Xem 1-20 trên 68 kết quả Quantitative finance
  • In this book I present classical quantitative finance. The book is suitable for students on advanced undergraduate finance and derivatives courses, MBA courses, and graduate courses that are mainly taught, as opposed to ones that are based on research. The text is quite self-contained, with, I hope, helpful sidebars (‘Time Out’) covering the more mathematical aspects of the subject for those who feel a little bit uncomfortable. Little prior knowledge is assumed, other than basic calculus, even stochastic calculus is explained here in a simple, accessible way.

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  • Tham khảo sách 'quantitative finance: its development , mathematical foundations, and current scope', kinh doanh - tiếp thị, quản trị kinh doanh phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả

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  • The aim of this book is to bring students of economics and finance who have only an introductory background in mathematics up to a quite advanced level in the subject, thus preparing them for the core mathematical demands of econometrics, economic theory, quantitative finance and mathematical economics, which they are likely to encounter in their final-year courses and beyond. The level of the book will also be useful for those embarking on the first year of their graduate studies in Business, Economics or Finance.

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  • This work gives an overview of core topics in the “investment” side of finance, stressing the quantitative aspects of the subject. The presentation is at a moderately sophisticated level that would be appropriate for masters or early doctoral students in economics, engineering, finance, and mathematics. It would also be suitable for advanced and well motivated undergraduates-provided they are adequately prepared in math, probability, and statistics.

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  • This book is designed for students and researchers who want to develop professional skill in modern quantitative applications in nance. The Center for Applied Statistics and Economics (CASE) course at Humboldt-Universitat zu Berlin that forms the basis for this book is o ered to interested students who have had some experience with probability, statistics and software applications but have not had advanced courses in mathematical nance.

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  • English for Careers Finance 1 gives you the language, information, and skills you need to start your career or work towards the ICFE (International Certificate in Financial English exams. Learn the English you need to do the job, practise language in real work situations, and learn specialist vocabulary on every page.

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  • This book presents and develops major numerical methods currently used for solving problems arising in quantitative finance. Our presentation splits into two parts. Part I is methodological, and offers a comprehensive toolkit on numerical methods and algorithms. This includes Monte Carlo simulation, numerical schemes for partial differential equations, stochastic optimization in discrete time, copula functions, transform-based methods and quadrature techniques. Part II is practical, and features a number of self-contained cases.

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  • ..Applied and Numerical Harmonic Analysis Series Editor John J. Benedetto University of Maryland Editorial Advisory Board Akram Aldroubi Vanderbilt University Ingrid Daubechies Princeton University Christopher Heil Georgia Institute of Technology James McClellan Georgia Institute of Technology Michael Unser Swiss Federal Institute of Technology, Lausanne M. Victor Wickerhauser Washington University Douglas Cochran Arizona State University Hans G.

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  • Stochastic Calculus of Variations (or Malliavin Calculus) consists, in brief, in constructing and exploiting natural differentiable structures on abstract probability spaces; in other words, Stochastic Calculus of Variations proceeds from a merging of differential calculus and probability theory. As optimization under a random environment is at the heart of mathematical finance, and as differential calculus is of paramount importance for the search of extrema, it is not surprising that Stochastic Calculus of Variations appears in mathematical finance.

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  • The predictive power of stock market indicator Ben Branch The journal of financial and quantitive analysis

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  • This book is primarily for PhD scientists and engineers who want to learn about quantitative finance, and for graduate students in finance programs’. Practicing quantitative analysts (“quants”) and research workers will find topics of interest. There are even essays with no equations for non-technical managers.

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  • The long-awaited sequel to the "Concepts and Practice of Mathematical Finance" has now arrived. Taking up where the first volume left off, a range of topics is covered in depth. Extensive sections include portfolio credit derivatives, quasi-Monte Carlo, the calibration and implementation of the LIBOR market model, the acceleration of binomial trees, the Fourier transform in option pricing and much more. Throughout Mark Joshi brings his unique blend of theory, lucidity, practicality and experience to bear on issues relevant to the working quantitative analyst....

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  • This book is written for those physicists who want to work on Wall Street but have not bothered to read anything about Finance. This is a crash course that the author, a physicist himself, needed when he landed a financial data analyst job and became fascinated with the huge data sets at his disposal. More broadly, this book addresses the reader with some background in science or engineering (college-level math helps) who is willing to learn the basic concepts and quantitative methods used in modern finance.

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  • Driven by the necessity to incorporate the observed stylized features of asset prices, continuous-time stochastic modeling has taken a predominant role in the financial literature over the past two decades. Most of the proposed models are particular cases of a stochastic volatility component driven by a Wiener process superposed with a pure-jump component accounting for the

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  • It has been mentioned in the Preface that the material of this book has been arranged in a way that should make it accessible to as wide a readership as possible. Prospective readers will have different backgrounds and objectives. The following four groups are suggestions to help use the book more efficiently.

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  • THE VENTURE CAPITAL INDUSTRY has grown dramatically over the last decade. In the United States, venture capital (hereafterVC) investments grew from $3.3 billion in 1990 to $100 billion in 2000. In Europe, funds invested in VC grew from $6.4 billion in 1998 to more than $10 billion in 1999.The success of VC is largely due to the active involvement of the venture capitalists.These so-called hands-on investors carefully select the investment projects they are proposed (Sahlman (1988, 1990)) and remain deeply involved in those projects after investment is realized.

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  • Why are we interested in solving simultaneous equations? We often have to find a point which satisfies more than one equation simultaneously, for example when finding equilibrium price and quantity given supply and demand functions.  To be an equilibrium, the point (Q; P) must lie on both the supply and demand curves.  Now both supply and demand curves can be plotted on the same diagram and the point(s) of intersection will be the equilibrium (equilibria)

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  • Lecture Quantiative methods for bussiness - Chapter 9 introduce linear programming applications in marketing, finance, and operations. This chapter includes contents: Marketing applications, financial applications, operations management applications.

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  • The term ìspreadsheetî covers a wide variety of elements useful for quantitative analysis of all kinds. Essentially, a spreadsheet is a simple tool consisting of a matrix of cells that can store numbers, text, or formulas. The spreadsheetís power comes from its ability to recalculate results as you change the contents of other cells. No longer does the user need to do these calculations by hand or on a calculator.

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  • The goal of this book is to develop robust, accurate and efficient numerical methods to price a number of derivative products in quantitative finance.We focus on one-factor and multi-factor models for a wide range of derivative products such as options, fixed income products, interest rate products and ‘real’ options. Due to the complexity of these products it is very difficult to find exact or closed solutions for the pricing functions. Even if a closed solution can be found it may be very difficult to compute. For this and other reasons we need to resort to approximate methods.

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