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Narrative and Consciousness
The evocation of narrative as a way to understand the content of consciousness has sparked truly interdisciplinary work among psychologists, philosophers and literary critics. The research presented in this volume should appeal to the general reader and researchers enmeshed in these problems.
Fitting Local Volatility: Analytic And Numerical Approaches In Black-scholes And Local Variance Gamma Models
The concept of local volatility as well as the local volatility model are one of the classical topics of mathematical finance. Although the existing literature is wide, there still exist various problems that have not drawn sufficient attention so far, for example: a) construction of analytical solutions of the Dupire equation for an arbitrary shape of the local volatility function; b) construction of parametric or non-parametric regression of the local volatility surface suitable for fast calibration; c) no-arbitrage interpolation and extrapolation of the local and implied volatility surfaces; d) extension of the local volatility concept beyond the Black-Scholes model, etc. Also, recent pro...
Handbook Of Heavy-tailed Distributions In Asset Management And Risk Management
The study of heavy-tailed distributions allows researchers to represent phenomena that occasionally exhibit very large deviations from the mean. The dynamics underlying these phenomena is an interesting theoretical subject, but the study of their statistical properties is in itself a very useful endeavor from the point of view of managing assets and controlling risk. In this book, the authors are primarily concerned with the statistical properties of heavy-tailed distributions and with the processes that exhibit jumps. A detailed overview with a Matlab implementation of heavy-tailed models applied in asset management and risk managements is presented. The book is not intended as a theoretical treatise on probability or statistics, but as a tool to understand the main concepts regarding heavy-tailed random variables and processes as applied to real-world applications in finance. Accordingly, the authors review approaches and methodologies whose realization will be useful for developing new methods for forecasting of financial variables where extreme events are not treated as anomalies, but as intrinsic parts of the economic process.
Tea in Health and Disease Prevention
While there is a nearly universal agreement that drinking tea can benefit health, information on the benefits or adverse effects of drinking tea is scattered, leaving definitive answers difficult to ascertain. Tea in Health and Disease Prevention, Second Edition, once again addresses this problem, bringing together all the latest and most relevant information on tea and its health effects into one comprehensive resource. This book covers compounds in black, green, and white teas and explores their health implications, first more generally, then in terms of specific organ systems and diseases. With over 75% brand new content, this fully reorganized, updated edition covers a wider range of tea...
An Introduction To Machine Learning In Quantitative Finance
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. Over the past few years, ML has gradually permeated the financial sector, reshaping the landscape of quantitative finance as we know it.An Introduction to Machine Learning in Quantitative Finance aims to demystify ML by uncovering its underlying mathematics and showing how to apply ML methods to real-world financial data. In this book the authorsFeatured with the balance of mathematical theorems and practical code examples of ML, this book will help you acquire an in-depth understanding of ML algorithms as well as hands-on experience. After reading An Introduction to Machine Learning in Quantitative Finance, ML tools will not be a black box to you anymore, and you will feel confident in successfully applying what you have learnt to empirical financial data!
Processing Contaminants in Edible Oils
Fully revised and updated, Processing Contaminants in Edible Oils, 2nd edition, presents the latest research on monochloropropanediol (MCPD) and glycidyl esters in edible oils. These potentially harmful contaminants are formed during the industrial processing of food oils during deodorization. A number of advancements in understanding these have been made since the publication of the first edition. These important changes, which impact industrial mitigation, analytical methods, toxicology and regulation, are highlighted for up-to-date reference. The mechanisms of formation for MCPD and glycidyl ester contaminants, as well as research identifying possible precursor molecules are reviewed, as ...
Magic on the Early English Stage
An original investigation into conjuring tricks and stage magic on the medieval stage.
Mathematical Modeling And Computation In Finance: With Exercises And Python And Matlab Computer Codes
This book discusses the interplay of stochastics (applied probability theory) and numerical analysis in the field of quantitative finance. The stochastic models, numerical valuation techniques, computational aspects, financial products, and risk management applications presented will enable readers to progress in the challenging field of computational finance.When the behavior of financial market participants changes, the corresponding stochastic mathematical models describing the prices may also change. Financial regulation may play a role in such changes too. The book thus presents several models for stock prices, interest rates as well as foreign-exchange rates, with increasing complexity...
Generalized Integral Transforms In Mathematical Finance
This book describes several techniques, first invented in physics for solving problems of heat and mass transfer, and applies them to various problems of mathematical finance defined in domains with moving boundaries. These problems include: (a) semi-closed form pricing of options in the one-factor models with time-dependent barriers (Bachelier, Hull-White, CIR, CEV); (b) analyzing an interconnected banking system in the structural credit risk model with default contagion; (c) finding first hitting time density for a reducible diffusion process; (d) describing the exercise boundary of American options; (e) calculating default boundary for the structured default problem; (f) deriving a semi-c...
