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Probability And Finance Theory

Author: Kian Guan Lim
Publisher: World Scientific Publishing Company
ISBN: 9814641952
Size: 64.22 MB
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This book is an introduction to the mathematical analysis of probability theory and provides some understanding of how probability is used to model random phenomena of uncertainty, specifically in the context of finance theory and applications. The integrated coverage of both basic probability theory and finance theory makes this book useful reading for advanced undergraduate students or for first-year postgraduate students in a quantitative finance course. The book provides easy and quick access to the field of theoretical finance by linking the study of applied probability and its applications to finance theory all in one place. The coverage is carefully selected to include most of the key ideas in finance in the last 50 years. The book will also serve as a handy guide for applied mathematicians and probabilists to easily access the important topics in finance theory and economics. In addition, it will also be a handy book for financial economists to learn some of the more mathematical and rigorous techniques so their understanding of theory is more rigorous. It is a must read for advanced undergraduate and graduate students who wish to work in the quantitative finance area.

Probability And Finance

Author: Glenn Shafer
Publisher: John Wiley & Sons
ISBN: 0471461717
Size: 22.15 MB
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Provides a foundation for probability based on game theory rather than measure theory. A strong philosophical approach with practical applications. Presents in-depth coverage of classical probability theory as well as new theory.

A Little Book On Probability And Finance

Author: Cho, Seung Mo
Publisher: 주식회사 부크크
ISBN:
Size: 34.94 MB
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Modern finance theory is vast and deep with various academic bases such as microeconomics, econometrics, probability theory, stochastic calculus, psychology, sociology, political economy, etc. depending on the specific research theme. Among those bases, this book is adopting probability theory and stochastic calculus to present some of the main contents of finance in a very concise manner. As a matter of fact, the objective of this book is to show, as concisely as possible, how probability and stochastic calculus is closely related to modern mathematical finance. So the organization of the book is to present theories of probability first and then their related financial theories later within each of the chapters in the theorem-proof style. From my past experience, students with a quantitative background prefer mathematical symbols to normal English sentences especially in case they are not native speakers of English. So I have tried to minimize the use of English sentences. This book is intended for upper level undergraduate courses and introductory graduate courses in mathematical finance for a single semester. This book can also be used for self-studying students with proper prerequisite knowledge. The only prerequisite for this book is one year courses of calculus.

Measure Probability And Mathematical Finance

Author: Guojun Gan
Publisher: John Wiley & Sons
ISBN: 1118831969
Size: 31.83 MB
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An introduction to the mathematical theory and financial models developed and used on Wall Street Providing both a theoretical and practical approach to the underlying mathematical theory behind financial models, Measure, Probability, and Mathematical Finance: A Problem-Oriented Approach presents important concepts and results in measure theory, probability theory, stochastic processes, and stochastic calculus. Measure theory is indispensable to the rigorous development of probability theory and is also necessary to properly address martingale measures, the change of numeraire theory, and LIBOR market models. In addition, probability theory is presented to facilitate the development of stochastic processes, including martingales and Brownian motions, while stochastic processes and stochastic calculus are discussed to model asset prices and develop derivative pricing models. The authors promote a problem-solving approach when applying mathematics in real-world situations, and readers are encouraged to address theorems and problems with mathematical rigor. In addition, Measure, Probability, and Mathematical Finance features: A comprehensive list of concepts and theorems from measure theory, probability theory, stochastic processes, and stochastic calculus Over 500 problems with hints and select solutions to reinforce basic concepts and important theorems Classic derivative pricing models in mathematical finance that have been developed and published since the seminal work of Black and Scholes Measure, Probability, and Mathematical Finance: A Problem-Oriented Approach is an ideal textbook for introductory quantitative courses in business, economics, and mathematical finance at the upper-undergraduate and graduate levels. The book is also a useful reference for readers who need to build their mathematical skills in order to better understand the mathematical theory of derivative pricing models.

Probability Theory In Finance

Author: Seán Dineen
Publisher: American Mathematical Soc.
ISBN: 0821894900
Size: 13.18 MB
Format: PDF, ePub
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The use of the Black-Scholes model and formula is pervasive in financial markets. There are very few undergraduate textbooks available on the subject and, until now, almost none written by mathematicians. Based on a course given by the author, the goal of

Financial Derivatives In Theory And Practice

Author: Philip Hunt
Publisher: John Wiley & Sons
ISBN: 0470863609
Size: 42.39 MB
Format: PDF
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The term Financial Derivative is a very broad term which has come to mean any financial transaction whose value depends on the underlying value of the asset concerned. Sophisticated statistical modelling of derivatives enables practitioners in the banking industry to reduce financial risk and ultimately increase profits made from these transactions. The book originally published in March 2000 to widespread acclaim. This revised edition has been updated with minor corrections and new references, and now includes a chapter of exercises and solutions, enabling use as a course text. Comprehensive introduction to the theory and practice of financial derivatives. Discusses and elaborates on the theory of interest rate derivatives, an area of increasing interest. Divided into two self-contained parts ? the first concentrating on the theory of stochastic calculus, and the second describes in detail the pricing of a number of different derivatives in practice. Written by well respected academics with experience in the banking industry. A valuable text for practitioners in research departments of all banking and finance sectors. Academic researchers and graduate students working in mathematical finance.

Elementary Probability Theory

Author: Kai Lai Chung
Publisher: Springer Science & Business Media
ISBN: 0387215484
Size: 21.40 MB
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This book provides an introduction to probability theory and its applications. The emphasis is on essential probabilistic reasoning, which is illustrated with a large number of samples. The fourth edition adds material related to mathematical finance as well as expansions on stable laws and martingales. From the reviews: "Almost thirty years after its first edition, this charming book continues to be an excellent text for teaching and for self study." -- STATISTICAL PAPERS

Stochastic Processes

Author: Wolfgang Paul
Publisher: Springer Science & Business Media
ISBN: 3319003275
Size: 42.76 MB
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This book introduces the theory of stochastic processes with applications taken from physics and finance. Fundamental concepts like the random walk or Brownian motion but also Levy-stable distributions are discussed. Applications are selected to show the interdisciplinary character of the concepts and methods. In the second edition of the book a discussion of extreme events ranging from their mathematical definition to their importance for financial crashes was included. The exposition of basic notions of probability theory and the Brownian motion problem as well as the relation between conservative diffusion processes and quantum mechanics is expanded. The second edition also enlarges the treatment of financial markets. Beyond a presentation of geometric Brownian motion and the Black-Scholes approach to option pricing as well as the econophysics analysis of the stylized facts of financial markets, an introduction to agent based modeling approaches is given.

Introduction To Probability And Statistics For Science Engineering And Finance

Author: Walter A. Rosenkrantz
Publisher: CRC Press
ISBN: 9781584888130
Size: 31.56 MB
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Integrating interesting and widely used concepts of financial engineering into traditional statistics courses, Introduction to Probability and Statistics for Science, Engineering, and Finance illustrates the role and scope of statistics and probability in various fields. The text first introduces the basics needed to understand and create tables and graphs produced by standard statistical software packages, such as Minitab, SAS, and JMP. It then takes students through the traditional topics of a first course in statistics. Novel features include: Applications of standard statistical concepts and methods to the analysis and interpretation of financial data, such as risks and returns Cox–Ross–Rubinstein (CRR) model, also called the binomial lattice model, of stock price fluctuations An application of the central limit theorem to the CRR model that yields the lognormal distribution for stock prices and the famous Black–Scholes option pricing formula An introduction to modern portfolio theory Mean-standard deviation diagram of a collection of portfolios Computing a stock’s betavia simple linear regression As soon as he develops the statistical concepts, the author presents applications to engineering, such as queuing theory, reliability theory, and acceptance sampling; computer science; public health; and finance. Using both statistical software packages and scientific calculators, he reinforces fundamental concepts with numerous examples.

Probability And Statistics For Finance

Author: Svetlozar T. Rachev
Publisher: John Wiley & Sons
ISBN: 0470400935
Size: 15.65 MB
Format: PDF
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A comprehensive look at how probability and statistics is applied to the investment process Finance has become increasingly more quantitative, drawing on techniques in probability and statistics that many finance practitioners have not had exposure to before. In order to keep up, you need a firm understanding of this discipline. Probability and Statistics for Finance addresses this issue by showing you how to apply quantitative methods to portfolios, and in all matter of your practices, in a clear, concise manner. Informative and accessible, this guide starts off with the basics and builds to an intermediate level of mastery. • Outlines an array of topics in probability and statistics and how to apply them in the world of finance • Includes detailed discussions of descriptive statistics, basic probability theory, inductive statistics, and multivariate analysis • Offers real-world illustrations of the issues addressed throughout the text The authors cover a wide range of topics in this book, which can be used by all finance professionals as well as students aspiring to enter the field of finance.