Author: Massimo Guidolin
Publisher:
ISBN:
Category : Bayesian statistical decision theory
Languages : en
Pages : 70
Book Description
Option Prices Under Bayesian Learning
Author: Massimo Guidolin
Publisher:
ISBN:
Category : Bayesian statistical decision theory
Languages : en
Pages : 70
Book Description
Publisher:
ISBN:
Category : Bayesian statistical decision theory
Languages : en
Pages : 70
Book Description
Asset Prices on Bayesian Learning Paths
Author: Massimo Guidolin
Publisher:
ISBN:
Category : Assets (Accounting)
Languages : en
Pages : 452
Book Description
Publisher:
ISBN:
Category : Assets (Accounting)
Languages : en
Pages : 452
Book Description
Bayesian Reasoning and Machine Learning
Author: David Barber
Publisher: Cambridge University Press
ISBN: 0521518148
Category : Computers
Languages : en
Pages : 739
Book Description
A practical introduction perfect for final-year undergraduate and graduate students without a solid background in linear algebra and calculus.
Publisher: Cambridge University Press
ISBN: 0521518148
Category : Computers
Languages : en
Pages : 739
Book Description
A practical introduction perfect for final-year undergraduate and graduate students without a solid background in linear algebra and calculus.
Bayesian Learning for Neural Networks
Author: Radford M. Neal
Publisher: Springer Science & Business Media
ISBN: 1461207452
Category : Mathematics
Languages : en
Pages : 194
Book Description
Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions remain about how the power of these models can be safely exploited when training data is limited. This book demonstrates how Bayesian methods allow complex neural network models to be used without fear of the "overfitting" that can occur with traditional training methods. Insight into the nature of these complex Bayesian models is provided by a theoretical investigation of the priors over functions that underlie them. A practical implementation of Bayesian neural network learning using Markov chain Monte Carlo methods is also described, and software for it is freely available over the Internet. Presupposing only basic knowledge of probability and statistics, this book should be of interest to researchers in statistics, engineering, and artificial intelligence.
Publisher: Springer Science & Business Media
ISBN: 1461207452
Category : Mathematics
Languages : en
Pages : 194
Book Description
Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions remain about how the power of these models can be safely exploited when training data is limited. This book demonstrates how Bayesian methods allow complex neural network models to be used without fear of the "overfitting" that can occur with traditional training methods. Insight into the nature of these complex Bayesian models is provided by a theoretical investigation of the priors over functions that underlie them. A practical implementation of Bayesian neural network learning using Markov chain Monte Carlo methods is also described, and software for it is freely available over the Internet. Presupposing only basic knowledge of probability and statistics, this book should be of interest to researchers in statistics, engineering, and artificial intelligence.
Option Volatility & Pricing: Advanced Trading Strategies and Techniques
Author: Sheldon Natenberg
Publisher: McGraw Hill Professional
ISBN: 155738486X
Category : Business & Economics
Languages : en
Pages : 485
Book Description
Provides a thorough discussion of volatility, the most important aspect of options trading. Shows how to identify mispriced options and to construct volatility and "delta neutral" spreads.
Publisher: McGraw Hill Professional
ISBN: 155738486X
Category : Business & Economics
Languages : en
Pages : 485
Book Description
Provides a thorough discussion of volatility, the most important aspect of options trading. Shows how to identify mispriced options and to construct volatility and "delta neutral" spreads.
The Paradox of Asset Pricing
Author: Peter Bossaerts
Publisher: Princeton University Press
ISBN: 1400850665
Category : Business & Economics
Languages : en
Pages : 187
Book Description
Asset pricing theory abounds with elegant mathematical models. The logic is so compelling that the models are widely used in policy, from banking, investments, and corporate finance to government. To what extent, however, can these models predict what actually happens in financial markets? In The Paradox of Asset Pricing, a leading financial researcher argues forcefully that the empirical record is weak at best. Peter Bossaerts undertakes the most thorough, technically sound investigation in many years into the scientific character of the pricing of financial assets. He probes this conundrum by modeling a decidedly volatile phenomenon that, he says, the world of finance has forgotten in its enthusiasm for the efficient markets hypothesis--speculation. Bossaerts writes that the existing empirical evidence may be tainted by the assumptions needed to make sense of historical field data or by reanalysis of the same data. To address the first problem, he demonstrates that one central assumption--that markets are efficient processors of information, that risk is a knowable quantity, and so on--can be relaxed substantially while retaining core elements of the existing methodology. The new approach brings novel insights to old data. As for the second problem, he proposes that asset pricing theory be studied through experiments in which subjects trade purposely designed assets for real money. This book will be welcomed by finance scholars and all those math--and statistics-minded readers interested in knowing whether there is science beyond the mathematics of finance. This book provided the foundation for subsequent journal articles that won two prestigious awards: the 2003 Journal of Financial Markets Best Paper Award and the 2004 Goldman Sachs Asset Management Best Research Paper for the Review of Finance.
Publisher: Princeton University Press
ISBN: 1400850665
Category : Business & Economics
Languages : en
Pages : 187
Book Description
Asset pricing theory abounds with elegant mathematical models. The logic is so compelling that the models are widely used in policy, from banking, investments, and corporate finance to government. To what extent, however, can these models predict what actually happens in financial markets? In The Paradox of Asset Pricing, a leading financial researcher argues forcefully that the empirical record is weak at best. Peter Bossaerts undertakes the most thorough, technically sound investigation in many years into the scientific character of the pricing of financial assets. He probes this conundrum by modeling a decidedly volatile phenomenon that, he says, the world of finance has forgotten in its enthusiasm for the efficient markets hypothesis--speculation. Bossaerts writes that the existing empirical evidence may be tainted by the assumptions needed to make sense of historical field data or by reanalysis of the same data. To address the first problem, he demonstrates that one central assumption--that markets are efficient processors of information, that risk is a knowable quantity, and so on--can be relaxed substantially while retaining core elements of the existing methodology. The new approach brings novel insights to old data. As for the second problem, he proposes that asset pricing theory be studied through experiments in which subjects trade purposely designed assets for real money. This book will be welcomed by finance scholars and all those math--and statistics-minded readers interested in knowing whether there is science beyond the mathematics of finance. This book provided the foundation for subsequent journal articles that won two prestigious awards: the 2003 Journal of Financial Markets Best Paper Award and the 2004 Goldman Sachs Asset Management Best Research Paper for the Review of Finance.
Recent Advances in Financial Engineering
Author: Masaaki Kijima
Publisher: World Scientific
ISBN: 9814304077
Category : Business & Economics
Languages : en
Pages : 284
Book Description
This book consists of 11 papers based on research presented at the KIER-TMU International Workshop on Financial Engineering, held in Tokyo in 2009. The Workshop, organised by Kyoto University's Institute of Economic Research (KIER) and Tokyo Metropolitan University (TMU), is the successor to the Daiwa International Workshop on Financial Engineering held from 2004 to 2008 by Professor Kijima (the Chair of this Workshop) and his colleagues. Academic researchers and industry practitioners alike have presented the latest research on financial engineering at this international venue. These papers address state-of-the-art techniques in financial engineering, and have undergone a rigorous selection process to make this book a high-quality one. This volume will be of interest to academics, practitioners, and graduate students in the field of quantitative finance and financial engineering
Publisher: World Scientific
ISBN: 9814304077
Category : Business & Economics
Languages : en
Pages : 284
Book Description
This book consists of 11 papers based on research presented at the KIER-TMU International Workshop on Financial Engineering, held in Tokyo in 2009. The Workshop, organised by Kyoto University's Institute of Economic Research (KIER) and Tokyo Metropolitan University (TMU), is the successor to the Daiwa International Workshop on Financial Engineering held from 2004 to 2008 by Professor Kijima (the Chair of this Workshop) and his colleagues. Academic researchers and industry practitioners alike have presented the latest research on financial engineering at this international venue. These papers address state-of-the-art techniques in financial engineering, and have undergone a rigorous selection process to make this book a high-quality one. This volume will be of interest to academics, practitioners, and graduate students in the field of quantitative finance and financial engineering
Bayesian Data Analysis, Third Edition
Author: Andrew Gelman
Publisher: CRC Press
ISBN: 1439840954
Category : Mathematics
Languages : en
Pages : 677
Book Description
Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.
Publisher: CRC Press
ISBN: 1439840954
Category : Mathematics
Languages : en
Pages : 677
Book Description
Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.
Operationalizing Dynamic Pricing Models
Author: Steffen Christ
Publisher: Springer Science & Business Media
ISBN: 3834961841
Category : Business & Economics
Languages : en
Pages : 363
Book Description
Steffen Christ shows how theoretic optimization models can be operationalized by employing self-learning strategies to construct relevant input variables, such as latent demand and customer price sensitivity.
Publisher: Springer Science & Business Media
ISBN: 3834961841
Category : Business & Economics
Languages : en
Pages : 363
Book Description
Steffen Christ shows how theoretic optimization models can be operationalized by employing self-learning strategies to construct relevant input variables, such as latent demand and customer price sensitivity.
The Oxford Handbook of Applied Bayesian Analysis
Author: Anthony O' Hagan
Publisher: OUP Oxford
ISBN: 0191613894
Category : Mathematics
Languages : en
Pages : 924
Book Description
Bayesian analysis has developed rapidly in applications in the last two decades and research in Bayesian methods remains dynamic and fast-growing. Dramatic advances in modelling concepts and computational technologies now enable routine application of Bayesian analysis using increasingly realistic stochastic models, and this drives the adoption of Bayesian approaches in many areas of science, technology, commerce, and industry. This Handbook explores contemporary Bayesian analysis across a variety of application areas. Chapters written by leading exponents of applied Bayesian analysis showcase the scientific ease and natural application of Bayesian modelling, and present solutions to real, engaging, societally important and demanding problems. The chapters are grouped into five general areas: Biomedical & Health Sciences; Industry, Economics & Finance; Environment & Ecology; Policy, Political & Social Sciences; and Natural & Engineering Sciences, and Appendix material in each touches on key concepts, models, and techniques of the chapter that are also of broader pedagogic and applied interest.
Publisher: OUP Oxford
ISBN: 0191613894
Category : Mathematics
Languages : en
Pages : 924
Book Description
Bayesian analysis has developed rapidly in applications in the last two decades and research in Bayesian methods remains dynamic and fast-growing. Dramatic advances in modelling concepts and computational technologies now enable routine application of Bayesian analysis using increasingly realistic stochastic models, and this drives the adoption of Bayesian approaches in many areas of science, technology, commerce, and industry. This Handbook explores contemporary Bayesian analysis across a variety of application areas. Chapters written by leading exponents of applied Bayesian analysis showcase the scientific ease and natural application of Bayesian modelling, and present solutions to real, engaging, societally important and demanding problems. The chapters are grouped into five general areas: Biomedical & Health Sciences; Industry, Economics & Finance; Environment & Ecology; Policy, Political & Social Sciences; and Natural & Engineering Sciences, and Appendix material in each touches on key concepts, models, and techniques of the chapter that are also of broader pedagogic and applied interest.