Financial Econometrics II (Ekonometria Finansowa II)

Script

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

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

Readings

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 (Block1codes.zip)

Data

comDdata.csv; CPI.csv; BQforUK.csv

Block 2. Forecasting the risk of a portfolio

Readings

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 (Block2codes.zip)

Data

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

Readings

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

Berkowitz.xlsx
exercise1.xlsx
data4logit.csv
logit_excel_example.xlsm
macrovariables.xlsx
ratings1.csv

Data and R codes toghether

credit_risk.zip

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)
Grade

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