PhDr. František Čech

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Position: Ph.D. Candidate
Field of interest: Financial Econometrics; Time-Series Models; Portfolio Choice; International Financial Markets
Membership: Finance and Capital Markets, PhD Candidates

Contact

Office: 503
Email: frantisek [DOT] cech [AT] fsv [DOT] cuni [DOT] cz
Phone: +420 776 535 106
Personal web pages: https://cz.linkedin.com/in/frantisek-cech-70a10538
Available: by appointment

More information

Assistant

JEM116 - Applied Econometrics

PhD study

Tutor: doc. PhDr. Jozef Baruník Ph.D.

Studying from: 2013
PhDr examination: 10/2013
Final exam: 01/2017
Dissertation Proposal defence: 2018
Dissertation defence: 2018

Current work:
On the modelling and forecasting multivariate realized volatility: Generalized Heterogeneous Autoregressive (GHAR) model

Measurement of Common Risk Factors: A Panel Quantile Regression Model for Returns

Dissertation topic:
Multivariate Volatility Modeling

Disertation abstract:
GHAR:
Recent multivariate extensions of popular heterogeneous autoregressive model (HAR) for realized volatility leave substantial information unmodelled in residuals. We propose to employ a system of seemingly unrelated regressions to model and forecast realized covariance matrix to capture this information. We find that the newly proposed generalized heterogeneous autoregressive (GHAR) model outperforms competing approaches in terms of economic gains providing better mean-variance trade-off while in terms of statistical precision GHAR is not substantially dominated by any other model. Additionally, our results provide a comprehensive comparison of the performance when realized covariance, sub-sampled realized covariance and noise-robust multivariate realized kernel estimators, are used. We study the contribution of the estimators across different sampling frequencies, and we show that the multivariate realized kernel and sub-sampled realized covariance estimators deliver further gains compared to realized covariance estimated on 5 minutes frequency. In order to show the economic and statistical gains of the GHAR model, portfolio of various sizes is used.


Measurement of Common Risk Factors: A Panel Quantile Regression Model for Returns:
This paper investigates how to measure common market risk factors using newly proposed Panel Quantile Regression Model for Returns. By exploring the fact that volatility crosses all quantiles of the return distribution and using penalized fixed effects estimator we are able to control for otherwise unobserved heterogeneity among financial assets. Direct benefits of the proposed approach are revealed in the portfolio Value-at-Risk forecasting application, where our modeling strategy performs significantly better than several benchmark models according to both statistical and economic comparison. In particular Panel Quantile Regression Model for Returns consistently outperforms all the competitors in the 5\% and 10\% quantiles. Sound statistical performance translates directly into economic gains which is demonstrated in the Global Minimum Value-at-Risk Portfolio and Markowitz-like comparison. Overall results of our research are important for correct identification of the sources of systemic risk, and are particularly attractive for high dimensional applications.

Optional courses:
WS 2016/2017: JED412 - Nonlinear Dynamic Economic Systems: Theory and Applications
WS 2016/2017: JED414 - Quantitative Methods I
SS 2016/2017: JED413 - Nonlinear Dynamic Economic Systems: Theory and Applications
SS 2016/2017: JED415 - Quantitative Methods II

WS 2015/2016: JED414 - Quantitative Methods I
SS 2015/2016: JED415 - Quantitative Methods II

WS 2014/2015: JED414 - Quantitative Methods I
SS 2014/2015: JED415 - Quantitative Methods II

WS 2013/2014: JED414 - Quantitative Methods I
SS 2013/2014: JED415 - Quantitative Methods II

CV

Organisation Memberships

DYME – Dynamic Models in Economics (Excellence Project of GAČR)

Education

07-08/2016: Visiting scholar at the University of California, Berkeley, Department of Economics
2013+: Ph.D., IES FSV UK
2013: PhDr., IES FSV UK
2010 - 2013: Mgr., IES FSV UK
2012: Erasmus program - Humboldt University in Berlin
2007 - 2010: Bc., IES FSV UK

Job history

2016+: GEMCLIME project administrator
2015+: ECOCEP project administrator
2014 - 2015: RWE Energie s.r.o , Analyst - Sales Portfolio Management
2013 - 2014: RWE Česká republika a.s., Trainee - Retail Portfolio Management

Extra activities

Teaching:
WS 2016/2017: JEM 035 - Financial Markets Instruments I
SS 2016/2017: JEM 116 - Applied Econometrics

WS 2015/2016: JEM 035 - Financial Markets Instruments I
SS 2015/2016: JEM 036 - Financial Markets Instruments II
SS 2015/2016: JEM 116 - Applied Econometrics

WS 2014/2015: JEM 035 - Financial Markets Instruments I
SS 2014/2015: JEM 036 - Financial Markets Instruments II
SS 2014/2015: JEM 116 - Applied Econometrics

WS 2013/2014: JEM 035 - Financial Markets Instruments I
SS 2013/2014: JEM 036 - Financial Markets Instruments II
SS 2013/2014: JEM 116 - Applied Econometrics

Referee:
Prague Economic Papers (5), Czech Journal of Economics and Finance (1)

Awards and prizes

2013: National bank of Slovakia Governor Award (2nd place) - award for outstanding dissertation or master thesis in economics
2013: M.A. with distinction from the Dean of the Faculty of Social Sciences for an excellent state-final examination performance and for an extraordinarily good masters diploma thesis.

Topics for supervision

Term papers

Applied Financial Econometrics - multivariate volatility modelling
Applied Financial Econometrics - volatility modelling

Bachelor theses

Applied Financial Econometrics - multivariate volatility modelling
Applied Financial Econometrics - volatility modelling

Master theses

Applied Financial Econometrics - multivariate volatility modelling
Applied Financial Econometrics - volatility modelling

Currently supervising 3 master thesis:
Šimon Procházka: Application of the Realized Semivariances within Realized GARCH framework
Zhang Haiying: The empirical research of cross listed stocks: The case of AH shares
Pavel Stirba: The Effects of Monetary Policy on Real Estate Market: a VAR Analysis

Supervised Master Theses

all/awarded: 3/0
Awarded:

Downloadable

Evaluation_2015
ISP
ISP_update_2014
ISP_update_2015

Partners

ČSOB
Deloitte
McKinsey & Company

Sponsors

CRIF