Content, progress and pedagogy of the module

This module applies statistical and econometric methods to analyse time series of prices and returns in the financial markets. This includes, but is not limited to, the estimation of expected returns on stocks, tests of return predictability, the modelling of risk and volatility, and the determination of returns based on factor fundamentals.

The aim of the module is to provide the student with the tools necessary to conduct advanced empirical studies of financial market data and to contribute to a deep understanding of the determinants of financial asset prices and returns.

The module also relies on the application of time series models in statistical software for the analysis of financial data.

Learning objectives

Knowledge

The objective is that the student after the module possesses the necessary knowledge on:

• solid understanding of statistical and econometric methods applied to financial prices and returns.
• relevance, reliability and validity of time series methods in the financial data context.
• how to apply several econometric models in statistical software and analyse their results, validity and relevance.

Skills

The objective is that the student after the module possesses the necessary skills in:

• analysing financial time series data and finding important patterns, including the use of relevant software.
• formulating time series models for the analysis of financial data, including testing financial theories.
• analysing results regarding validity, relevance, and limitations of econometric models especially in connection to their application in statistical software.
• discussing the possibilities and challenges within empirical finance scientifically, practically and contextually.

Competences

The objective is that the student after the module possesses the necessary competences in:

• reflecting upon the theoretical frame of reference to independently perform and justify the choice of theories and methods to analyse financial prices and returns.
• building models that can address issues related to the real world.
• analysing prices and returns of financial assets using appropriate statistical and econometric techniques and software.

Type of instruction

For information see § 17.

Exam

Exams