Time Series+finance

Comprehensive guide to time series analysis and forecasting techniques with Python, covering ARIMA, SARIMA, Prophet

Nonlinear time series methods have developed rapidly over a quarter of a century and have reached an advanced state of maturity during the last decade. Implementations of these methods for experimental data are now widely accepted and fairly routine, however genuinely useful applications remain rare. The aim of this book is to focus on the practice of applying these methods to solve real problems. It is my hope that the methods presented here are sufficiently accessible, and the examples sufficiently detailed, that practitioners in other areas may use this work to begin considering further applications of nonlinear time series analysis in their own disciplines.
This volume is therefore intended to be accessible to a fairly broad audience:
both specialists in nonlinear time series analysis (for whom many of these techniques may be new); and, scientists in other fields (who may be looking to apply these methods within their speciality). For the experimental scientist looking to use these methods, MATLAB implementation of the underlying algorithms accompany this book.

A new edition of the comprehensive, hands-on guide to financial time series, now featuring S-Plus® and R software
Time Series: Applications to Finance with R and S-Plus®, Second Edition is designed to present an in-depth introduction to the conceptual underpinnings and modern ideas of time series analysis.

Elements of Financial Time Series fills a gap in the market in the area of financial time series analysis by giving both conceptual and practical illustrations. Examples and discussions in the later chapters of the book make recent developments in time series more accessible.

The field of financial econometrics has exploded over the last decade. This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. This is the first book to show the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts.