SYRTO/LABEX ReFi Closing Conference

Paris, February 2016

Joint work with: István Barra (a)

Francisco Blasques (a)

Siem Jan Koopman (a,b) Rutger Jan Lange (a) Michiel van de Leur (a) Rutger Lit (a) Federico Nucera (c) Julia Schaumburg (a) Bernd Schwaab (d,*) Arjen Siegmann (a) Xin Zhang (e,*)

a)Vrije Universiteit Amsterdam and Tinbergen Institute b)CREATES c) Luiss, Rome d) ECB, these are not the opinions of the ECB e) Riksbank, these are not the opinions of the Riksbank

André Lucas  

Systemic Risk Indicators

SYstemic  Risk  TOmography:  Signals,  Measurements,  Transmission  Channels,  and  Policy  Interven@ons  

(Gerlach,  2009:  policy  note  to  European  Parliament)  

Financial  surveillance  before  the  current  crisis  erupted  suggested  that  problems  were  forming  but  the  indica@ons  were  too  imprecise  to  permit  a  policy  response.    

Work  is  currently  being  undertaken  to  improve  the  measurement,  monitoring  and  management  of  systemic  risk.    

That  requires  it  to  be  defined,  which  is  unproblema5c,  and  opera5onalized,  which  is  not.    

While  promising  methods  to  measure  risk  exist,  the  data  demands  are  so  pronounced  that  sta5s5cal  risk  monitoring  will  remain  an  imprecise  science  for  years  to  come.  

Where  are  we  now  ?  

Types  of  systemic  risk  

•  Level  of  systemic  risk  –  is  systemic  risk  currently  high  or  low:  ``objec@ve’’  policy  trigger  

•  Dynamics  of  systemic  risk  –  is  systemic  risk  building  up  or  not,  growing  misalignments,  bubbles,  growing  linkages  

•  Distribu@on  of  systemic  risk  – finding  biggest  systemic  risk  contributors,  targeNed  monitoring  

Types  of  measurements  

•  Market  prices  –  forward  looking  (stock  markets,  yields,  CDS),  …  – but  also  possibly  misaligned  risk  cycles  (Minksy)  

– signals  typically  coincidental  

ESRB  Risk  Dashboard  (2016)  Lucas,  Schwaab,  Zhang  (2014,  SYRTO/JBES):    Condi@onal  euro  area  sovereign  default  risk  Lucas,  Schwaab,  Zhang  (2016,  SYRTO/JAppEctr):  Measuring  Credit  Risk  in  a  Large  Banking       System:  Econometric  Modeling  and  Empirics  

Lange,  Siegmann  (2016,  SYRTO):  Es@ma@ng  Sovereign  Join  Default  Probabili@es  from  Bond  Yields  

Types  of  measurements  

•  Fundamentals  versus  experience,  or  versus  prices  – create  a  benchmark  (fundamental)  and  see  whether  data  are  aligned  with  the  fundamentals  

–  typically  more  leading  

Creal,  Schwaab,  Koopman,  Lucas  (2014,  SYRTO/REStat):  Observa@on  Driven  Mixed-­‐     Measurement  Dynamic  Factor  Models  with  an  Applica@on  to  Credit  Risk  Koopman,  Lucas,  Schwaab  (2014,  SYRTO/IJF):  Nowcas@ng  and  forecas@ng  global  financial       sector  stress  and  credit  market  disloca@on  

Creal,  Schwaab,  Koopman,  Lucas  (2014,  SYRTO/REStat):  Observa@on  Driven  Mixed-­‐     Measurement  Dynamic  Factor  Models  with  an  Applica@on  to  Credit  Risk  Koopman,  Lucas,  Schwaab  (2014,  SYRTO/IJF):  Nowcas@ng  and  forecas@ng  global  financial       sector  stress  and  credit  market  disloca@on  

Schwaab,  Koopman,  Lucas  (2016,  SYRTO/JAppEctr):  Global  Credit  Risk:  World,       Country  and  Industry  Factors  

ESRB  Risk  Dashboard  (2016)  Schwaab,  Koopman,  Lucas  (2016,  SYRTO/JAppEctr):  Global  Credit  Risk:  World,       Country  and  Industry  Factors  Creal,  Schwaab,  Koopman,  Lucas  (2014,  SYRTO/REStat):  Observa@on  Driven  Mixed-­‐     Measurement  Dynamic  Factor  Models  with  an  Applica@on  to  Credit  Risk  Koopman,  Lucas,  Schwaab  (2014,  SYRTO/IJF):  Nowcas@ng  and  forecas@ng  global  financial       sector  stress  and  credit  market  disloca@on  

Barra,  Lucas  (2016,  SYRTO):  Unobserved  components  in  corporate  defaults  and  bond  prices  

Nucera,  Schwaab,  Koopman,  Lucas  (2016,  SYRTO/JEmpFin):  The  Informa@on  in  Systemic  Risk  Rankings  

Koopman,  Lit,  Lucas  (2016,  SYRTO):  A  decomposi@on  of  economic  and  financial  @me  series       into  business  and  financial  cycles  

Types  of  measurements  

•  Network  structures  – create  summary  measures  of  the  network  structure  –  leading  or  coincidental?  – value-­‐added  to  macro  summaries?  

van  de  Leur,  Lucas  (2016,  SYRTO):  Network,  Market,  and  Book-­‐Based  Systemic  Risk  Rankings.  

van  de  Leur,  Lucas  (2016,  SYRTO):  Network,  Market,  and  Book-­‐Based  Systemic  Risk  Rankings.  

van  de  Leur,  Lucas  (2016,  SYRTO):  Network,  Market,  and  Book-­‐Based  Systemic  Risk  Rankings.  

Types  of  measurements  

•  Text  parsing  – count  posi@ve  and  nega@ve  news  – news  on  linkages,  even  if  indirect  ?  

Garmaev,  Rus@ge,  Lammers,  Borovkova  (2016,  VU):  Systemic  Risk:  A  News  Sen@ment  based  Approach  

SRisk  

SensR  

Summary  and  conclusions  

•  Price  based  informa@on  largely  coincidental  •  Misalignments  more  promising  in  lead  @mes,  though  also  

more  data/methodology  intensive  •  Network  data  appear  to  add  new  informa@on:  which?  

And  how  useful?  

•  Research  direc@ons  –  beNer  understanding  of  the  genesis  of  risks  and  imbalances;  

find  appropriate  proxies  –  exploi@ng  new  network  data  (benchmarking  will  be  hard)  –  exploi@ng  text  or  other  big  data  sources  – measuring  and  exploi@ng  misalignments  

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.