The field of finance has experienced significant growth over the past few decades. Its main characteristic is that it utilizes and combines scientific findings from many different disciplines, attempting to depict and describe investment behavior with greater realism.

Financial econometrics employs a set of mathematical and statistical tools and techniques, as well as financial theory, to address various vital financial problems, such as the creation, estimation, and forecasting of financial models. The structure of the material in all chapters represents a "marriage" of theory with empirical applications and examples using real data analyzed in each chapter through the econometric software EViews.

The writing of the book is based on contemporary scientific developments presented in the global literature, as well as on the long-term research, consulting, and teaching experience of the authors in the field of econometrics. This book covers the basic concepts of financial theory that are essential for both undergraduate and graduate students who are interested in empirical methods in finance.

Additionally, it provides advanced knowledge to students who wish to familiarize themselves with recent techniques for analyzing time series, which they can apply in their undergraduate and master’s theses, as well as in their future research.

Table of Contents:

• Subject of Financial Econometrics
• Volatility
• The Capital Asset Pricing Model (CAPM)
• Exponential Smoothing
• Univariate Time Series: Linear Models
• The ARIMA Model – Box Jenkins Process
• Stochastic Volatility Models of the GARCH Family
• Hybrid Models
• Artificial Neural Networks