Quantitive methods in Financial Management 2600-MSFRdz1MIZF
1) Characteristics of financial time series (stock market indicators as a specific type of financial time series, rate of return - its characteristics and properties).
2) Adaptive forecasting methods for financial time series (naïve methods, moving averages, ex-post errors)
3) Exponential smoothing models (Brown's model, Holt's model, Winter’s model - choice of parameters in models)
4) Using regression models to estimate forecast of values in financial time series (fitting an appropriate analytical form of model, ex-ante errors)
5) Time series decomposition (seasonality indicators in additive and multiplicative approach using binary variables)
6) The concept of a stochastic process. Stationary and non-stationary economic time series (types of stationarity, autocorrelation functions, non-stationarity - test methods: DF test, ADF, Hasza DF, KPSS, Philips - Peron test with structural changes),
7) Selected econometric time series models (random walk process, random walk with drift, random walk with drift and trend, autoregressive process, autoregressive moving average process, autoregressive integrated moving average process).
8) Forecasting based on autoregressive models (estimation and verification of AR, MA, ARMA, ARIMA models).
9) Testing the long-run relationship between selected financial time series and spurious regression.
10) Analysis of volatility in financial time series: GARCH family models (testing the ARCH effect, modifications of the GARCH model)
Course coordinators
Type of course
Mode
Learning outcomes
At the end of the course the student will be able to:
K_W01
knows and understands the research methodology and the terminology in the discipline of Management and Quality Sciences and in the complementary disciplines (Economics and Finance, Legal Sciences), in particular in the field of Financial Management and Accounting.
K_U01
use the theory of the discipline of management and quality sciences and complementary sciences (economics and finance, law) to identify, diagnose and solve problems related to financial decisions in an organisation and the management of financial institutions, using an appropriate selection of sources and adapting existing or developing new methods.
K_U03
analyse, diagnose and report on complex and non-standard problems related to financial management in organisations, accounting, management of financial institutions and strategies of financial institutions, both independently and in teams, and to present them communicatively, also in English, using information and communication technology tools.
K_U06
possesses the ability to self-educate, to improve acquired skills and to support others in doing so.
Assessment criteria
Lectures: T - Final examination,
Classes: pass/fail
Bibliography
Compulsory literature:
1. Mills T.C.: The econometric Modeling of Financial Time Series. Cambridge University Press. Cambridge 2004
2. Brooks C: Introductory Econometrics for Finance. Second Edition, Cambridge University Press. Cambridge, 2008
3. Witkowska D.,Matuszewska A.,Kompa K.: Wprowadzenie do ekonometrii dynamicznej i finansowej. Wydawnictwo SGGW. Warszawa 2008
4. Borkowski B, Dudek H., Szczesny W.: Ekonometria. Wybrane zagadnienia, PWN. Warszawa 2017
5. Lipiec-Zajchowska M. (red.), Wspomaganie Procesów Decyzyjnych, tom 2, C.H. Beck, Warszawa 2003
Recommended literature:
6. Osińska M: Ekonometria finansowa, PWE, Warszawa 2006
7. Box G.E.P., Jenkins G.M.: Analiza szeregów czasowych. Prognozowanie i sterowanie. PWN, Warszawa 1983
8. Maddala G.S.: Ekonometria. PWN. Warszawa 2006
9. Clemens M.P., D.F. Hendry: Forcasting economic time series. Cambridge University Press , Cambridge 2004