Investment Strategies with New Classes of Assets 2400-EN3SL301B
The aim of this seminar is not only to help students in writing very good bachelor thesis dissertation but presenting all the practical applications for financial theories and models used in the process of its preparing.
The main theoretical concepts discussed in the course of this seminar are:
1. Modeling and forecasting of the financial markets, in particular with the use of modern machine learning models
2. Volatility time series modeling
3. Volatility estimators calculated on the basis of HF data
4. Volatility indexes based on HF option data, e.g. VIX introduced by CBOE. The methods of their creation and pricing of volatility derivatives
5. Capital asset pricing models and asset management
6. Fundamental and technical analysis; automatic investment strategies
7. Pricing and risk of financial instruments, especially derivatives; option valuation models with special focus on volatility modeling
8. Modeling and managing the risk of financial institutions
9. Efficient market hypothesis in the information sense
10. Anomalies of the capital market
11. Behavioral finance
Type of course
Prerequisites (description)
Course coordinators
Learning outcomes
Upon the course completion (lecture, discussions) students will be able to:
- analyze, model and forecast financial markets,
- recognize the practical implications of theoretical theories in case of the specific financial problem,
- provide an explanation for the use of specific tool and model in the process of pricing derivatives, designing investment strategies, risk management, etc.
Assessment criteria
Conditions of participation:
1. Self-discipline, systematic work during the whole academic year, and willingness to invest a great deal of effort necessary to write a very good bachelor thesis.
2. The knowledge of basic econometric techniques and financial theories and models enabling to plan and write the research verifying main research hypotheses.
The basic condition of passing graduate research seminar is to timely write very good bachelor thesis dissertation. The assessment of each semester is based on providing the following parts of the dissertation before the end of each semester:
1st Semester:
• Analysis and presentation of at least two research papers of similar research area to the thesis subject.
• Formulation the subject and the detailed plan of the thesis (together with the description of each thesis parts).
• Formulation of the main hypothesis and other research questions.
• Discussing and reconciling the final methodology of the empirical study
• Collecting and describing the empirical data used in verification of the research hypothesis.
• Class presence is mandatory (maximum three non justified absences).
2nd Semester:
• Analysis and presentation of at least one research paper of similar research area to the thesis subject.
• Finishing empirical part of the thesis.
• Discussion of results in the empirical part, the preparation of the theoretical part.
• Preparation of the final version of the text and editorial corrections.
• Class presence is mandatory (maximum three non justified absences).
Bibliography
Books:
• Bandy H., 2007, Quantitative Trading Systems, Blue Owl Press.
• Bernstein P.L., 2005, Capital Ideas, Wiley, New Jersey.
• Brooks Ch., 2002, Introductory econometrics for Finance, Cambridge University Press, Cambridge.
• Cuthberston K., Nitzsche D., 2004, Quantitative Financial Economics, Wiley, Chichester.
• Elton J.E., Gruber M.J., 1998, Nowoczesna Teoria Portfelowa,WIG-Press, Warszawa.
• Fabozzi F.J., 2000, Rynki obligacji. Analiza i strategie, WIG-Press, Warszawa.
• Fabozzi F.J., 2004, Fixed Income Analysis, Wiley, New Jersey.
• Gatheral J., 2006, The Volatility Surface, Wiley Finance, New Jersey.
• Haugen Robert A., 1993, Modern Investment Theory, Prentice Hall Inc.
• Hull J., Options, Futures and Other Derivatives, Prentice Hall, New Jersey 2006.
• Javaheri A., 2005, Inside Volatility Arbitrage, Wiley Finance, New Jersey.
• Jorion P., 2007, Value at Risk 3rd edition, McGraw-Hill, New York.
• Lo A.W., MacKinlay A.C., 1999, A Non-Random Walk Down Wall Street, Princeton, NJ, Princeton University Press.
• Merton R.C., Continuous-Time Finance, Revised Edition, Oxford, UK: Basic Blackwell.
• Poon S., Granger C.W.J., 2003, Forecasting volatility in financial markets: A review, Journal of Economic Literature 41, 478-539.
• Sharpe W.F., 1995, Investments, Prentice Hall International, London.
• Tsay R.S., 2005, Analysis of Time Series, Wiley, New Jersey.
• Wlimott P., Paul Wilmott On Quantitative Finance, 2nd Edition, John Wiley & Sons, Chichester 2006.
Papers:
• Andersen T.G., Bollerlev T., 1998, Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts", International Economic Review, 39, No.4, 885-905.
• Andersen T.G., Bollerslev T., Diebold F.X, Ebens H., 2001, The Distribution of Realized Stock Return Volatility, Journal of Financial Economics, 61, 43-76.
• Bachelier L., 1900, Theorie de la Speculation, Gauthier-Villars, Paris, w: P. Cootner, The Random Character of Stock Market Prices, MIT Press, Cambridge, Mass., 17-78.
• Bakshi, G., Cao, Ch., Chen, Z., 1997, Empirical Performance of Alternative Option Pricing Models, Journal of Finance, LII, 5, 2003-2049.
• Bates, D.S., 2003, Empirical option pricing: a retrospection, Journal of Econometrics, 116, 387-404.
• Black F., 1976, Studies of stock market volatility changes, Proceedings of the American Statistical Association, Business and Economic Statistics Section, 177-181.
• Black, F., and Scholes, M., 1973, The pricing of options and corporate liabilities, Journal of Political Economy, 81, 637-659.
• Brock W., Lakonishok J., LeBaron B., 1992, Simple Technical Trading Rules and the Stochastic Properties of Stock Returns, Journal of Finance 47(5), 1731-1764.
• Campbell J.Y., Lo A.W., MacKinley A.C., The Econometrics of Financial Markets, Princeton University Press, New Jersey 1997.
• Cowles A., 1933, Can Stock Market Forecasters Forecast?, Econometrica 1(3), 309-324.
• Derman E., Demeterfi K, Kamal M., Zou J., 1999, More than you ever wanted to know about volatility swaps, Quantitative Strategies Research Notes, Goldman Sachs.
• Fama E.F., 1998, Market Efficiency, Long-Term Returns and Behavioral Finance, Journal of Financial Economics 49, 283-306.
• Gencay R., 1998, The predictability of security returns with simple technical trading rules, Journal of Empirical Finance 5, 347-359.
• Giot P., Laurent S., 2004, Modelling daily Value-at-Risk using realized volatility and ARCH type models, Journal of Empirical Finance, vol. 11(3), 379-398.
• Hull J., White A., 1987, The pricing of options on assets with stochastic volatilities, Journal of Finance 42, 281-300.
• Malkiel B.G., 2003, The Efficient Market Hypothesis and Its Critics, CEPS Working Paper No. 91, Princeton University.
• Martens M., Zein J., 2003, Prediciting Financial Volatility: High-Frequency Time Series Forecasts vis-à-vis Implied Volatility.
• Merton R. C., 1973, Theory of Rational Option Pricing, Bell Journal of Economics and Management Science, 4, 141-183.
• Mixon S., 2009, Option markets and implied volatility: Past versus present, Journal of Financial Economics 94, 171-191.
• Yu W.W., Lui E.C.K., Wang J.W., 2010, The predictive power of the implied volatility of options traded OTC and on exchanges, Journal of Banking & Finance 34, 1-11
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: