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Financial Econometrics (ETS-810/E-776)
- Instructor Name: Dr. Saud Ahmed Khan
- Credit Hours: 03
- E-mail: [email protected]
- Office Hours: 08:00 AM - 04::00PM (Monday through Friday)
Prerequisites For this Course:
- Econometric Methods
Text Book(s):
- Ruey S. Tsay (2010), Analysis of Financial Time Series 3rd John Willey & Sons.
- Brooks, Chris (2008), Introductory Econometrics for Finance, 2nd Ed., Cambridge University Press.
- Rachev, S.T., Mittnik, S., Fabozzi, F.J., Focardi, S.M., Teo, J. (2007), Financial Econometrics: From Basics to Advanced Modeling Techniques, John Willey & Sons.
Reference Book(s):
- Gourieroux, C. and J. Jasiak (2001), Financial Econometrics, Princeton University Press.
- Mills, T. C. (1999), The Econometric Modelling Of Financial Time series, 2nd Ed., Cambridge University Press.
- Taylor,S. J. (2005), Asset Price Dynamics, Volatility, and Prediction, Princeton University Press.
- Verbeek, M. (2004), A Guide to Modern Econometrics, Wiley & Sons.
Course Description
Financial Econometrics (FETS) is the application of Econometric tools to analyze Financial Time Series; these series possess distinct structure, usually subject to ARCH effect. FETS provides a set of empirical tools to analyze historical financial data, model underlying economic mechanisms, and predict future trends (Risk and Return). This course covers both univariate and multivariate data analysis. Univariate analyses provide conditional mean and conditional spread equations (risk and return). Univariate tools estimate volatility but unable to provide co-volatilities; the Multivariate regression tools estimate co-volatilities, further enable researchers to explore information transmission. Applications of these techniques to evaluate the performance of firms’ trading strategies and hedge fund managers are also discussed. Furthermore, time-series models are introduced to model and forecast both time-varying aggregate stock returns and volatility.
Course Objectives
- To develop an understanding of univariate and multivariate financial time-series methods, including estimation and statistical model evaluation.
- To become familiar with methods for modelling long-run relationships in finance.
- To become familiar with methods for modelling volatility and correlation, such as ARCH and GARCH.
- To be able to forecast return and volatility.
- To apply the concepts learnt using appropriate computer programs and simulation methods.
- To be able to trace information transmission and propose Optimal Hedge Ratio.
Learning Outcomes
By the end of this course, students will be able to: understand the significance of financial markets’ development and integration, hedging technique and estimation of optimal hedge ratios, analysis of risk and return trade off, evaluation of dynamic VaR, Modeling exchange rate and its volatility, food price volatility, currency devaluation, models of interest rate, inflation and inflation uncertainty.
Case Studies: Inflation, Exchange rates, CPI, SPI, Energy Firms, Oil Prices, Cryptocurrencies, Equity Markets
Software:
- OxMetrics
- R – studio
Some Readings:
- Volatility Modelling and Dynamic Linkages between Pakistan and Leading Foreign Stock Markets: A Multivariate GARCH Analysis”, PDR 58:3, 2019 pp. 265-282. https://file.pide.org.pk/pdfpdr/2019/265-282.pdf
- “Modeling Exchange Rate Volatility by Macroeconomic Fundamental in Pakistan”, International Econometric Review. Volume 6. Issue 2. Pp.58-76. ISSN (online) 1308-8815. September 2014. https://www.econstor.eu/bitstream/10419/238811/1/ier-v06-i2-p058-076.pdf
- “Inflation and Inflation Uncertainty Nexus: Empirical Evidence from Pakistan” International Journal of Economics & Financial Issues, No. 3 Vol.2, pp: 348-356, 2012. https://www.econjournals.com/index.php/ijefi/article/view/149
- https://www.jstor.org/stable/2029468?seq=1
- https://www.cambridge.org/core/journals/econometric-theory/article/abs/financial-calculus-an-introduction-to-derivative-pricing/E40790662AD399712C7990190093ECEC
- https://academic.oup.com/jrsssa/article/167/1/188/7084227
- https://www.researchgate.net/publication/391723248_Fractional_calculus_and_its_application_in_financial_mathematics
- “Multi-modality in the Likelihood Function of GARCH Model”. Review of Pacific Basin Financial Markets and Policies Vol. 23, No. 3 (2020) 2050018 (23 pages) °c World Scientific Publishing Co. and Center for Pacific Basin Business, Economics and Finance Research. https://doi.org/10.1142/S0219091520500186
Lecture Plan
| Session | Topic | Readings | Activities
Quizzes/Assignments/Term papers |
| Week-1 | Stylized Properties of Financial Time Series at level, Intro to OxMetrics | https://www.doornik.com/doc/PcGive/PcGive_vol1.pdf | Hands on/Lab |
| Stylized properties of Financial return Series | Ppt/TB-1 | Hands on/Lab | |
| Week-2 | Continued… | How Stable are the Stable Coins | Hands on/Lab |
| Tests for Normal moments | “When Genius Failed” | Assignment#1 | |
| Week-3 | Fallacies about modeling gauges t-stat and R2 | Ppt/RB-1 | Hands on/Lab |
| Continued… | Ppt/RB-1 | Hands on/Lab | |
| Week-4 | Autoregressive Conditional Heteroscedasticity | Ppt/TB-2 | Hands on/Lab |
| Continued… | Ppt/TB-2 | Hands on/Lab | |
| Week-5 | Univariate GARCH type models | Ppt/TB-1 | Hands on/Lab |
| Continued… | Students’ Presentation | Assignment#2 | |
| Week-6 | Asymmetric GARCH type models | Ppt/TB-1 | Hands on/Lab |
| Continued… | Ppt/TB-1 | Hands on/Lab | |
| Week-7 | Risk premium | Students’ Presentation | Hands on/Lab |
| SPI VS CPI inflation and inflation uncertainty hypotheses | “Evaluating the Friedman-Ball and Cukierman-Meltzer Hypothesis: A GARCH application on Pakistan and Neighboring Economies” | Hands on/Lab | |
| Week-8 | Continued… | “Analyzing the Uncertainty of Sensitive Price Indicator: Evaluating the Friedman-Ball and Cukierman-Meltzer hypothesis in Pakistan Economy” | Quiz#1 |
| MID TERM EXAM | |||
| Week-9 | Spillover Effect | “Co-movement Analysis: An Application of ARDL-GARCH Model” | Hands on/Lab |
| Continued … | “Tracing Dynamic Linkages and Volatility Spillover Effect between Pakistani and Foreign Stock Markets” | Hands on/Lab | |
| Week-10 | Continued…. | Students’ presentation | Assignmnet#3 |
| The ARMA-APARCH-M-t model | “HEDGING: AN ISLAMIC APPROACH” | Hands on/Lab | |
| Module-2 Multivariate Analysis | |||
| Week-11 | Continue… | Hedging the Currency Devaluation | Hands on/Lab |
| BEKK models | TB | Hands on/Lab | |
| Week-12 | Scalar BEKK and DBEKK | TB | Quiz#2 |
| Continued… | “HEDGING: AN ISLAMIC APPROACH” | Hands on/Lab | |
| Week-13 | Continued… | Students’ presentation | Hands on/Lab |
| Hedging | “Hedging the Currency Devaluation” | Hands on/Lab | |
| Week-14 | Continued… | “Hedging by Diversification: An analysis of stocks, Bonds, and Gold: Evidence from Pakistani Markets”. | Lab |
| Continued… | Students’ presentation | Lab | |
| Week-15 | Intro to CAPM | Khan Academy | Online |
| Estimating VaR by simulation | “Forecasting Value at Risk for Energy Firms in Pakistan”. | Quiz#3 | |
| Week-16 | Continued… | Students’ presentation | Lab |
| Final Exam | |||
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