Download Quantitative Finance I

Quantitative Finance I
Syllabus
WS 2010/2011
Principal literature:
1. Campbell, Lo and MacKinlay (CLM): The Econometrics of Financial Markets,
Princeton, 1997.
2. Tsay R.S.: Analysis of Financial Time Series, Wiley, 2002.
4. Barucci E.(BE): Financial Markets Theory,Springer, 2003.
6. Hamilton J.C. (HJ): Time Setries Analysis, Princeton, 1994
7. Evzen Kocenda, Alexander Cerny (2007) Elements of Time Series Econometrics. The
Karolinum Press, UK
8. Walter Enders (2004) .Applied Econometric Time Series, Second Edition
9. Hommes CH (2006) Heterogeneous agent models in economics and finance. In:
Tesfatsion L, Judd KL (eds) Handbook of computational economics, agent-based
computational economics, vol 2. Elsevier Science BV, Amsterdam, pp 1109–1186
Lecture notes and other material used during lectures will also be available at:
http://staff.utia.cas.cz/barunik/
Classification and Organization:
Final Exam: …………………….
40%
Midterm Exam: ………………....
20%
Homeworks and Presentations: ...
40%
+
Extra points for active class participation / extraordinary presentation and
homeworks……………………… max 10%
Course Organization:
Winter Semester, every Tuesday, 15:30 - 18:20
Room 105, IES, Opletalova 26, Prague 1
Lecturers:
Jozef Baruník (JB) [email protected]
Lukáš Vácha (LV) [email protected]
Quantitative Finance I
Syllabus cont.
5.10. (JB+LV)
1. Introductory Lecture
12.10. (JB)
1. Introduction to Financial Time Series (Assets, Prices, Random
Walk, Moving average Models) (CLM, Chapter 2).
Exercise: Simulation of random walk - application on stock market time series.
Homework: Random walk in selected time series..
19.10. (JB)
2. Testing for Random Walk in Asset Prices - Statistical Theory,
Unit Root Tests.* (CLM, Chapter 2).
Exercise: Testing for random walk - application on stock market time series.
Homework: Testing for random walk in selected time series.
* Optional: Overview of Classical Linear Regression
26.10. (LV)
3. Linear Models of Financial Time Series - Moving Average
Models, AR, ARMA, ARIMA. (BC, Chapter 5).
Exercise: Application on real-world data.
Homework: Estimation of MA, AR, ARMA, ARIMA
2.11. (JB+LV)
4. Reading (modeling volatility)
Exercise: Reading
Homework: Reading
9.11. (LV)
5. Introduction to Nonlinearities in Financial Data I
(Modelling volatility and correlation, GARCH models)
Exercise: Application on the real-world data
Homework: GARCH estimation
Quantitative Finance I
Syllabus cont.
16.11 (JB)
6. Introduction to Nonlinearities in Financial Data II
(Threshold models, Parametric Estimation, Neural Networks)
Exercise: Application on the real-world data
Homework: Kernel Regression estimation
23.11. (JB+LV)
7. Reading (high-frequency data)
Exercise: Reading
Homework: Reading
30.11 (JB)
8. High-frequency financial models I
(Realized Volatility)
Exercise: basic properties of high-frequency data series
Homework: Estimation
7.12. (JB)
9. High-frequency financial models II
(Jumps, microstructure noise bias on realized volatility estimation)
Exercise: realized volatility estimation
Homework: realized volatility estimation
14.12. (LV)
10. Heterogeneous Agent Models (HAM) I.
Exercise & Homework: Simulation of basic HAM model.
Additional Reading: Brock WA, Hommes CH (1998) Heterogeneous beliefs and routes to chaos in a simple asset pricing model. J Econ
Dyn Control 22:1235–1274
21.12. (LV)
11. Heterogeneous Agent Models (HAM) II.
Exercise: Simulations.
Homework: Simulation of basic HAM model.
? (JB, LV)
12. Final