FINANCIAL TIME SERIES ANALYSIS
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Type of course
Elective
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Level of course
Advanced Undergraduate
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Year of study
2005-2006
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Semester
spring
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Number of credits allocated
ECTS 6
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Name of lecturer
Dr Raphael N. Markellos
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Objective of the course (expected learning outcomes
and competences to be acquired)
The theory and practice of
finance in recent years is increasingly based on time series analysis. The
objective of this course is to present some important time series methods and
tools along with their application to specific financial problems ranging from
financial analysis, asset pricing, trading, forecasting, etc. Special attention
will be given in the implementation of the methods taught using specialized
software packages. Starting from the celebrated univariate ARMA framework the
course will introduce the notions of nonstationarity, nonlinearity, stochastic
volatility, long-run equilibrium relationships, long-memory and multivariate
time series models. At the end of the course the students will be able to
describe and identify the characteristics of financial time series such as
stocks, exchange rates, interest rates, commodity prices, etc. They will also
be able to evaluate and select the most appropriate model using a variety of
testing procedures.
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Prerequisites
Basic Econometrics and Statistics
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Course contents
► Foundations of Financial Econometrics
► ARMA Modelling
► Nonstationarity
► Long-Memory
► Volatility Modelling
► Nonlinear Models
► Cointegration Analysis
► Vector ARMA
1.
Recommended reading
& Mills, T.C. (1999) The Econometric Modelling of Financial Time
Series, Cambridge University Press
& Hamilton, J.D. (1994) Time Series Analysis, Princeton
University Press
& Brooks, C. (2002) Introductory Econometrics for Finance,
Cambridge University Press
& Markellos, R.N. Lecture Notes
Lectures with Study Groups
Written Exams and Coursework
English