Chapter 1, Time Series Modeling in the Financial Industry, introduces time series modeling, and discusses its importance, the characteristics and challenges of data, and explains its use in the financial industry. The chapter also discusses the way forecasting is used across industries and what is meant by a good or bad forecast.
Chapter 2, Forecasting Stock Prices and Portfolio Decisions using Time Series, discusses the concept of portfolio forecasting and the decisions involved in managing portfolios. After exploring the forecasting process and the visualization of time series data, the chapter discusses modeling techniques and explains how to select the most suitable one based on real-world modeling examples.
Chapter 3, Credit Risk Management, provides context regarding the highly regulated nature of the industry. Basel norms and key terms such as PD, LGD, EAD, and EL are discussed. A PD model build methodology is briefly discussed.
Chapter 4, Budget and Demand Forecasting, helps create an understanding of the Markov model and showcases how to build a model. The chapter goes on to compare the Markov model forecast with ARIMA-generated forecasts. It also explains how Markov Chain Monte Carlo can be used for data imputation.
Chapter 5, Inflation Forecasting for Financial Planning, defines inflation, explores the reasons for inflation, and discusses its outcomes using the theory of the Phillips curve. The chapter also shows how to leverage various procedures for data quality checks. Univariate and multivariate modeling techniques are used for forecasting and a comparison of the results.
Chapter 6, Managing Customer Loyalty using Time Series Data, introduces survival modeling, data preparation techniques, and various methodologies, including parametric and semi-parametric methods. It does this in the context of solving a business problem related to customer loyalty.
Chapter 7, Transforming Time Series – Market Basket and Clustering, provides multiple business examples while discussing the background and methodology of these techniques.
