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Overview: Financial Data Analysis with R: Monte-Carlo Validation is a comprehensive exploration of statistical methodologies and their applications in finance. Readers are taken on a journey in each chapter through practical explanations and examples, enabling them to develop a solid foundation of these methods in R and their applications in finance. This book aims to serve as a comprehensive guide for students, researchers, and practitioners seeking to harness the power of R for analyzing financial data. The journey begins with a solid foundation in both financial theory and R programming, gradually progressing to more advanced topics such as time series analysis, risk and risk management. The practical examples provided throughout the book are rooted in real-world financial scenarios, offering readers a bridge between academic concepts and practical applications. The book goes beyond just teaching statistical methods in R and incorporates a unique section of informative Monte-Carlo simulations. These Monte-Carlo simulations are uniquely designed to showcase the reader the potential consequences and misleading conclusions that can arise when fundamental model assumptions are violated. Through step-by-step tutorials and realworld cases, readers will learn how and why model assumptions are important to follow. With a focus on practicality, Financial Data Analysis with R: Monte-Carlo Validation equips readers with the skills to construct and validate financial models using R.
Genre: Non-Fiction > Tech & Devices
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