Financial Econometrics Models and Methods By Oliver Linton
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Financial Econometrics Models and Methods By Oliver Linton

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Pages
557
File size
24.58 MB
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Digital PDF
Category
eBook[PDF]
About this ebook
The book Financial Econometrics: Models and Methods by Oliver Linton provides a thorough exploration of modern financial econometrics, bridging theoretical principles with real-world applications. It covers major developments in empirical finance over the past two decades, extending the core frameworks originally popularised in standard texts. [1, 2, 3]
The textbook is sequentially organised into the following core topics: [1]
🗒 Main Course Topics
  • Introduction and background – Contextual framework of financial markets and quantitative research foundations.
  • Econometric background – Review of the statistical and econometric foundations needed for modern financial time series analysis.
  • Return predictability and the efficient markets hypothesis – Core concepts testing whether asset returns can be predicted using historical prices.
  • Robust tests and tests of nonlinear predictability of returns – Advanced techniques handling non-standard distributions and complex, non-linear relationships in market data.
  • Empirical market microstructure – Analysis of order flows, trading mechanisms, bid-ask spreads, and transaction costs.
  • Event study analysis – Methodology tracking how specific corporate or economic events impact asset prices.
  • Portfolio choice and testing the capital asset pricing model (CAPM) – Statistical evaluation of the CAPM framework and mean-variance portfolio optimisation.
  • Multifactor pricing models – Econometric frameworks for structural factor designs, including Arbitrage Pricing Theory (APT) and empirical multi-factor models.
  • Present value relations – Mathematical and statistical tracking of stock prices, corporate dividends, and discount rate dynamics.
  • Intertemporal equilibrium pricing – Advanced asset pricing models that simulate consumer choice, risk aversion, and consumption patterns across time.
  • Volatility – In-depth measurement and modelling of financial volatility, featuring ARCH, GARCH, and stochastic volatility frameworks.
  • Continuous time processes – Mathematical models underlying derivative pricing, continuous asset paths, and Brownian motion.
  • Yield curve – Econometric modeling of fixed-income security pricing, interest rate term structures, and bond dynamics.
  • Risk management and tail estimation – Statistical analysis focusing on extreme market events, Value at Risk (VaR), and Expected Shortfall (ES). [1, 2, 3, 4, 5]
📊 Practical and Review Sections
  • Exercises and complements – Analytical and quantitative problems designed to test conceptual understanding.
  • Appendix – Supplementary technical notes and data foundations supporting the core chapters. [1, 2, 3]

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Topics

ARCH GARCH and stochastic volatility frameworks Contextual framework of financial markets and quantitative research foundations Continuous time processes – Mathematical models underlying derivative pricing Empirical market microstructure – Analysis of order flows trading mechanisms Event study analysis – Methodology tracking how specific corporate or economic events impact asset prices. Intertemporal equilibrium pricing – Advanced asset pricing models Multifactor pricing models – Econometric frameworks for structural factor designs Portfolio choice and testing the capital asset pricing model (CAPM) Present value relations – Mathematical and statistical tracking of stock prices Return predictability and the efficient markets hypothesis Risk management and tail estimation Robust tests and tests of nonlinear predictability of returns statistical and econometric foundations needed for modern financial time series analysis Value at Risk (VaR) and Expected Shortfall (ES) Volatility – In-depth measurement and modelling of financial volatility Yield curve – Econometric modeling of fixed-income security pricing
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