INSTITUTE OF APPLIED MATHEMATICS
Last Updated:
21/07/2017 - 12:25

IAM526 - Time Series Applied To Finance

Credit: 3(3-0); ECTS: 8.0
Instructor(s): Consent of IAM
Prerequisites: Consent of Instructor(s)

Course Catalogue Description

This course introduces time series methodology emphasizing the data analytic aspects related to financial applications. Topics that will be discussed are as follows: Univariate linear stochastic models: ARMA and ARIMA models building and forecasting using these models. Univariate non-linear stochastic models: Stochastic variance models, ARCH processes and other non-linear univariate models. Topics in the multivariate modeling of financial time series. Applications of these techniques to finance such as time series modeling of equity returns, trading day effects and volatility estimations will be discussed.

Course Objectives

The objective of this course is to initiate students to basic time series models.

Course Learning Outcomes

Student who completes this course successfully
  • will have solved a reasonable number of exercises on classical time series models
  • find research texts (books / articles) using time series models more accessible
  • may get involved in applied research making use of basic time series models
  • will have a reasonable background to study more advanced texts and models

Tentative (Weekly) Outline

This course introduces time series methodology emphasizing the data analytic aspects related to financial applications. Topics that will be discussed are as follows: Univariate linear stochastic models: ARMA and ARIMA models building and forecasting using these models. Univariate non-linear stochastic models: Stochastic variance models, ARCH processes and other non-linear univariate models. Topics in the multivariate modeling of financial time series. Applications of these techniques to finance such as time series modeling of equity returns, trading day effects and volatility estimations will be discussed.

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