Our management structure is based on a model allowing full exploitation of the innovation potential of the project, short communication lines and straightforward decision making. Our main tasks are the following:
We collect data in order to:
monitor markets, financial institutions and the economy;
Data Management Infrastructure
Data integration, comparing financial and economic data across multiple institutions and/or data-sources.
Data quality, taking into account the missing value problems.
Metadata management, to get a common platform with reliable data, which often derive from data-mergers (different databases) and data-adjustments on balance sheets items.
Identification of the fundamental risk sources
We focus on each “slice” of the financial system making clear the fundamental risk sources for:
The objective is to understand the risks of the system S-BFIs-C from a theoretical and empirical perspectives.
Exploration of the two-way causal relations
We explore the bivariate risk connections among the system S-BFIs-C:
List of methodologies to capture the two-way linkages (i) PC Regression analysis; (ii) Canonical Correlations and Latent Class Analysis (LCA); (iii) VAR models; (iv) Frailty models and dynamic latent component analysis; (v) Student-t full-factor multivariate GARCH models; (vi) Factor models with time-varying and stochastic coefficients.
Linkages and vulnerability of the financial system
We will implement a battery of systemic risk measurement:
• Dynamic Conditional Correlations
• Copula functions and copula-based models
• Principal Component Analysis
• Regime-switching models
• Frailty models
• Dynamic latent component analysis
• Granger causality tests
• Shrinkage-based regressions
• Latent Class Analysis
• Contingent Claim Analysis (CCA)
• Dynamic Factor Models of Tail Real and Financial Risks
The connection between financial-economic linkages and shocks
We focus on the joint determination of risks, in order to detect the relevant financial and economic linkages as a channel for propagation of shocks. The following approaches will be used to accomplish this task:
These approaches may reveal the vulnerable parts of the systems to give adverse scenarios arising due to their close interconnections with sectors and countries that are directly exposed to unforeseen events.
Step 1: Approaches to identify risks and vulnerabilities
We will realize an EWS for S-BFI-C, providing a comprehensive risk analysis covering countries and sectors and aggregating the individual risk dimensions by using the following methodologies:
Step 2: Risk Dashboard – Jointly with ECB (MaRS)
Our aim is to realize a risk dashboard in order to realize a risk mapping and identify potential vulnerabilities within the Eurozone:
Step 3: Risk Thresholds and Warning Signals
Our aim is to realize a web platform through which verifying in real time the risk profile by web-based data imputation.
The system should periodically update the entire dataset and model estimates planned in the project.
Risk Reports articulated in 4 sections will be available for individual Sovereigns, BFIs and Corporations:
A normative superstructure regarding policy, monetary, and regulatory implication of systemic risks
The objective is to realize a SYRTO Code collecting a series of recommendations and prescriptions on:
Monetary and Policy Intervention Perceptions
Using data from EC (Eurobarometer qualitative surveys) we plan to inspect the common perception European citizens have relative to
Our aim is to identify potential areas of improvement of the macroprudential policy making process.
Through recent techniques used to measure the job satisfaction pertaining to Rasch Rating Scale Model, we will introduce two measures:
Meetings, Conferences, Scientific Networking
We realize a website in order to raise awareness of the project activities and to disseminate its results www.syrtoproject.eu
2. Conferences and meetings
The Consortium as a whole aims at sharing ideas and results on research activity with academics and institutions involved in the topic of systemic risk through international conferences and meetings
3. Scientific Networking
Scientific networking with academic institutions to contribute to the knowledge of systemic risks and its impacts on financial stability in the European Union