : 68
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Book Description
Author: Robert R. Bliss
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Implied probability density functions (PDFs) estimated from cross-sections of observed option prices are gaining increasing attention amongst academics and practitioners. However, to date little attention has been paid to the robustness of these estimates or to the confidence users can place in the summary statistics, for example skewness or the 99th percentile, derived from fitted PDFs. This paper begins to address these questions by examining the absolute and relative robustness of two of the most common methods for estimating implied PDFs--the double-lognormal approximating function and the smoothed implied volatility smile methods. The changes resulting from randomly perturbing quoted prices by no more than a half tick provide a lower bound on the confidence intervals of the summary statistics derived from the estimated PDFs. Tests are conducted using options contracts tied to Short Sterling futures and the FTSE 100 index--both trading on the London International Financial Futures Exchange. Our tests show that the smoothed implied volatility smile method dominates the double-lognormal as a technique for estimating implied PDFs when average goodness-of-fits are comparable for both methods.
Author: Stephen Satchell
Publisher: Elsevier
ISBN: 0080494978
Category : Business & Economics
Languages : en
Pages : 417
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Book Description
'Forecasting Volatility in the Financial Markets' assumes 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 then uses a technical survey to explain the different ways to measure risk and define the different models of volatility and return.The editors have brought together a set of contributors that give the reader a firm grounding in relevant theory and research and an insight into the cutting edge techniques applied in this field of the financial markets.This book is of particular relevance to anyone who wants to understand dynamic areas of the financial markets.* Traders will profit by learning to arbitrage opportunities and modify their strategies to account for volatility.* Investment managers will be able to enhance their asset allocation strategies with an improved understanding of likely risks and returns.* Risk managers will understand how to improve their measurement systems and forecasts, enhancing their risk management models and controls.* Derivative specialists will gain an in-depth understanding of volatility that they can use to improve their pricing models.* Students and academics will find the collection of papers an invaluable overview of this field. This book is of particular relevance to those wanting to understand the dynamic areas of volatility modeling and forecasting of the financial marketsProvides the latest research and techniques for Traders, Investment Managers, Risk Managers and Derivative Specialists wishing to manage their downside risk exposure Current research on the key forecasting methods to use in risk management, including two new chapters
Author: Shigenori Shiratsuka
Publisher:
ISBN:
Category : Assets (Accounting)
Languages : en
Pages : 56
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Book Description
Author: Massimiliano Bonamente
Publisher: Springer Nature
ISBN: 9811903654
Category : Science
Languages : en
Pages : 492
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Book Description
This book is the third edition of a successful textbook for upper-undergraduate and early graduate students, which offers a solid foundation in probability theory and statistics and their application to physical sciences, engineering, biomedical sciences and related disciplines. It provides broad coverage ranging from conventional textbook content of probability theory, random variables, and their statistics, regression, and parameter estimation, to modern methods including Monte-Carlo Markov chains, resampling methods and low-count statistics. In addition to minor corrections and adjusting structure of the content, particular features in this new edition include: Python codes and machine-readable data for all examples, classic experiments, and exercises, which are now more accessible to students and instructors New chapters on low-count statistics including the Poisson-based Cash statistic for regression in the low-count regime, and on contingency tables and diagnostic testing. An additional example of classic experiments based on testing data for SARS-COV-2 to demonstrate practical applications of the described statistical methods. This edition inherits the main pedagogical method of earlier versions—a theory-then-application approach—where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and practical application of the materials. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required. The book includes many numerical tables of data as well as exercises and examples to aid the readers' understanding of the topic.
Author: Siu-Kui Au
Publisher: Springer
ISBN: 9811041180
Category : Science
Languages : en
Pages : 552
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Book Description
This book presents operational modal analysis (OMA), employing a coherent and comprehensive Bayesian framework for modal identification and covering stochastic modeling, theoretical formulations, computational algorithms, and practical applications. Mathematical similarities and philosophical differences between Bayesian and classical statistical approaches to system identification are discussed, allowing their mathematical tools to be shared and their results correctly interpreted. The authors provide their data freely in the web at https://doi.org/10.7910/DVN/7EVTXG Many chapters can be used as lecture notes for the general topic they cover beyond the OMA context. After an introductory chapter (1), Chapters 2–7 present the general theory of stochastic modeling and analysis of ambient vibrations. Readers are first introduced to the spectral analysis of deterministic time series (2) and structural dynamics (3), which do not require the use of probability concepts. The concepts and techniques in these chapters are subsequently extended to a probabilistic context in Chapter 4 (on stochastic processes) and in Chapter 5 (on stochastic structural dynamics). In turn, Chapter 6 introduces the basics of ambient vibration instrumentation and data characteristics, while Chapter 7 discusses the analysis and simulation of OMA data, covering different types of data encountered in practice. Bayesian and classical statistical approaches to system identification are introduced in a general context in Chapters 8 and 9, respectively. Chapter 10 provides an overview of different Bayesian OMA formulations, followed by a general discussion of computational issues in Chapter 11. Efficient algorithms for different contexts are discussed in Chapters 12–14 (single mode, multi-mode, and multi-setup). Intended for readers with a minimal background in mathematics, Chapter 15 presents the ‘uncertainty laws’ in OMA, one of the latest advances that establish the achievable precision limit of OMA and provide a scientific basis for planning ambient vibration tests. Lastly Chapter 16 discusses the mathematical theory behind the results in Chapter 15, addressing the needs of researchers interested in learning the techniques for further development. Three appendix chapters round out the coverage. This book is primarily intended for graduate/senior undergraduate students and researchers, although practitioners will also find the book a useful reference guide. It covers materials from introductory to advanced level, which are classified accordingly to ensure easy access. Readers with an undergraduate-level background in probability and statistics will find the book an invaluable resource, regardless of whether they are Bayesian or non-Bayesian.
Author: Cheng-Few Lee
Publisher: Springer Science & Business Media
ISBN: 0387771174
Category : Business & Economics
Languages : en
Pages : 1700
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Book Description
Quantitative finance is a combination of economics, accounting, statistics, econometrics, mathematics, stochastic process, and computer science and technology. Increasingly, the tools of financial analysis are being applied to assess, monitor, and mitigate risk, especially in the context of globalization, market volatility, and economic crisis. This two-volume handbook, comprised of over 100 chapters, is the most comprehensive resource in the field to date, integrating the most current theory, methodology, policy, and practical applications. Showcasing contributions from an international array of experts, the Handbook of Quantitative Finance and Risk Management is unparalleled in the breadth and depth of its coverage. Volume 1 presents an overview of quantitative finance and risk management research, covering the essential theories, policies, and empirical methodologies used in the field. Chapters provide in-depth discussion of portfolio theory and investment analysis. Volume 2 covers options and option pricing theory and risk management. Volume 3 presents a wide variety of models and analytical tools. Throughout, the handbook offers illustrative case examples, worked equations, and extensive references; additional features include chapter abstracts, keywords, and author and subject indices. From "arbitrage" to "yield spreads," the Handbook of Quantitative Finance and Risk Management will serve as an essential resource for academics, educators, students, policymakers, and practitioners.
