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AECO 480/580(9671/9672) Financial
Econometrics
I. Introduction
Zhongwen Liang
Department of Economics
University at Albany, SUNY
January 26, 2018
Textbooks:
- Lim, K.G., Financial Valuation and Econometrics: 2nd Edition, 2nd Revised. World Scientific Publishing Co, 2015.
- Tsay, R.S., An Introduction to Analysis of Financial Data with R. Wiley, 2013.
- Hilpisch, Y., Python for Finance: Analyze Big Financial Data. OReilly Media, 2014.
Reference textbooks:
- Tsay, R.S., Analysis of Financial Time Series, Third Edition. Wiley, 2010.
- Fan, J., Yao, Q., The Elements of Financial Econometrics. Science Press, Beijing, 2015.
- Brandimarte, P., Numerical Methods in Finance and Economics: A MATLAB-Based Introduction. 2nd Edition. Wiley-Interscience, 2006.
- Hilpisch, Y., Listed Volatility and Variance Derivatives: A Python-based Guide (Wiley Finance). Wiley, 2016.
- Hilpisch, Y., Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging (The Wiley Finance Series). Wiley, 2015.
Course Description and Prerequisites:
- Introduction to fundamental financial econometric models with applications to financial asset pricing and valuation, financial investment, financial forecasting and the empirical analyses of financial data.
- Emphasis is on hands-on experience of financial data analysis and applications using R, Python and MATLAB.
- Prerequisites: AECO 320 or equivalence, Calculus.
Objective:
- To help students understand the fundamentals in financial econometrics, which will assistant them in obtaining techniques and experience to solve the real world financial data problems.
Grading:
- Attendance: 10% of the final grade.
- Assignments: 30% of the final grade.
- Midterm: 30% of the final grade.
- Final Project: 30% of the final grade.
Examinations:
- Midterm: Friday, March 9, 2018, in class
- Final Exam: There will be no final exam but a final project.
Course Outline:(subject to changes)
I. Financial Time Series and Their Characteristics
II. Linear Models and CAPM
III. Bond and Term Structure Models
IV. Option Pricing and Diffusion Models
V. Asset Volatility and Volatility Models
VI. Portfolio Choices and Risk Management
VII. High-Frequency Data Analysis
VIII. Multivariate and Factor Models
Resources for R
Introduction: http://cran.r-project.org/doc/manuals/r-release/R-intro.html
Contributed manuals: http://cran.r-project.org/other-docs.html
Reference cards for R: http://cran.r-project.org/doc/contrib/refcard.pdf https://cran.cnr.berkeley.edu/doc/contrib/Short-refcard.pdf
Reference card for time series: http://cran.r-project.org/doc/contrib/Ricci-refcard-ts.pdf
Resources for Python
Web: https://www.python.org/
Beginners Guide: https://wiki.python.org/moin/BeginnersGuide