Xem 1-20 trên 59 kết quả Mathematical demands
  • 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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  • ..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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  • A shift in demand that moves the demand curve to the right causes equilibrium price and quantity to rise. A shift in supply that moves the supply curve to the left causes equilibrium price to rise and equilibrium quantity to fall.

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  • Elasticity is a measure of the responsiveness of one variable to a change in another. The most commonly used elasticity concept is price elasticity of demand. The price elasticity of demand is the percentage change in quantity demanded divided by the percentage change in price.

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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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  • The demand curve is the graphic representation of the relationship between price and quantity demanded. The demand curve slopes downward and to the right. As the price goes up, the quantity demanded goes down. The demand curve is the graphic representation of the relationship between price and quantity demanded. The demand curve slopes downward and to the right. As the price goes up, the quantity demanded goes down.

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  • 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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  • 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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  • Clearly and elegantly presented, Mathematical Methods in Science and Engineering provides a coherent treatment of mathematical methods, bringing advanced mathematical tools to a multidisciplinary audience. The growing interest in interdisciplinary studies has brought scientists from many disciplines such as physics, mathematics, chemistry, biology, economics, and finance together, which has increased the demand for courses in upper-level mathematical techniques.

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  • Economists have an answer to the question of why people behave as they do — self interest. Economists' analysis of individual choice does not deny individual differences. A good beginning in understanding individual choice is to focus on the rational part of people's behavior.

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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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  • Tham khảo sách 'basic mathematics for economists second edition', 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 mathematics students need to learn today is not the same mathematics that their parents and grandparents needed to learn. When today's students become adults, they will face new demands for mathematical proficiency that school mathematics should attempt to anticipate. Moreover, mathematics is a realm no longer restricted to a select few. All young Americans must learn to think mathematically, and they must think mathematically to learn.

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  • Learning skills and remembering facts in mathematics are important but they are only the means to an end. Facts and skills are not important in themselves. They are important when we need them to solve a problem. Students will remember facts and skills easily when they use them to solve real problems. As well as using mathematics to solve real-life problems, students should also be taught about the different parts of mathematics, and how they fit together.

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  • This text offers the perfect introduction to social benefit-cost analysis. The book closely integrates the theory and practice of benefit-cost analysis using a spreadsheet framework. The spreadsheet model is constructed in a truly original way which contributes to transparency, provides a check on the accuracy of the analysis, and facilitates sensitivity, risk and alternative scenario assessment. A case study inco

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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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  • Stable laws { also called -stable or Levy-stable { are a rich family of probability distributions that allow skewness and heavy tails and have many interesting mathematical properties. They appear in the context of the Generalized Central Limit Theorem which states that the only possible non-trivial limit of normalized sums of independent identically distributed variables is -stable. The Standard Central Limit Theorem states that the limit of normalized sums of independent identically distributed terms with nite variance is Gaussian ( -stable with = 2).

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  • 4 Graphs and functions Interpret the meaning of functions and inverse functions. Draw graphs that correspond to linear, non-linear and composite functions. Find the slopes of linear functions and tangents to non-linear function by graphical analysis. Use the slope of a linear demand function to calculate point elasticity.

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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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