About the book
Financial markets, which do not get stuck only in theoretical structure and develop in practice, play an important role in the sustainable growth of the economy. The starting point of the financial models is the uncertainty faced by investors that includes the uncertainty in the behavior and thus the uncertainty in market prices. Therefore, the existence of the financial economy is based on uncertainty. The structure and effect of fluctuations are determined by using econometrics theory in the modeling and estimation process of uncertainties in financial models. Development of econometrics that makes use of data, statistical inference methods and structural or descriptive modeling to solve economic problems has been paralleled by increasing variety and complexity of financial products. Efforts to measure fluctuations in terms of time, dimension and turning/breaking points in the context of financial developments and the desire to have the best return in financial market practices with the minimum loss can be counted as some of the reasons why econometrics theory develops from linear to non-linear models. Financial market mechanisms can be better explained by the development of models in the domains of martingales and non-linear time series, the use of parametric and non-parametric estimation methods, the use of diffusion equations, and an approximation for pricing and derivatives. This book aims to outline the econometrics models readily applicable to financial markets using linear and non-linear approaches such as GARCH-type models, Markov Switching, Threshold Models, Hybrid Models,State Space Models, Artifical Neural Networks, Genetic Algorithms, Big Data, Forecasting and Model Evaluation, Value at Risk and Other Risk Metrics, Option Portfolios, Scenario Analysis, Stress Testing, Capital Allocation, Portfolio Mapping, Extreme Value Theory and others.