Financial modelling – and for that matter, quantitative finance – is a very crucial area of study for the decision makers to make informed and robust choices in matters of interest to the growth and survival of their organisations. Thus, the skills and knowledge (at least, in this book) must be possessed by every finance professional; risk analysts, quantitative analysts, asset and portfolio managers, compliance officers, Forex and Contract for Difference (CFD) traders, etc. Econometric and statistical models employed in financial modelling are too many to be captured under this course. The econometric models captured in this book are for the purposes of fostering understanding, appreciation, and the reality of the mathematics beneath the topics in econometrics. Broadly speaking, this book covers the various facets of regression models in this important field. Diagnostics on the linear regression model, Logit and Probit (Categorical Dependent Variable Models), Stationary and Non-Stationary Time Series, Cointegration and Error Correction Models (ECM), Autoregressive Distributed Lag (ARDL) Models, forecasting with ARIMA and Vector Autoregression (VAR) models, Panel Data Regression Models, and finally Asset Price/Return Volatility: ARCH and GARCH Models are illustrated for easy comprehension. (Nova).