Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics

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    Financial Investment Planning

    A tantárgy neve magyarul / Name of the subject in Hungarian: Pénzügyi befektetések tervezése

    Last updated: 2013. november 10.

    Budapest University of Technology and Economics
    Faculty of Electrical Engineering and Informatics

    Business Information Systems MSc.

    Specialization: Financial informatics

    Course ID Semester Assessment Credit Tantárgyfélév
    GT35M404   3/0/0/v 4  
    3. Course coordinator and department Dr. Ormos Mihály, Pénzügyek Tanszék
    4. Instructors

    László Györfi DSc

    Professor

    Department. of Computer. Science and Information Theory

    András Telcs DSc

    Assoc. Prof.

    Department. of Computer. Science and Information Theory

    5. Required knowledge

    Recommended: Mathematical statistics, Finance

    6. Pre-requisites
    Kötelező:
    Training.code=("5N-MGAIN")

    A fenti forma a Neptun sajátja, ezen technikai okokból nem változtattunk.

    A kötelező előtanulmányi rendek grafikus formában itt láthatók.

    Ajánlott:
    -
    7. Objectives, learning outcomes and obtained knowledge

    Students meet with the basic financial instruments and the risk involved by their usage. Acquire knowledge in their handling, pricing and combination in a portfolio.  Learn on modern theory of option pricing following the CRR method.   Lectures deliver the basics and advanced models of time series with particular emphasis on financial data.

    8. Synopsis
    1. Basic financial instruments.
    2. Markovitz's portfolio theory.
    3. Utility theory, optimal portfolio, the CAPM model.
    4. The options.
    5. Types of options and their trade.
    6. Option pricing.
    7. Discrete martingales.
    8. The binomial model.
    9. The Cox-Ross-Rubinstein formula.
    10. Black-Scholes formula.
    11. The fundaments of the analysis of stock price time series, stochastic processes.
    12. Deterministic models, smoothing.
    13. The Box-Jenkins model family.
    9. Method of instruction

    Lectures

    10. Assessment

    a. Active involvement during lectures (mini lecture presentations). One test. Condition of the course signature is the successful test.

    b. Oral exam.

    c. Pre exam subject of tutor's agreement.

    11. Recaps

    One retake of the test is possible during the recap weak.

    12. Consultations upon personal inquiry
    13. References, textbooks and resources

    1.      Száz János: Tőzsdei opciók vételre és eladásra, Tanszék Kft, 1999.

    2.      R. S. Tsay: Analysis of Financial Time Series, Wiley, 2nd edition, 2005.

    3.      L. Györfi, M. Kohler, A. Krzyzak, H. Walk: A Distribution-Free Theory of Nonparametric Regression, Springer-Verlag, 2002.

    4.      L. Györfi, G. Ottucsák: Empirical log-optimal portfolio selections: a survey, http://www.szit.bme.hu/~oti/portfolio/articles/tgyorfi.pdf 2007

    14. Required learning hours and assignment
    Kontakt óra42
    Félévközi készülés órákra18
    Felkészülés zárthelyire18
    Házi feladat elkészítése
    Kijelölt írásos tananyag elsajátítása
    Vizsgafelkészülés42
    Összesen120
    15. Syllabus prepared by

    László Györfi DSc

    Professor

    Department. of Computer. Science and Information Theory