Here you can check the status of
the SYRTO project at
Saturday 26 September at 19 pm

Management Structure

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:

• planning and controlling of project activities
• providing overall financial management
• interacting with the EC
• periodical project reports
• day-by-day interaction of the group
• monitoring the working progress
• efficient dissemination of project information to the public and to the target group

Data Center

We collect data in order to:

monitor markets, financial institutions and the economy;
evaluate the severity of the risks impact, both considering individual and systemic risks.

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:

1. Sovereigns
2. Bank and other Financial Intermediaries
3. Corporates

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:

1. Sovereigns – BFIs
2. Sovereigns – Corporate Sectors
3. BFIs – Corporate Sectors

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:

1. System of multiple equations
2. Network Modeling
3. Sparse Graphs and other data-mining techniques

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:

• 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 Risks

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:

• Sovereign Risks
• Bank Risks
• Corporate Risks
• Market Risks
• Credit Risks
• Funding and Liquidity Risks
• Policy Uncertainty
• Interlinkages
• Composite measures
• Monetary and Policy Intervention Perception

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:

• Rating, specifying the membership risk category and corresponding risk value;
• Risk Anomalies, i.e. the risk indicators which appear as excessively risky;
• Risk Assessment, namely the sensitivity towards systemic risk;
• Risk Impacts, quantifying the potential risk severity of specific risk dimensions.

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:

1. governance structures
2. monetary and fiscal systems interactions
3. micro-/macro-prudential responsibilities

Monetary and Policy Intervention Perceptions

Using data from EC (Eurobarometer qualitative surveys) we plan to inspect the common perception European citizens have relative to

1. Monetary Integration
2. Policy Interventions

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:

1. Monetary Integration Satisfaction
2. Policy Intervention Satisfaction

Meetings, Conferences, Scientific Networking

1. Website