data center for systemic risk - michele costola. july, 2 2014
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Data Center for systemic risk - Michele Costola SYRTO Code Workshop Syrto Workshop on Systemic Risk Policy ISSUES Bundesbank-ECB-ESRB Head Office of Deustche Bundesbank, Guest House Frankfurt am Main - July, 2 2014TRANSCRIPT
SYRTO: Data
management
SYstemic Risk TOmography:
Signals, Measurements, Transmission Channels, and Policy Interventions
Michele Costola Ca’ Foscari University of Venice SYRTO Code Workshop Workshop on Systemic Risk Policy Issues for SYRTO July, 2 2014 - Frankfurt (Bundesbank-ECB-ESRB)
SYRTO - Data Management
Data Management
The aim is to structure the data framework in three hierarchical levels,
1 the first level includes “raw” financial and economic data,
2 the second level is constituted by systemic risk measures estimatedon the basis of the first level data,
3 the third level is represented by early warning indicators.
Currently, SYRTO is working on the first and second level,
ETL process (Extraction, transformation and loading),
Coding and testing systemic risk measures on “working” databases.
Building blocks
Level 1
The first level of raw data contains information on single institutions andrelevant macroeconomic variables for contagion and systemic riskanalysis.
The institutions considered are the constituents of the STOXXEurope 600 index.
Data includes prices at a daily frequency and balance sheets data ata lower frequency (quarterly).
Macroeconomic variable.
Economic indicators such as Industry, Employment, Consumersurvey, Prices and National accounts.
Level 1
This set of data is a result of merging information from different sources,
Market and Accounting Data
Price data on the constituents of the STOXX Europe 600 index arefrom Thomson Reuters Datastream R©.Balance sheets data (Total Assets, Total Liabilities, etc.) are fromThomson Reuters Worldscope R©.
Bond
Credit default swap and Corporate bonds for the constituents of theSTOXX Europe 600 from Bloomberg R©.
Macroeconomic Data
Source: Eurostata, OECD.
Level 2
The second level data represents different systemic risk measuresconsidered at micro-level (single institution) and macro-level (financialsystem):
Micro - Single Financial Institution
Standard Systemic risk measuresNew Systemic risk measures
Macro Systemic risk Measures
Standard Macro Systemic risk measuresNew Macro systemic risk measures
Aggregation/Disaggregation (from Micro to Macro and viceversa).
Level 2 - Single Financial Institution
The single financial institution systemic risk measures represent theSystemic risk at a micro level.The measures describe the single institution’s contribution to thesystemic risk.
Standard Systemic risk Measures
Equity side (CoVar, MES, SES, SRISK, Granger Causality),Bond side (CoRisk, Distressed Insurance Premium).
New Systemic risk Measures
Markov switching models,Betas from factor models.
Technical Implementation
⇒ The measures are evaluated on a rolling-window basis (1 or 2 year fordaily frequency and 3 year for monthly frequency).⇒ Measure evaluation has been implemented in MATLAB and R withparallel computing (e.g., GPU computing) is used in order to reduce thecomputing time.
Level 2 - Macro Systemic Measures
The Macro systemic risk measures refer to the whole financial system(Macro-Level),
Standard Systemic Measures
Dynamic Granger Causality Index,Principal Component Analysis.
New Systemic Measures
Multivariate Rank reflection symmetry,Graphical models,Markov switching models,Copula models (Vine Copula),Factor models.
Level 2 - Aggregation/Disaggregation
This block can be viewed as a two-way channel between Single-Financialinstitution and the Financial System.
Single Institutions → Financial System (Aggregation), MacroSystemic Risk measures obtained from aggregation ofsingle-institution systemic risk measures,
Quantile/entropy measures (i.e cross-sectional MES, ∆Covar),Composite Indices (equally weighted, credit weighted),Panel regressions.
Single Institutions ← Financial System (Disaggregation),
Graphical Models,Network analysis.
Level 2 - Macroeconomic Systemic risk measures
Macroeconomic Systemic risk measures are obtained from economicindicators at a lower frequency,
Financial Condition indices through Principal Component Analysis,
Other possible measures: Costly Asset-Price Boom/Bust Cycles,Property and Equity Price and Credit-Gap Indicators.
These Systemic risk measures could be in the right but also on the leftside equation as target variables for early warning indicators.
Level 3 - Early Warning and Nowcasting
The purpose of this level is to realize Early Warning and NowCastingindicators,
Micro - Single Financial Institution,
Macro Systemic Risk.
Mapping Micro and Macro, threshold indicators from micro tomacro dimension.
Level 3 - Target Variables
At the moment, the variables collected to be used as target in the earlywarning system are,
Crisis indicators used in Reinhart and Rogoff (2011), Laeven andValencia (2008, 2012), Babecky et al. (2012).
Financial stress indexes used in Hollo et al.(2012), Kliesen etal.(2012).
Industrial production index used in Engle and Brownlees (2012).
Open Questions
Are these the “right” target variables?
Should we consider different variables?
What should be the time horizon?
All suggestions are welcome!
Working Databases
Different databases have been created with the purpose to comparesystemic risk measures proposed in the literature and test new systemicrisk measures.
US database, based on the data used by Acharya et al. (2010) forMES and SES.It contains 101 financial firms with market capitalization more than$5bill (end 2007).
Constituents of the financial Industry from Eurozone (8000 - ICBDatastream R©),
EU database, the database is the one used by Engle, Jondeau andRockinger (2012) and it contains the large financial institutions inEurope with a market capitalization of at least e1 bill (at end 2011)and a price series that started before January 2000.
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.