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Implied Elasticity Of Cev Model And Leverage Effect
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Book Synopsis Introduction to Stochastic Finance by : Jia-An Yan
Download or read book Introduction to Stochastic Finance written by Jia-An Yan and published by Springer. This book was released on 2018-10-10 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a systematic introduction to the basic theory of financial mathematics, with an emphasis on applications of martingale methods in pricing and hedging of contingent claims, interest rate term structure models, and expected utility maximization problems. The general theory of static risk measures, basic concepts and results on markets of semimartingale model, and a numeraire-free and original probability based framework for financial markets are also included. The basic theory of probability and Ito's theory of stochastic analysis, as preliminary knowledge, are presented.
Book Synopsis Fuel Hedging and Risk Management by : Simo M. Dafir
Download or read book Fuel Hedging and Risk Management written by Simo M. Dafir and published by John Wiley & Sons. This book was released on 2016-04-25 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on guide to navigating the new fuel markets Fuel Hedging and Risk Management: Strategies for Airlines, Shippers and Other Consumers provides a clear and practical understanding of commodity price dynamics, key fuel hedging techniques, and risk management strategies for the corporate fuel consumer. It covers the commodity markets and derivative instruments in a manner accessible to corporate treasurers, financial officers, risk managers, commodity traders, structurers, as well as quantitative professionals dealing in the energy markets. The book includes a wide variety of key topics related to commodities and derivatives markets, financial risk analysis of commodity consumers, hedge program design and implementation, vanilla derivatives and exotic hedging products. The book is unique in providing intuitive guidance on understanding the dynamics of forward curves and volatility term structure for commodities, fuel derivatives valuation and counterparty risk concepts such as CVA, DVA and FVA. Fully up-to-date and relevant, this book includes comprehensive case studies that illustrate the hedging process from conception to execution and monitoring of hedges in diverse situations. This practical guide will help the reader: Gain expert insight into all aspects of fuel hedging, price and volatility drivers and dynamics. Develop a framework for financial risk analysis and hedge programs. Navigate volatile energy markets by employing effective risk management techniques. Manage unwanted risks associated with commodity derivatives by understanding liquidity and credit risk calculations, exposure optimization techniques, credit charges such as CVA, DVA, FVA, etc.
Book Synopsis Volatility Surface and Term Structure by : Kin Keung Lai
Download or read book Volatility Surface and Term Structure written by Kin Keung Lai and published by Routledge. This book was released on 2013-09-11 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides different financial models based on options to predict underlying asset price and design the risk hedging strategies. Authors of the book have made theoretical innovation to these models to enable the models to be applicable to real market. The book also introduces risk management and hedging strategies based on different criterions. These strategies provide practical guide for real option trading. This book studies the classical stochastic volatility and deterministic volatility models. For the former, the classical Heston model is integrated with volatility term structure. The correlation of Heston model is considered to be variable. For the latter, the local volatility model is improved from experience of financial practice. The improved local volatility surface is then used for price forecasting. VaR and CVaR are employed as standard criterions for risk management. The options trading strategies are also designed combining different types of options and they have been proven to be profitable in real market. This book is a combination of theory and practice. Users will find the applications of these financial models in real market to be effective and efficient.
Book Synopsis Analytically Tractable Stochastic Stock Price Models by : Archil Gulisashvili
Download or read book Analytically Tractable Stochastic Stock Price Models written by Archil Gulisashvili and published by Springer Science & Business Media. This book was released on 2012-09-04 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Asymptotic analysis of stochastic stock price models is the central topic of the present volume. Special examples of such models are stochastic volatility models, that have been developed as an answer to certain imperfections in a celebrated Black-Scholes model of option pricing. In a stock price model with stochastic volatility, the random behavior of the volatility is described by a stochastic process. For instance, in the Hull-White model the volatility process is a geometric Brownian motion, the Stein-Stein model uses an Ornstein-Uhlenbeck process as the stochastic volatility, and in the Heston model a Cox-Ingersoll-Ross process governs the behavior of the volatility. One of the author's main goals is to provide sharp asymptotic formulas with error estimates for distribution densities of stock prices, option pricing functions, and implied volatilities in various stochastic volatility models. The author also establishes sharp asymptotic formulas for the implied volatility at extreme strikes in general stochastic stock price models. The present volume is addressed to researchers and graduate students working in the area of financial mathematics, analysis, or probability theory. The reader is expected to be familiar with elements of classical analysis, stochastic analysis and probability theory.
Book Synopsis Differential Algebra & Algebraic Groups by :
Download or read book Differential Algebra & Algebraic Groups written by and published by Academic Press. This book was released on 1973-06-15 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: Differential Algebra & Algebraic Groups
Book Synopsis Energy and Power Risk Management by : Alexander Eydeland
Download or read book Energy and Power Risk Management written by Alexander Eydeland and published by John Wiley & Sons. This book was released on 2003-02-03 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for Energy and Power Risk Management "Energy and Power Risk Management identifies and addresses the key issues in the development of the turbulent energy industry and the challenges it poses to market players. An insightful and far-reaching book written by two renowned professionals." -Helyette Geman, Professor of Finance University Paris Dauphine and ESSEC "The most up-to-date and comprehensive book on managing energy price risk in the natural gas and power markets. An absolute imperative for energy traders and energy risk management professionals." -Vincent Kaminski, Managing Director Citadel Investment Group LLC "Eydeland and Wolyniec's work does an excellent job of outlining the methods needed to measure and manage risk in the volatile energy market." -Gerald G. Fleming, Vice President, Head of East Power Trading, TXU Energy Trading "This book combines academic rigor with real-world practicality. It is a must-read for anyone in energy risk management or asset valuation." -Ron Erd, Senior Vice President American Electric Power
Book Synopsis Credit Risk Frontiers by : Tomasz Bielecki
Download or read book Credit Risk Frontiers written by Tomasz Bielecki and published by John Wiley & Sons. This book was released on 2011-02-14 with total page 770 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timely guide to understanding and implementing credit derivatives Credit derivatives are here to stay and will continue to play a role in finance in the future. But what will that role be? What issues and challenges should be addressed? And what lessons can be learned from the credit mess? Credit Risk Frontiers offers answers to these and other questions by presenting the latest research in this field and addressing important issues exposed by the financial crisis. It covers this subject from a real world perspective, tackling issues such as liquidity, poor data, and credit spreads, as well as the latest innovations in portfolio products and hedging and risk management techniques. Provides a coherent presentation of recent advances in the theory and practice of credit derivatives Takes into account the new products and risk requirements of a post financial crisis world Contains information regarding various aspects of the credit derivative market as well as cutting edge research regarding those aspects If you want to gain a better understanding of how credit derivatives can help your trading or investing endeavors, then Credit Risk Frontiers is a book you need to read.
Book Synopsis Mathematical and Statistical Methods for Actuarial Sciences and Finance by : Marco Corazza
Download or read book Mathematical and Statistical Methods for Actuarial Sciences and Finance written by Marco Corazza and published by Springer Nature. This book was released on 2022-04-11 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: The cooperation and contamination among mathematicians, statisticians and econometricians working in actuarial sciences and finance are improving the research on these topics and producing numerous meaningful scientific results. This volume presents new ideas in the form of four- to six-page papers presented at the International Conference MAF2022 – Mathematical and Statistical Methods for Actuarial Sciences and Finance. Due to the COVID-19 pandemic, the conference, to which this book is related, was organized in a hybrid form by the Department of Economics and Statistics of the University of Salerno, with the partnership of the Department of Economics of Cà Foscari University of Venice, and was held from 20 to 22 April 2022 in Salerno (Italy) MAF2022 is the tenth edition of an international biennial series of scientific meetings, started in 2004 on the initiative of the Department of Economics and Statistics of the University of Salerno. It has established itself internationally with gradual and continuous growth and scientific enrichment. The effectiveness of this idea has been proven by the wide participation in all the editions, which have been held in Salerno (2004, 2006, 2010, 2014, 2022), Venice (2008, 2012 and 2020 online), Paris (2016) and Madrid (2018). This book covers a wide variety of subjects: artificial intelligence and machine learning in finance and insurance, behavioural finance, credit risk methods and models, dynamic optimization in finance, financial data analytics, forecasting dynamics of actuarial and financial phenomena, foreign exchange markets, insurance models, interest rate models, longevity risk, models and methods for financial time series analysis, multivariate techniques for financial markets analysis, pension systems, portfolio selection and management, real-world finance, risk analysis and management, trading systems, and others. This volume is a valuable resource for academics, PhD students, practitioners, professionals and researchers. Moreover, it is also of interest to other readers with quantitative background knowledge.
Book Synopsis Portfolio Construction, Measurement, and Efficiency by : John B. Guerard, Jr.
Download or read book Portfolio Construction, Measurement, and Efficiency written by John B. Guerard, Jr. and published by Springer. This book was released on 2016-09-23 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, inspired by and dedicated to the work of pioneering investment analyst, Jack Treynor, addresses the issues of portfolio risk and return and how investment portfolios are measured. In a career spanning over fifty years, the primary questions addressed by Jack Treynor were: Is there an observable risk-return trade-off? How can stock selection models be integrated with risk models to enhance client returns? Do managed portfolios earn positive, and statistically significant, excess returns and can mutual fund managers time the market? Since the publication of a pair of seminal Harvard Business Review articles in the mid-1960’s, Jack Treynor has developed thinking that has greatly influenced security selection, portfolio construction and measurement, and market efficiency. Key publications addressed such topics as the Capital Asset Pricing Model and stock selection modeling and integration with risk models. Treynor also served as editor of the Financial Analysts Journal, through which he wrote many columns across a wide spectrum of topics. This volume showcases original essays by leading researchers and practitioners exploring the topics that have interested Treynor while applying the most current methodologies. Such topics include the origins of portfolio theory, market timing, and portfolio construction in equity markets. The result not only reinforces Treynor’s lasting contributions to the field but suggests new areas for research and analysis.
Book Synopsis The Econometric Modelling of Financial Time Series by : Terence C. Mills
Download or read book The Econometric Modelling of Financial Time Series written by Terence C. Mills and published by Cambridge University Press. This book was released on 2008-03-20 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: Terence Mills' best-selling graduate textbook provides detailed coverage of research techniques and findings relating to the empirical analysis of financial markets. In its previous editions it has become required reading for many graduate courses on the econometrics of financial modelling. This third edition, co-authored with Raphael Markellos, contains a wealth of material reflecting the developments of the last decade. Particular attention is paid to the wide range of nonlinear models that are used to analyse financial data observed at high frequencies and to the long memory characteristics found in financial time series. The central material on unit root processes and the modelling of trends and structural breaks has been substantially expanded into a chapter of its own. There is also an extended discussion of the treatment of volatility, accompanied by a new chapter on nonlinearity and its testing.
Book Synopsis The Legacy of Fischer Black by : Bruce N. Lehmann
Download or read book The Legacy of Fischer Black written by Bruce N. Lehmann and published by Oxford University Press. This book was released on 2005 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fischer Black was a remarkable social scientist, one whose contributions range from the lofty perch of highbrow theory to the trenches of practical application. The papers represented in this work span the same range, the contributions of a remarkable array of financial economists who embody in different ways Fischer's ideal of insight from economic theory that both guides and is rooted in the kind of detailed observation of relevant aspects of actual financial markets. It is hoped that readers find this volume to be both a fitting tribute and a stimulus to further research. After all, the advancement of economic science remained a constant goal throughout Fischer's remarkable career in the many and disparate venues in which he plies his trade.
Book Synopsis Financial Data Analytics with Machine Learning, Optimization and Statistics by : Sam Chen
Download or read book Financial Data Analytics with Machine Learning, Optimization and Statistics written by Sam Chen and published by John Wiley & Sons. This book was released on 2024-10-18 with total page 823 pages. Available in PDF, EPUB and Kindle. Book excerpt: An essential introduction to data analytics and Machine Learning techniques in the business sector In Financial Data Analytics with Machine Learning, Optimization and Statistics, a team consisting of a distinguished applied mathematician and statistician, experienced actuarial professionals and working data analysts delivers an expertly balanced combination of traditional financial statistics, effective machine learning tools, and mathematics. The book focuses on contemporary techniques used for data analytics in the financial sector and the insurance industry with an emphasis on mathematical understanding and statistical principles and connects them with common and practical financial problems. Each chapter is equipped with derivations and proofs—especially of key results—and includes several realistic examples which stem from common financial contexts. The computer algorithms in the book are implemented using Python and R, two of the most widely used programming languages for applied science and in academia and industry, so that readers can implement the relevant models and use the programs themselves. The book begins with a brief introduction to basic sampling theory and the fundamentals of simulation techniques, followed by a comparison between R and Python. It then discusses statistical diagnosis for financial security data and introduces some common tools in financial forensics such as Benford's Law, Zipf's Law, and anomaly detection. The statistical estimation and Expectation-Maximization (EM) & Majorization-Minimization (MM) algorithms are also covered. The book next focuses on univariate and multivariate dynamic volatility and correlation forecasting, and emphasis is placed on the celebrated Kelly's formula, followed by a brief introduction to quantitative risk management and dependence modelling for extremal events. A practical topic on numerical finance for traditional option pricing and Greek computations immediately follows as well as other important topics in financial data-driven aspects, such as Principal Component Analysis (PCA) and recommender systems with their applications, as well as advanced regression learners such as kernel regression and logistic regression, with discussions on model assessment methods such as simple Receiver Operating Characteristic (ROC) curves and Area Under Curve (AUC) for typical classification problems. The book then moves on to other commonly used machine learning tools like linear classifiers such as perceptrons and their generalization, the multilayered counterpart (MLP), Support Vector Machines (SVM), as well as Classification and Regression Trees (CART) and Random Forests. Subsequent chapters focus on linear Bayesian learning, including well-received credibility theory in actuarial science and functional kernel regression, and non-linear Bayesian learning, such as the Naïve Bayes classifier and the Comonotone-Independence Bayesian Classifier (CIBer) recently independently developed by the authors and used successfully in InsurTech. After an in-depth discussion on cluster analyses such as K-means clustering and its inversion, the K-nearest neighbor (KNN) method, the book concludes by introducing some useful deep neural networks for FinTech, like the potential use of the Long-Short Term Memory model (LSTM) for stock price prediction. This book can help readers become well-equipped with the following skills: To evaluate financial and insurance data quality, and use the distilled knowledge obtained from the data after applying data analytic tools to make timely financial decisions To apply effective data dimension reduction tools to enhance supervised learning To describe and select suitable data analytic tools as introduced above for a given dataset depending upon classification or regression prediction purpose The book covers the competencies tested by several professional examinations, such as the Predictive Analytics Exam offered by the Society of Actuaries, and the Institute and Faculty of Actuaries' Actuarial Statistics Exam. Besides being an indispensable resource for senior undergraduate and graduate students taking courses in financial engineering, statistics, quantitative finance, risk management, actuarial science, data science, and mathematics for AI, Financial Data Analytics with Machine Learning, Optimization and Statistics also belongs in the libraries of aspiring and practicing quantitative analysts working in commercial and investment banking.
Book Synopsis Modern SABR Analytics by : Alexandre Antonov
Download or read book Modern SABR Analytics written by Alexandre Antonov and published by Springer. This book was released on 2019-04-23 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on recent advances in option pricing under the SABR model, this book shows how to price options under this model in an arbitrage-free, theoretically consistent manner. It extends SABR to a negative rates environment, and shows how to generalize it to a similar model with additional degrees of freedom, allowing simultaneous model calibration to swaptions and CMSs. Since the SABR model is used on practically every trading floor to construct interest rate options volatility cubes in an arbitrage-free manner, a careful treatment of it is extremely important. The book will be of interest to experienced industry practitioners, as well as to students and professors in academia. Aimed mainly at financial industry practitioners (for example quants and former physicists) this book will also be interesting to mathematicians who seek intuition in the mathematical finance.
Book Synopsis Application of Markov Diffusion Processes in Economics and Finance by : Dmitry Davydov
Download or read book Application of Markov Diffusion Processes in Economics and Finance written by Dmitry Davydov and published by . This book was released on 2000 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Modeling and Valuation of Energy Structures by : Daniel Mahoney
Download or read book Modeling and Valuation of Energy Structures written by Daniel Mahoney and published by Springer. This book was released on 2016-01-26 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: Commodity markets present several challenges for quantitative modeling. These include high volatilities, small sample data sets, and physical, operational complexity. In addition, the set of traded products in commodity markets is more limited than in financial or equity markets, making value extraction through trading more difficult. These facts make it very easy for modeling efforts to run into serious problems, as many models are very sensitive to noise and hence can easily fail in practice. Modeling and Valuation of Energy Structures is a comprehensive guide to quantitative and statistical approaches that have been successfully employed in support of trading operations, reflecting the author's 17 years of experience as a front-office 'quant'. The major theme of the book is that simpler is usually better, a message that is drawn out through the reality of incomplete markets, small samples, and informational constraints. The necessary mathematical tools for understanding these issues are thoroughly developed, with many techniques (analytical, econometric, and numerical) collected in a single volume for the first time. A particular emphasis is placed on the central role that the underlying market resolution plays in valuation. Examples are provided to illustrate that robust, approximate valuations are to be preferred to overly ambitious attempts at detailed qualitative modeling.
Book Synopsis A Practical Guide to Forecasting Financial Market Volatility by : Ser-Huang Poon
Download or read book A Practical Guide to Forecasting Financial Market Volatility written by Ser-Huang Poon and published by John Wiley & Sons. This book was released on 2005-08-19 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial market volatility forecasting is one of today's most important areas of expertise for professionals and academics in investment, option pricing, and financial market regulation. While many books address financial market modelling, no single book is devoted primarily to the exploration of volatility forecasting and the practical use of forecasting models. A Practical Guide to Forecasting Financial Market Volatility provides practical guidance on this vital topic through an in-depth examination of a range of popular forecasting models. Details are provided on proven techniques for building volatility models, with guide-lines for actually using them in forecasting applications.
Book Synopsis Essentials of Excel, Excel VBA, SAS and Minitab for Statistical and Financial Analyses by : Cheng-Few Lee
Download or read book Essentials of Excel, Excel VBA, SAS and Minitab for Statistical and Financial Analyses written by Cheng-Few Lee and published by Springer. This book was released on 2016-11-24 with total page 1043 pages. Available in PDF, EPUB and Kindle. Book excerpt: This introductory textbook for business statistics teaches statistical analysis and research methods via business case studies and financial data using Excel, Minitab, and SAS. Every chapter in this textbook engages the reader with data of individual stock, stock indices, options, and futures. One studies and uses statistics to learn how to study, analyze, and understand a data set of particular interest. Some of the more popular statistical programs that have been developed to use statistical and computational methods to analyze data sets are SAS, SPSS, and Minitab. Of those, we look at Minitab and SAS in this textbook. One of the main reasons to use Minitab is that it is the easiest to use among the popular statistical programs. We look at SAS because it is the leading statistical package used in industry. We also utilize the much less costly and ubiquitous Microsoft Excel to do statistical analysis, as the benefits of Excel have become widely recognized in the academic world and its analytical capabilities extend to about 90 percent of statistical analysis done in the business world. We demonstrate much of our statistical analysis using Excel and double check the analysis and outcomes using Minitab and SAS—also helpful in some analytical methods not possible or practical to do in Excel.
