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Quantitative methods (economics)

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"Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors"--

Social sciences --- Quantitative methods in social research

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Microeconomics --- Quantitative methods (economics) --- micro-economie --- econometrie

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This treatise delves into the latest advancements in stochastic volatility models, highlighting the utilization of Markov chain Monte Carlo simulations for estimating model parameters and forecasting the volatility and quantiles of financial asset returns. The modeling of financial time series volatility constitutes a crucial aspect of finance, as it plays a vital role in predicting return distributions and managing risks. Among the various econometric models available, the stochastic volatility model has been a popular choice, particularly in comparison to other models, such as GARCH models, as it has demonstrated superior performance in previous empirical studies in terms of fit, forecasting volatility, and evaluating tail risk measures such as Value-at-Risk and Expected Shortfall. The book also explores an extension of the basic stochastic volatility model, incorporating a skewed return error distribution and a realized volatility measurement equation. The concept of realized volatility, a newly established estimator of volatility using intraday returns data, is introduced, and a comprehensive description of the resulting realized stochastic volatility model is provided. The text contains a thorough explanation of several efficient sampling algorithms for latent log volatilities, as well as an illustration of parameter estimation and volatility prediction through empirical studies utilizing various asset return data, including the yen/US dollar exchange rate, the Dow Jones Industrial Average, and the Nikkei 225 stock index. This publication is highly recommended for readers with an interest in the latest developments in stochastic volatility models and realized stochastic volatility models, particularly in regards to financial risk management.

Statistical science --- Quantitative methods (economics) --- statistiek --- econometrie --- statistisch onderzoek

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This elementary introduction was developed from lectures by the authors on business mathematics and the lecture "Analysis and Linear Algebra" for Bachelor's degree programmes. It is designed for courses in business administration and business informatics at universities, universities of applied sciences and cooperative universities. With the 5th edition, the title was changed to "Analysis and Linear Algebra". The treatment of sequences and series has been added and some exercises have been added to the introductory chapters. The focus is on teaching mathematical basics with regard to applications in business and financial mathematics. Contents from the upper secondary school are repeated in a compact form. Numerous examples and exercises make the book clear and promote understanding of interrelationships. The introduction is therefore also suitable for A-level students at business schools. The detailed solutions to the exercises are provided on the book's website. The book is therefore also very suitable for self-study. The contents Elementary basics Functions Differential calculus Integral calculus Linear Algebra Functions with several variables Financial mathematics The Authors Prof. Dr. Thomas Holey is head of the Business Information Systems programme at the Baden-Württemberg Cooperative State University Mannheim and represents the basic mathematical subjects in teaching. Prof. Dr. Armin Wiedemann teaches formal methods of computer science as well as the mathematical subjects at the Baden-Württemberg Cooperative State University Mannheim. He is retired now.

Philosophy of science --- Quantitative methods (economics) --- Mathematics --- wetenschapsfilosofie --- econometrie --- wiskunde