Chaos and Finance
ataozk@yahoo.com
Content
Objective
The course aims to develop students’ conceptual understanding of time series, chaos, risk and uncertainty, behavioural economics, and financial markets, and to examine the relationships among these concepts through modelling methods.
It focuses on modelling and testing stochastic processes in economic and financial markets and relating these processes to economic agents’ decision-making within the framework of behavioural economics.
Linear stochastic processes are analysed using Stata 10.0, while chaotic processes are examined using R. The course also covers estimation and forecasting methods.
The course schedule is available at the following link: Course Schedule.
Course Content
Analysis and critical assessment of the Efficient Market Hypothesis.
Risk, uncertainty, and time.
Information, Bayesian decision-making, and rationality.
Applications of behavioural economics.
The concept of equilibrium.
Time series analysis:
Linear modelling of stochastic processes, with applications using Stata 10.0.
Nonlinear modelling, with applications using R.
Chaotic processes.
Application of time series methods to financial variables in markets with high and low trading volumes, including equity, foreign exchange, and bond markets.
Course Learning Outcomes
Upon successful completion of the course, students will be able to:
Explain the relationship between behavioural economics and finance.
Analyse the effects of decision-making processes on markets.
Model stochastic processes.
Use Stata 10.0 and EViews to model stochastic processes.
Explain phase spaces and nonlinear processes.
Explain the concept of chaos and test for chaotic dynamics in financial processes.
Use R to model and test nonlinear processes.
Teaching and Learning Methods
Theory and Practice
The course will draw on contemporary examples of central bank practices worldwide, monetary and fiscal policies, and current developments in financial markets.
Developments in global financial markets, particularly equity markets, will also be used to illustrate the application of time series analysis methods.
References
In addition to the studies of 4 scientists who received the award in the fields of Nobel Economics and Physics, the following sources will be followed.
Johansen, S. (1991) Estimation and hypothesis testing of cointegration vectors in gaussian vector autoregressive models. Econometrica, 59, p 1151-1181
Johansen, S ., Juselius, K. (1991) Testing structural hypotheses in a multivariate cointegration analysis of the PPP and the UIP for UK. Journal of Econometrics, 53, p 211-244
Weekly Contents
| Week | Weekly Contents |
|---|---|
| 1 | Criticism of dynamical economic models in terms of system theory |
| 2 | Efficient market hypothesis and numerical criticism |
| 3 | Introduction to time series analysis and modeling and linear time series |
| 4 | Non-linear time series |
| 5 | A methodological approach to chaos theory |
| 6 | Takens theorem and Recurrence graphs |
| 7 | Phase space restructuring and analysis of European countries public debt interest rates, |
| 8 | Sensitive dependence of debt interest rates on preliminary policies and Lyapunov coefficient, |
| 9 | BISE - 100 and FTSE-100 indexes maximum Lyapunov coefficient calculation, |
| 10 | Chaotic behavior of certain world stock markets |
| 11 | Agent behaviors that can cause chaos in trade and markets |
| 12 | Agent behaviors that can cause chaos in trade and markets |
| 13 | Financial crises and chaos |
| 14 |
| Week | Weekly Contents |
|---|---|
| 9 | BISE - 100 and FTSE-100 indexes maximum Lyapunov coefficient calculation, |
| 10 | Chaotic behavior of certain world stock markets |
| 13 | Financial crises and chaos |
Assessment System
| Activities | Number | Contribution |
|---|---|---|
| Contribution of in-term studies to overall grade | 13 | 60 |
| Contribution of final exam to overall grade | 5 | 40 |
| Total | 18 | 100 |
| Activities | Number | Contribution |
|---|---|---|
| Assignments | 9 | 20 |
| Presentation | 2 | 20 |
| Midterm Examinations (including preparation) | 2 | 20 |
| Project | 0 | 0 |
| Laboratory | 3 | 0 |
| Other Applications | 0 | 0 |
| Quiz | 0 | 0 |
| Term Paper/ Project | 2 | 40 |
| Portfolio Study | 0 | 0 |
| Reports | 0 | 0 |
| Learning Diary | 0 | 0 |
| Thesis/ Project | 0 | 0 |
| Seminar | 0 | 0 |
| Other | 0 | 0 |
| Make-up | 0 | 0 |
| Total | 18 | 100 |
ECTS
| Activities | Number | Period | Total Workload |
|---|---|---|---|
| Class Hours | 14 | 3 | 42 |
| Working Hours out of Class | 0 | 0 | 0 |
| Assignments | 14 | 1 | 14 |
| Presentation | 1 | 20 | 20 |
| Midterm Examinations (including preparation) | 2 | 10 | 20 |
| Project | 2 | 10 | 20 |
| Laboratory | 0 | 0 | 0 |
| Other Applications | 0 | 0 | 0 |
| Final Examinations (including preparation) | 1 | 30 | 30 |
| Quiz | 0 | 0 | 0 |
| Term Paper/ Project | 0 | 0 | 0 |
| Portfolio Study | 0 | 0 | 0 |
| Reports | 0 | 0 | 0 |
| Learning Diary | 0 | 0 | 0 |
| Thesis/ Project | 0 | 0 | 0 |
| Seminar | 0 | 0 | 0 |
| Other | 0 | 0 | 0 |
| Make-up | 0 | 0 | 0 |
| Yıl Sonu | 0 | 0 | 0 |
| Hazırlık Yıl Sonu | 0 | 0 | 0 |
| Hazırlık Bütünleme | 0 | 0 | 0 |
| Total Workload | 146 | ||
| Total Workload / 25 | 5.84 | ||
| Credits ECTS | 6 | ||