Comment on:Risk Dynamics in the Eurozone: A New Factor Model forSovereign CDS and Equity Returnsby Dellaportas, Meligkotsidou, Savona, Vrontos. Andre Lucas. Amsterda, June, 25 2015. Spillover Dynamics for Systemic Risk Measurement Using Spatial Financial Time Series Models. Andre Lucas. Amsterdam - June, 25 2015. European Financial Management Association 2015 Annual Meetings.

1. Comment on:
Risk Dynamics in the Eurozone: A New Factor Model for
Sovereign CDS and Equity Returns
by Dellaportas, Meligkotsidou, Savona, Vrontos
SYstemic Risk TOmography:
Signals, Measurements, Transmission Channels, and
Policy Interventions
Andre Lucas
VU University Amsterdam and Tinbergen
Institute
EFMA Nyenrode
June 2015

2. Contributions
 Modeling sovereign, financial, and non-financial
sector simultaneously
 Model with a lot of flexibility
 Observable and latent common factors
 Time varying loadings, contingent on observable and latent
variables
 Bayesian estimation of the model; potentially get
a better impression of what we can/cannot get
from the data

3. Comments (1)
 Why this sample: 2007-2009?
 The sample contains the financial crisis, but nothing of the for EU
at least as important sovereign debt crisis
 The model

4. Comments (2)
 Why not complicate the model further?
 Why not simplify the model first?
 What is the value added of all these complications?
 What is there value added of each of the components for model fit?
t
t

5. Comments (3)
 The model works well in simulations, but is not easy to interpret
empirically, e.g. financial sector betas
 What about the choice of the number of factors, the
distribution, which parameters to vary over time, and
the origins of this

6. Comments (4)
 Empirical model
 Choice of variables better motivated, plus better described
(returns, changes, levels?)
 Remove causal statements, as the model is reduced form
 Economic rationale, e.g.: “An increase of Industrial production in
Greece and Spain leads to increased CDS returns.”
 What is the empirical value-added of each of the components?
Build up contributions and comparisons in marginal predictive
likelihood?
 Convergence issues in samplers?

7. This project has received funding from the European Union’s
Seventh Framework Programme for research, technological
development and demonstration under grant agreement no° 320270
www.syrtoproject.eu
This document reflects only the author’s views.
The European Union is not liable for any use that may be made of the information contained therein.