Title	Financial Econometrics, Mathematics and Statistics [electronic resource] : Theory, Method and Application / by Cheng-Few Lee, Hong-Yi Chen, John Lee
Imprint	New York, NY : Springer New York : Imprint: Springer, 2019
Edition	1st ed. 2019
Connect to	https://doi.org/10.1007/978-1-4939-9429-8
Descript	XX, 655 p. 129 illus., 57 illus. in color. online resource

This rigorous textbook introduces graduate students to the principles of econometrics and statistics with a focus on methods and applications in financial research. Financial Econometrics, Mathematics, and Statistics illustrates tools and methods important for both finance and accounting that assist with asset pricing, corporate finance, options and futures, and conducting financial accounting research. Divided into four parts, the text offers insight into the following models and topics, among others: • Multiple linear regression • Time-series analysis • Option pricing models • Risk management • Heteroskedasticity • Itô’s Calculus • Spurious regression • Errors-in-variable Written by leading academics in the quantitative finance field, this book allows readers to implement the principles behind financial econometrics and statistics through real-world applications and problem sets. It will appeal to a less-served market of advanced students and scholars in finance, economics, accounting, and statistics

Introduction to Financial Econometrics and Statistics -- Part A: Regression and Financial Econometrics -- Multiple Linear Regression -- Other Topics in Applied Regression Analysis.-Simultaneous Equation Models.-Econometric Approach to Financial Analysis, Planning, and Forecasting -- Fixed Effect vs Random Effect in Finance Research -- Alternative Methods to Deal with Measurement Error.-Three Alternative Errors-in-Variables Estimation Methods in Testing Capital Asset Pricing Model -- Spurious Regression and Data Mining in Conditional Asset Pricing Models.-Time-Series Analysis and Its Applications.-Time-Series: Analysis, Model, and Forecasting.-Hedge Ratio and Time-Series Analysis -- The Binomial, Multi-Nominal Distributions and Option Pricing Model -- Two Alternative Binomial Option Pricing Model Approaches to Derive Black-Scholes Option Pricing Model.-Normal, Lognormal Distribution, and Option Pricing Model.-Copula, Correlated Defaults, and Credit VaR.-Multivariate Analysis: Discriminant Analysis and Factor Analysis.-Stochastic Volatility Option Pricing Models -- Alternative Method to Estimate Implied Variance: Review and Comparison -- Numerical Valuation of Asian Options with Higher Moments in the Underlying Distribution.-Itô’s Calculus: Derivation of the Black-Scholes Option Pricing Model.-Alternative Methods to Derive Option Pricing Models.-Constant Elasticity of Variance Option Pricing Model: Integration and Detailed Derivation -- Option Pricing and Hedging Performance under Stochastic Volatility and Stochastic Interest Rates.-Non-Parametric Method for European Option Bounds