Uniwersytet Warszawski, Wydział Nauk Ekonomicznych - Centralny System Uwierzytelniania
Strona główna

Modelling and Forecasting Returns and Volatility on Capital Markets & Algorithmic Investment Strategies

Informacje ogólne

Kod przedmiotu: 2400-PP3SL234
Kod Erasmus / ISCED: 14.3 Kod klasyfikacyjny przedmiotu składa się z trzech do pięciu cyfr, przy czym trzy pierwsze oznaczają klasyfikację dziedziny wg. Listy kodów dziedzin obowiązującej w programie Socrates/Erasmus, czwarta (dotąd na ogół 0) – ewentualne uszczegółowienie informacji o dyscyplinie, piąta – stopień zaawansowania przedmiotu ustalony na podstawie roku studiów, dla którego przedmiot jest przeznaczony. / (0311) Ekonomia Kod ISCED - Międzynarodowa Standardowa Klasyfikacja Kształcenia (International Standard Classification of Education) została opracowana przez UNESCO.
Nazwa przedmiotu: Modelling and Forecasting Returns and Volatility on Capital Markets & Algorithmic Investment Strategies
Jednostka: Wydział Nauk Ekonomicznych
Grupy: Anglojęzyczna oferta zajęć WNE UW
Seminaria licencjackie dla III r. st.lic. ( Finanse i Inwestycje Międzynarodowe)
Punkty ECTS i inne: 3.50 Podstawowe informacje o zasadach przyporządkowania punktów ECTS:
  • roczny wymiar godzinowy nakładu pracy studenta konieczny do osiągnięcia zakładanych efektów uczenia się dla danego etapu studiów wynosi 1500-1800 h, co odpowiada 60 ECTS;
  • tygodniowy wymiar godzinowy nakładu pracy studenta wynosi 45 h;
  • 1 punkt ECTS odpowiada 25-30 godzinom pracy studenta potrzebnej do osiągnięcia zakładanych efektów uczenia się;
  • tygodniowy nakład pracy studenta konieczny do osiągnięcia zakładanych efektów uczenia się pozwala uzyskać 1,5 ECTS;
  • nakład pracy potrzebny do zaliczenia przedmiotu, któremu przypisano 3 ECTS, stanowi 10% semestralnego obciążenia studenta.

zobacz reguły punktacji
Język prowadzenia: angielski
Rodzaj przedmiotu:

seminaria licencjackie

Założenia (opisowo):

(tylko po angielsku) The registration limit for the master thesis seminar has been deliberately set at 0, although it is higher than it. Registration for the seminar is possible only after prior contact with the seminar coordinator, preferably via e-mail: rslepaczuk@wne.uw.edu.pl

Skrócony opis:

The main aim of this seminar is to present the latest financial research published in top journals in the field and to help students to choose the most adequate theme of their master thesis, taking into account not only their abilities but their future career paths and job interests. Students will learn the latest volatility and returns forecasting models and advanced investment derivatives based strategies which incorporate unconventional distributions of returns in the process of managing of financial assets. Additionally, they will learn how to calibrate models and test them on empirical data (financial time series), with daily and intra-daily frequency. Moreover, the topics of identifying, quantifying, modeling and managing risk according to the latest investigation in financial literature will be discussed. The assessment will be based on timely preparation of highly marked master thesis dissertation.

Pełny opis:

In the course of this seminar the fundamental factors determining the process of capital markets returns fluctuation will be presented with special focus on equities, currencies, bonds, commodities and derivatives based on above mentioned. Moreover, we will focus on risk associated with all kinds of capital market investments. We will discuss the latest approaches to volatility modelling (realised volatility calculated on HF data), as the crucial risk measure on capital markets, which is incorporated in almost all risk management models, capital asset pricing models, option valuation models, etc.

The main theoretical concepts discussed in the course of this seminar are:

1. Modelling and forecasting of the financial markets

2. Volatility time series modelling

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 modelling

8. Modelling and managing the risk of financial institutions

9. Efficient market hypothesis in the information sense

10. Anomalies of the capital market

11. Behavioural finance

The aim of this seminar is to present methods of financial instruments pricing (including derivatives), with special focus on the practical aspects. The wide range of modern investment strategies, implemented in the process of managing of financial assets, which are developed based on different motives of speculation, arbitrage or hedging, will be presented. Specific issues, discussed during seminar are based on real financial market cases, which will provide the participants with the knowledge on market turbulences and financial crisis which occur more frequently on the global financial markets.

Assessment:

Timely high mark preparation for the master thesis dissertation.

Literatura:

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.

Czekaj J., Woś M., Żarnowski J., 2001, Efektywność giełdowego rynku akcji w Polsce, Wydawnictwo Naukowe PWN, Warszawa.

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.

Haugen Robert A., 1999, Nowa nauka o finansach. Przeciw efektywności rynku, WIG-Press, Warszawa.

Hull J., Options, Futures and Other Derivatives, Prentice Hall, New Jersey 2006.

Jajuga K., 2000, Metody ekonometryczne i statystyczne w analizie rynku kapitałowego, Wydawnictwo Akademii Ekonomicznej we Wrocławiu, Wrocław.

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.

Murphy J.J., 1998, Międzyrynkowa analiza techniczna, WIG-Press, Warszawa.

Murphy J.J., 1999, Analiza techniczna rynków finansowych, WIG–Press, Warszawa.

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.

Szyszka A., 2003, Efektywność giełdy papierów wartościowych w Warszawie na tle rynków dojrzałych, Wydawnictwo Akademii Ekonomicznej, Poznań.

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.

Efekty uczenia się:

Upon the course completion (lecture, discussions) a student:

- is able to analyze, model and forecast financial markets,

- is able to recognize the practical implications of theoretical theories in case of the specific financial problem,

- is able to provide an explanation for the use of specific tool and model in the process of pricing derivatives, designing investment strategies, risk management, etc.

The aim of this seminar is not only to help students in writing very good master thesis dissertation but presenting all the practical applications for financial theories and models used in the process of its preparing.

Metody i kryteria oceniania:

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 master 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 master thesis dissertation. The assessment of each semester is based on providing the following parts of the dissertation before the end of each semester:

Winter Semester:

Analysis and presentation of at least two research papers of similar research area to the thesis subject.

Formulation of the main hypothesis and other research questions.

Formulation the subject and the detailed plan of the thesis (together with the description of each thesis parts).

Collecting and describing the empirical data used in verification of the research hypothesis.

Class presence is mandatory (maximum three non justified absences).

Spring 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).

It is advisable to pass all the courses focusing on tools, mathematical methods and introducing students to the theme of modeling and forecasting of financial markets what in results will help them to write very good master thesis dissertation, e.g: Econometrics, Finance I and II, Financial Markets, Time Series Analysis, Modeling Financial Markets.

Zajęcia w cyklu "Semestr zimowy 2022/23"

Okres: 2022-10-01 - 2023-01-29
Wybrany podział planu:


powiększ
zobacz plan zajęć
Typ zajęć:
Seminarium licencjackie, 30 godzin więcej informacji
Koordynatorzy: Robert Ślepaczuk
Prowadzący grup: Robert Ślepaczuk
Lista studentów: (nie masz dostępu)
Zaliczenie: Przedmiot - Zaliczenie
Seminarium licencjackie - Zaliczenie
Uwagi:

Limit zapisów na seminarium celowo został ustalony na poziomie 0, chociaż jest od niego większy. Zapisy na seminarium są możliwe jedynie po uprzednim kontakcie z prowadzącym seminarium, najlepiej za pośrednictwem maila: rslepaczuk@wne.uw.edu.pl

Zajęcia w cyklu "Semestr letni 2022/23" (jeszcze nie rozpoczęty)

Okres: 2023-02-20 - 2023-06-18
Wybrany podział planu:


powiększ
zobacz plan zajęć
Typ zajęć:
Seminarium licencjackie, 30 godzin więcej informacji
Koordynatorzy: Robert Ślepaczuk
Prowadzący grup: Robert Ślepaczuk
Lista studentów: (nie masz dostępu)
Zaliczenie: Przedmiot - Zaliczenie
Seminarium licencjackie - Zaliczenie
Opisy przedmiotów w USOS i USOSweb są chronione prawem autorskim.
Właścicielem praw autorskich jest Uniwersytet Warszawski, Wydział Nauk Ekonomicznych.
ul. Długa 44/50
00-241 Warszawa
tel: +48 22 55 49 126 https://www.wne.uw.edu.pl/
kontakt deklaracja dostępności USOSweb 6.8.1.0-1 (2023-01-18)