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Nonlinear Optimization with Financial Applications
The book introduces the key ideas behind practical nonlinear optimization. Computational finance—an increasingly popular area of mathematics degree programmes—is combined here with the study of an important class of numerical techniques. The essentials of most currently popular algorithms are described and their performance is demonstrated on a range of optimization problems arising in financial mathematics. Theoretical convergence properties of methods are stated and formal proofs are provided in enough cases to be instructive rather than overwhelming. Practical behaviour of methods is illustrated by computational examples and discussions of efficiency, accuracy and computational costs. Supporting software for the examples and exercises is available
Financial mathematics, derivatives and structured products
Introduces readers to the financial markets, derivatives, structured products and how the products are modelled and implemented by practitioners. In addition, it equips readers with the necessary knowledge of financial markets needed in order to work as product structurers, traders, sales or risk managers. As the book seeks to unify the derivatives modelling and the financial engineering practice in the market, it will be of interest to financial practitioners and academic researchers alike. Further, it takes a different route from the existing financial mathematics books, and will appeal to students and practitioners with or without a scientific background. The book can also be used as a textbook for the following courses: Financial Mathematics (undergraduate level) Stochastic Modelling in Finance (postgraduate level) Financial Markets and Derivatives (undergraduate level) Structured Products and Solutions (undergraduate/postgraduate level)
Financial economics and econometrics
Covers financial data and univariate models; asset returns; interest rates, yields and spreads; volatility and correlation; and corporate finance and policy. Each chapter begins with a theory in financial economics, followed by econometric methodologies which have been used to explore the theory. Next, the chapter presents empirical evidence and discusses seminal papers on the topic. Boxes offer insights on how an idea can be applied to other disciplines such as management, marketing and medicine, showing the relevance of the material beyond finance. Readers are supported with plenty of worked examples and intuitive explanations throughout the book, while key takeaways, ‘test your knowledge’ and ‘test your intuition’ features at the end of each chapter also aid student learning.
Mathematical Formulas for Economists
The present collection of formulas has been composed for students of economics or management science at universities, colleges and trade schools. It contains basic knowledge in mathematics, financial mathematics and statistics in a compact and clearly arranged form. This volume is meant to be a reference work to be used by students of undergraduate courses together with a textbook and by researchers in need of exact statements of mathematical results. People dealing with practical or applied problems will also find this collection to be an efficient and easy-to-use work of reference.
Mathematical Formulas for Economists
This collection of formulas constitutes a compendium of mathematics for eco nomics and business. It contains the most important formulas, statements and algorithms in this significant subfield of modern mathematics and addresses primarily students of economics or business at universities, colleges and trade schools. But people dealing with practical or applied problems will also find this collection to be an efiicient and easy-to-use work of reference. First the book treats mathematical symbols and constants, sets and state ments, number systems and their arithmetic as well as fundamentals of com binatorics. The chapter on sequences and series is followed by mathematics of finance, the representation of functions of one and several independent vari ables, their differential and integral calculus and by differential and difference equations. In each case special emphasis is placed on applications and models in economics. The chapter on linear algebra deals with matrices, vectors, determinants and systems of linear equations. This is followed by the representation of struc tures and algorithms of linear programming. Finally, the reader finds formu las on descriptive statistics (data analysis, ratios, inventory and time series analysis), on probability theory (events, probabilities, random variables and distributions) and on inductive statistics (point and interval estimates, tests). Some important tables complete the work.
Math for business and economics : Compedium of essential formulas
This mathematical formulary is presented in a practice-oriented, clear, and understandable manner, as it is needed for meaningful and relevant application in global business, as well as in the academic setting and economic practice. The topics presented include but are not limited to mathematical signs and symbols, logic, arithmetic, algebra, linear algebra, combinatorics, and financial mathematics, including an international comparison between different national methods used in the calculation of interest, optimization of linear models, functions, differential calculus, integral calculus, elasticities, annuity calculation, economic functions, and the Peren Theorem.
Martingales and financial mathematics in discrete time
This book is entirely devoted to discrete time and provides a detailed introduction to the construction of the rigorous mathematical tools required for the evaluation of options in financial markets. Both theoretical and practical aspects are explored through multiple examples and exercises, for which complete solutions are provided. Particular attention is paid to the Cox, Ross and Rubinstein model in discrete time.
Binomial models in finance
This book deals with many topics in modern financial mathematics in a way that does not use advanced mathematical tools and shows how these models can be numerically implemented in a practical way. The book is aimed at undergraduate students, MBA students, and executives who wish to understand and apply financial models in the spreadsheet computing environment.The basic building block is the one-step binomial model where a known price today can take one of two possible values at the next time. In this simple situation, risk neutral pricing can be defined and the model can be applied to price forward contracts, exchange rate contracts, and interest rate derivatives.
Big Data Science in Finance
Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Examines the mathematics, theory, and practical use of the revolutionary techniques that are transforming the industry. Designed for mathematically-advanced students and discerning financial practitioners alike, this energizing book presents new, cutting-edge content based on world-class research taught in the leading Financial Mathematics and Engineering programs in the world. Marco Avellaneda, a leader in quantitative finance, and quantitative methodology author Irene Aldridge help readers harness the power of Big Data. Provides a complete account of Big Data that includes proofs, step-by-step applications, and code samples Explains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) Covers vital topics in the field in a clear, straightforward manner Compares, contrasts, and discusses Big Data and Small Data Includes Cornell University-tested educational materials such as lesson plans, end-of-chapter questions, and downloadable lecture slides
