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Module Specifications..

Current Academic Year 2023 - 2024

Please note that this information is subject to change.

Module Title Financial Econometrics
Module Code EF5162
School DCUBS
Module Co-ordinatorSemester 1: Hiroyuki Kawakatsu
Semester 2: Hiroyuki Kawakatsu
Autumn: Hiroyuki Kawakatsu
Module TeachersHiroyuki Kawakatsu
NFQ level 9 Credit Rating 7.5
Pre-requisite None
Co-requisite None
Compatibles None
Incompatibles None
Resubmit take home assignments

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

Workload Full-time hours per semester
Type Hours Description
Lecture36lectures and in-class programming
Independent Study72readings and review of lectures
Assignment Completion79.5review for in-class test and submission of assignment reports
Total Workload: 187.5

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.

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.

Assessment Breakdown
Continuous Assessment100% Examination Weight0%
Course Work Breakdown
TypeDescription% of totalAssessment Date
AssignmentTake home assignments60%As required
In Class TestIn-class test40%As required
Reassessment Requirement Type
Resit arrangements are explained by the following categories;
1 = A resit is available for all components of the module
2 = No resit is available for 100% continuous assessment module
3 = No resit is available for the continuous assessment component
This module is category 1
Indicative Reading List

  • 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,
Other Resources

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.
Programme or List of Programmes
MFCMMSc in Finance

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