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Planning (firm) --- Finance --- Commercial statistics --- Statistical methods --- Commercial statistics. --- Statistical methods. --- Finance - Statistical methods
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Finance --- Economics --- Econometrics --- Statistical methods --- Econometrics. --- Statistical methods. --- Finance - Statistical methods --- Economics - Statistical methods
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An Introduction to Machine Learning in Finance, With Mathematical Background, Data Visualization, and R Nonparametric function estimation is an important part of machine learning, which is becoming increasingly important in quantitative finance. Nonparametric Finance provides graduate students and finance professionals with a foundation in nonparametric function estimation and the underlying mathematics. Combining practical applications, mathematically rigorous presentation, and statistical data analysis into a single volume, this book presents detailed instruction in discrete chapters that allow readers to dip in as needed without reading from beginning to end. Coverage includes statistical finance, risk management, portfolio management, and securities pricing to provide a practical knowledge base, and the introductory chapter introduces basic finance concepts for readers with a strictly mathematical background. Economic significance is emphasized over statistical significance throughout, and R code is provided to help readers reproduce the research, computations, and figures being discussed. Strong graphical content clarifies the methods and demonstrates essential visualization techniques, while deep mathematical and statistical insight backs up practical applications. Written for the leading edge of finance, Nonparametric Finance: • Introduces basic statistical finance concepts, including univariate and multivariate data analysis, time series analysis, and prediction • Provides risk management guidance through volatility prediction, quantiles, and value-at-risk • Examines portfolio theory, performance measurement, Markowitz portfolios, dynamic portfolio selection, and more • Discusses fundamental theorems of asset pricing, Black-Scholes pricing and hedging, quadratic pricing and hedging, option portfolios, interest rate derivatives, and other asset pricing principles • Provides supplementary R code and numerous graphics to reinforce complex content Nonparametric function estimation has received little attention in the context of risk management and option pricing, despite its useful applications and benefits. This book provides the essential background and practical knowledge needed to take full advantage of these little-used methods, and turn them into real-world advantage. Jussi Klemelä, PhD, is Adjunct Professor at the University of Oulu. His research interests include nonparametric function estimation, density estimation, and data visua...
Finance --- Statistical methods. --- Mathematical models. --- Finance - Statistical methods --- Finance - Mathematical models
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The Handbooks in Finance are intended to be a definitive source for comprehensive and accessible information in the field of finance. Each individual volume in the series should present an accurate self-contained survey of a sub-field of finance, suitable for use by finance and economics professors and lecturers, professional researchers, graduate students and as a teaching supplement. The goal is to have a broad group of outstanding volumes in various areas of finance. The Handbook of Heavy Tailed Distributions in Finance is the first handbook to be published in this series. This vo
Finance --- Statistical methods --- Financial risk. --- Business risk (Finance) --- Money risk (Finance) --- Risk --- Statistical methods. --- Finance - Statistical methods
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This respected high-level text is aimed at students and professionals working on random processes in various areas, including physics and finance. The first author, Melvin Lax (1922-2002) was a distinguished Professor of Physics at City College of New York and a member of the U. S. National Academy of Sciences, and is widely known for his contributions to our understanding of random processes in physics. Most chapters of this book are outcomes of the class notes which Lax taught at the City University of New York from 1985 to 2001. The material is unique as it presents the theoretical framework of Lax's treatment of random processes, from basic probability theory to Fokker-Planck and Langevin Processes, and includes diverse applications, such as explanations of very narrow laser width, analytical solutions of the elastic Boltzmann transport equation, and a critical viewpoint of mathematics currently used in the world of finance.
Statistical physics --- Stochastic processes --- Finance --- Statistical methods --- Stochastic processes. --- Statistical methods. --- -530.15828 --- Funding --- Funds --- Economics --- Currency question --- Random processes --- Probabilities --- Finance - Statistical methods
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This book concerns the use of concepts from statistical physics in the description of financial systems. The authors illustrate the scaling concepts used in probability theory, critical phenomena, and fully developed turbulent fluids. These concepts are then applied to financial time series. The authors also present a stochastic model that displays several of the statistical properties observed in empirical data. Statistical physics concepts such as stochastic dynamics, short- and long-range correlations, self-similarity and scaling permit an understanding of the global behaviour of economic systems without first having to work out a detailed microscopic description of the system. Physicists will find the application of statistical physics concepts to economic systems interesting. Economists and workers in the financial world will find useful the presentation of empirical analysis methods and well-formulated theoretical tools that might help describe systems composed of a huge number of interacting subsystems.
Finance --- Statistical physics --- Physics --- Mathematical statistics --- Mathematical models --- Statistical methods --- General and Others --- Finances --- Physique statistique --- Méthodes statistiques --- Modèles mathématiques --- Statistical physics. --- Statistical methods. --- Mathematical models. --- E-books --- Econophysics. --- Economics --- Finance - Statistical methods --- Finance - Mathematical models
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The interaction between mathematicians and statisticians reveals to be an effective approach for dealing with actuarial, insurance and financial problems, both in an academic and in an operative perspective. The international conference MAF 2008, held at the University Ca’ Foscari of Venezia (Italy) in 2008, had precisely this purpose, and the collection here published gathers a selection of about the one hundred papers presented at the conference and successively referred and reviewed to this aim. They cover a wide variety of subjects in actuarial, insurance and financial fields, all treated in light of the successful cooperation between the two quantitative approaches.
Finance -- Statistical methods -- Congresses. --- Finance -- Statistical methods. --- Insurance -- Mathematical models -- Congresses. --- Insurance -- Mathematical models. --- Finance --- Insurance --- Business & Economics --- Economic Theory --- Statistical methods --- Mathematical models --- Mathematical statistics. --- Economics --- Economic theory --- Political economy --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Mathematics. --- Business mathematics. --- Applied mathematics. --- Engineering mathematics. --- Economics, Mathematical. --- Actuarial science. --- Statistics. --- Macroeconomics. --- Quantitative Finance. --- Actuarial Sciences. --- Business Mathematics. --- Statistical Theory and Methods. --- Macroeconomics/Monetary Economics//Financial Economics. --- Applications of Mathematics. --- Social sciences --- Economic man --- Statistics --- Probabilities --- Sampling (Statistics) --- Finance. --- Math --- Science --- Arithmetic, Commercial --- Business --- Business arithmetic --- Business math --- Commercial arithmetic --- Funding --- Funds --- Currency question --- Economics, Mathematical . --- Statistics . --- Engineering --- Engineering analysis --- Mathematical analysis --- Statistical analysis --- Statistical data --- Statistical science --- Econometrics --- Mathematical economics --- Methodology
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Finance --- Mathematical statistics --- Finances --- Statistical methods. --- Méthodes statistiques --- Statistical methods --- 519.2 --- 336.7 --- -Funding --- Funds --- Economics --- Currency question --- Probability. Mathematical statistics --- Geldwezen. Kredietwezen. Bankwezen. Financien. Monetaire econonomie. Beurswezen --- -Probability. Mathematical statistics --- 336.7 Geldwezen. Kredietwezen. Bankwezen. Financien. Monetaire econonomie. Beurswezen --- 519.2 Probability. Mathematical statistics --- -336.7 Geldwezen. Kredietwezen. Bankwezen. Financien. Monetaire econonomie. Beurswezen --- Funding --- Méthodes statistiques --- Finance - Statistical methods
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Statistical Tools for Finance and Insurance presents ready-to-use solutions, theoretical developments and method construction for many practical problems in quantitative finance and insurance. Written by practitioners and leading academics in the field, this book offers a unique combination of topics from which every market analyst and risk manager will benefit. Features of the significantly enlarged and revised second edition: Offers insight into new methods and the applicability of the stochastic technology Provides the tools, instruments and (online) algorithms for recent techniques in quantitative finance and modern treatments in insurance calculations Covers topics such as - expected shortfall for heavy tailed and mixture distributions* - pricing of variance swaps* - volatility smile calibration in FX markets - pricing of catastrophe bonds and temperature derivatives* - building loss models and ruin probability approximation - insurance pricing with GLM* - equity linked retirement plans*(new topics in the second edition marked with*) Presents extensive examples.
Finance -- Statistical methods. --- Finance. --- Insurance -- Statistical methods. --- Insurance. --- Mathematics --- Finance --- Business & Economics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Insurance --- Statistical methods. --- Actuarial statistics --- Insurance statistics --- Statistics. --- Economics, Mathematical. --- Statistics for Business/Economics/Mathematical Finance/Insurance. --- Quantitative Finance. --- Statistics for Business, Management, Economics, Finance, Insurance. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Funding --- Funds --- Economics --- Currency question --- Statistics . --- Economics, Mathematical . --- Mathematical economics --- Methodology
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This textbook emphasizes the applications of statistics and probability to finance. Students are assumed to have had a prior course in statistics, but no background in finance or economics. The basics of probability and statistics are reviewed and more advanced topics in statistics, such as regression, ARMA and GARCH models, the bootstrap, and nonparametric regression using splines, are introduced as needed. The book covers the classical methods of finance such as portfolio theory, CAPM, and the Black-Scholes formula, and it introduces the somewhat newer area of behavioral finance. Applications and use of MATLAB and SAS software are stressed. The book will serve as a text in courses aimed at advanced undergraduates and masters students in statistics, engineering, and applied mathematics as well as quantitatively oriented MBA students. Those in the finance industry wishing to know more statistics could also use it for self-study. David Ruppert is the Andrew Schultz, Jr. Professor of Engineering, School of Operations Research and Industrial Engineering, Cornell University. He received a PhD in Statistics from Michigan State University in 1977 and taught for ten years in the Department of Statistics at the University of North Carolina at Chapel Hill. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics and a winner of the Wilcoxon Prize for the best practical applications paper in Technometrics. He is former Editor of the Institute of Mathematical Statistics's Lecture Notes-Monographs Series, former Associate Editor of The American Statistician and The Annals of Statistics, and currently Associate Editor of Biometrics and The Journal of the American Statistical Associate. He has published over 80 scientific papers and three books, Transformation and Weighting in Regression, Measurement Error in Nonlinear Models, and Semiparametric Regression.
Private finance --- Mathematical statistics --- Finance --- Statistics. --- Finances --- Statistique --- Statistical methods. --- Méthodes statistiques --- Statistics --- Statistical methods --- 519.2 --- -Statistics --- Statistical analysis --- Statistical data --- Statistical science --- Mathematics --- Econometrics --- Funding --- Funds --- Economics --- Currency question --- Probability. Mathematical statistics --- 519.2 Probability. Mathematical statistics --- Méthodes statistiques --- Statistics . --- Economics, Mathematical . --- Statistics for Business, Management, Economics, Finance, Insurance. --- Quantitative Finance. --- Statistical Theory and Methods. --- Mathematical economics --- Methodology --- Finance - Statistical methods --- Probabilités
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