Module:

Latest Module Specifications

Current Academic Year 2025 - 2026

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Module Title
Module Code	(ITS: EF5162)
Faculty		School
NFQ level		Credit Rating

Description

Introduction to the theory and practice of financial time series analysis. Students will learn statistical methods to characterize empirical features of financial time series data, apply relevant time series methods to analyze data using appropriate statistical software, critically evaluate empirical results reported in academic journal articles.

Learning Outcomes

1. analyse financial time series data using appropriate statistical methods and software
2. explain theoretical properties of financial time series models
3. validate past empirical analyses published in academic journals
4. apply financial econometric techniques to quantitatively address practical issues in finance

*Type*	*Hours*	*Description*
Workload	Full time hours per semester
Lecture	36	lectures and in-class programming
Independent Study	72	readings and review of lectures
Assignment Completion	79.5	review for in-class test and submission of assignment reports
Total Workload: 187.5

Type	Description	% of total	Assessment Date
Assessment Breakdown
Assignment	Take home assignments	60%	As required
In Class Test	In-class test	40%	As required

Reassessment Requirement Type
Resit arrangements are explained by the following categories; RC1: A resit is available for both^* components of the module. RC2: No resit is available for a 100% coursework module. RC3: No resit is available for the coursework component where there is a coursework and summative examination element. ^* ‘Both’ is used in the context of the module having a coursework/summative examination split; where the module is 100% coursework, there will also be a resit of the assessment

Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Empirical characteristics of asset returns
autocorrelation, skew, kurtosis, time aggregation, volatility clustering, long memory, leverage, trading volume.

Volatility
nonparametric measurement, GARCH-type models, forecasting, news impact curve, stochastic volatility, option implied volatility.

Ultra high frequency data
market microstructure, stylized facts, bid-ask bounce, irregularly spaced data, realized variance, jumps.

Statistics of extremes
extreme value theory, generalized extreme value distribution, threshold exceedance, generalized Pareto distribution.

Indicative Reading List

Books:

Ruey Tsay: 0, Analysis of Financial Time Series, 3rd,
Stephen Taylor: 0, Asset Price Dynamics, Volatility, and Prediction,
Alexander McNeil and Rudiger Frey and Paul Embrechts: 0, Quantitative Risk Management, revised,

Articles:
None

Other Resources

None

Module for new MSc in Finance as approved by Programme Board 26th March 2014. Submitting final document for T&L to Jonathan 28th March 2014.