Financial Econometrics II (Ekonometria Finansowa II)


Micha³ Rubaszek, 2021. Materials for the course Financial Econometrics II, Warsaw (DOWNLOAD)

Block 1. Forecasting and simulating the economy with ARMA and VAR models


Michal Rubaszek (2012). Modelowanie Polskiej Gospodarki z Pakietem R, Oficyna Wydawnicza SGH. Chapters 1-5 (link)
Appied Econometrics with R, Kleiber Ch. i Zeileis A. (link)
Tsay R. S. (2002). Analysis of Financial Time Series, Wiley.
Lütkepohl H., Krätzig M. (2004). Applied Time Series Econometrics, Cambridge University Press.
Nelson Ch.R, 1972. The Prediction Performance of the FRB-MIT-PENN Model of the U.S. Economy, American Economic Review 62(5), 902-17 (link)
Nelson Ch.R., Plosser Ch., 1982. Trends and random walks in macroeconmic time series : Some evidence and implications, Journal of Monetary Economics 10(2), 139-162 (link)
Smets F., Peersman G., 2001. The monetary transmission mechanism in the Euro area: more evidence from VAR analysis, ECB Working Paper Series 091 (link)
Blanchard O., Quah D., 1989. The Dynamic Effects of Aggregate Demand and Supply Disturbances, American Economic Review 79(4): 655-673 (link lub link)

R codes

Topic 1. Introduction to R. (Block1T1.R)
Topic 2. ARMA models. (Block1T2.R)
Topic 3. VAR models. (Block1T3.R)
Topic 4. Forecast evaluation. (Block1T4.R); (Block1adds.R)
Functions (Block1Functions.R)
Zipped codes (


comDdata.csv; CPI.csv; BQforUK.csv

Block 2. Forecasting the risk of a portfolio


Michal Rubaszek (2012). Modelowanie Polskiej Gospodarki z Pakietem R, Oficyna Wydawnicza SGH. Chapter 6 (link)
Tsay R. S. (2002). Analysis of Financial Time Series, Wiley.
Cont R., 2001. Empirical properties of asset returns: stylized facts and statistical issues, Quantitative Finance 1, 223-236 (link)
Bauwens L., Laurent S., Rombouts J., 2006. Multivariate GARCH models: a survey, Journal of Applied Econometrics 21, 79-109 (link)
Ghalanos A., 2018, Introduction to the rugarch package (link)
Nelsen R., 2006. An Introduction to Copulas, Springer (link)

R codes

Topic 5. GARCH models. (Block2T5.R)
Topic 6. MGARCH models. (Block2T6.R)
Topic 7. Copulas. (Block2T7.R)
Topic 8. Backtesting. (Block2T8.R)
Functions (Block2Functions.R)
Downloading data for WIG20 stocks / PLN rates (Block2data.R)
Zipped codes (


wig20.csv; wig20.Rdata; PLN.csv; PLN.Rdata;

Blok 3. Credit risk

Materials / presentations

Topic 1: CredRisk1.pdf
Topic 2: CredRisk2.pdf
Housework: HouseworkCredRisk.pdf


Bolder, D.J. (2018). Credit-Risk Modelling, Springer (link)

R codes

Creating database: 00_database_generation.R
Topic 1. 01_credit_scores_logit.R and 01_winsorizing.R
Topic 2. 02_bootstrapping.R; 02_stressmodel.R; 02_transition_matrix.R and 02_mapping2ratings.R



Data and R codes toghether

Evaluation / grades: 2020 Spring course

Points to be gathered:

  1. Two presentations (max 24 pkt)
  2. Active participation in classes (max 3 pkt)
  3. Online test (max 10 pkt)

do 15: 2 (ndst)
od 15: 3 (dst)
od 19: 3+ (dst+)
od 23: 4 (db)
od 27: 4+ (db+)
od 31: 5 (bdb)