A Systematic Approach to Systemic Risk

Transcription

1 A Systematic Aroach to Systemic Risk Antoaneta Serguieva and David Bholat Advance Analytics Division, Bank o England 8th Conerence o the Irving Fisher Committee on Central Bank Statistics: Imlications o the New Financial Landscae 8 th Setember 2016 We would like to thank Paul Robinson, Oliver Burrows, Yaacov Mutnikas, Jamie Coen, Cian O'Neill, Murray Stehen and Veselin Karadotchev, or their comments on the drats o the aer and or coordinating access to data. This work is artly suorted by grant ISS1415\7\65 rom the Royal Academy o Engineering. Any views exressed are solely those o the authors and so cannot be taken to reresent those o the Bank o England or to state Bank o England olicy.

2 Motivation emergence o structure as actor in economic analysis inancialization at macro, meso, and micro levels o economy (Van der Zwan, 2014) roagation o inluence and the challenges to causal analysis need or a comrehensive exloration o systemic risk (Schwarcz, 2011) system-o-systems model with macro, meso, and micro sub-systems (Haldane, 2015) ; (Serguieva, 2016; Serguieva & Bholat, 2016, 2017) single-layer network vs multilex at macro level (De Domenico et al., 2013); (Buldyrev et al., 2010); (Serguieva, 2013b, 2016; Serguieva & Bholat, 2016, 2017) extending the scoe o analysis beyond the banking system: systemic risk is not contained within the banking system (Serguieva, 2016; Serguieva & Bholat, 2016, 2017) requirement or new aroaches to modelling interconnectedness network links vs tensors balancing behavioural tendencies o nodes/institutions (Serguieva, 2016) 2

3 Motivation evaluation o multichannel contagion dynamics and systemic imact multichannel vs single-channel contagion systemic imact in a single market vs systemic imact within multile interconnected markets (Markose, 2012); (Serguieva, 2016; Serguieva & Bholat, 2016, 2017) 3

4 Conclusions we ormulate and emirically evaluate the minimum-cost strategy or multile-market stabilisation: the strategy is caable o containing contagion and involves all UK-incororated deosit takers and signiicant investment irms within the strongly connected comonent o the structure o inter-institutional imacts the stabilisation strategy involves careully estimated and minimally invasive rebalancing o how the system coes with the emerged structure o exosures this work ormulates and emirically evaluates structural measures o systemic-risk and systemic-resilience or the banking system as a whole, as well as relative systemic-risk indexes or each institution and the absolute contribution o each institution to the overall systemic risk systemic-stability conditions o banks interactions in multile interconnected markets are evaluated as a structural characteristic and does not deend on the trigger or tye o crisis the multile-market (multilex) systemic-risk measures and indexes are a more realistic basis or regulation the ormulation o the tensor-multilex acilitates the simulation o multichannel contagion dynamics and the design o stabilisation strategies 4

5 Conclusions dierent institutions have the higher systemic imacts in multile markets vs single markets, and as institutions realistically interact in multile markets then stabilisation strategies should be based on institutions' multile-market imact dierent institutions have the higher systemic imacts under EAD and NAC scenarios, and as both scenarios are lausible though in dierent arts o the system at dierent stages o the contagion rocess, then the rebalancing o imact should be based on both scenarios evaluating emirically multile-market centralities o the wider system o inter-institutional exosures - involving banks, non-bank inancial institutions, non-inancial cororates, governments, central banks, and suranational organisations allowed us to identiy concentration o vulnerabilities within the wider economic system tensors are more realistic models o comlex structures, as they cature not only magnitudes o interlinkages but also tensions within the structure due to behavioural tendencies o nodes with otential to change the magnitudes, and this can be used to extend the scoe o stress-testing scenarios 5

6 ormulation and emirical simulation o: stability conditions the dynamics o multi-channel vs single-channel contagion multile-market stabilisation rocesses vs single-market rocesses dierent institutions have the higher systemic imacts in multile interconnected markets vs single markets 6

7 ,, derivatives market (D): three-dimensional decomosition o size o imact magnitudes, where imacting institutions are in market D securities-inancing market (SFT): three-dimensional decomosition o size o imact magnitudes, where imacting institutions are in market SFT,, ixed-income market (FI): three-dimensional decomosition o size o imact magnitudes, where exosed institutions are in market FI Multilex: Four-dimensional decomosition o inter- and intra-link magnitudes o imact S 8th IFC Conerence on, BIS Set 2016 It catures the imact magnitudes among institutions within each inancial market and between any air o markets. 7

8 multi-channel systemic imact, through the single-channel systemic imact, through ixed-income, SFT and derivatives markets the derivatives-market number o reorting banks number o reorting banks number o banks _ number o banks in the strongly connected (18 overlaing (18 overlaing in the strongly connected subtensor banks) banks) subtensor _ stability (insolvency) condition _ or _ 0 (no stabilisation ste imlemented) (a stabilisation ste imlemented) _ _ th IFC Conerence on, BIS Set 2016 stability (insolvency) condition _ or 0 (no stabilisation ste imlemented) no stabilisation ste required 8

9 ormulation and emirical simulation o stability conditions, and the dynamics o multi-channel vs single-channel contagion dierent institutions have the higher systemic imacts in multile interconnected markets vs single markets Institution i E F G rank at _ 0, (multile-market contagion dynamics) rank at 0, (single-market contagion dynamics) _ at _ 0 (multile-market systemic-risk index) _ at 0 (single-market systemic-risk index) (not articiating in the multilex strongly-connected comonent) % 0.33% 0% 0.28% 4.05% 0.23% 8th IFC Conerence on, BIS Set

10 ormulation and emirical simulation o single-market stabilisation rocesses or 0 1 and 1, ; rebalanced rebalanced i=1 j q q ; 0, 0, ; a A connected connected connected 10

11 ormulation and emirical simulation o stabilisation rocesses in multile interconnected markets or 0 _ 1; 1, _ ; 1, l 3 ; rebalanced _ rebalanced _ i _ l t _ j _ z y qyz z,y q _ l _ _ 0,, l _,, l,, l ; _ min 8th IFC Conerence on, BIS Set 2016 _ connected _ 11

12 ormulation and emirical evaluation o absolute vs relative systemic-risk measures relative systemic-risk indexes _ or _ 0 or _ absolute systemic risk measure and 1 _ 0, 0 _ 0 12

13 ormulation and emirical simulation o scenarios in the derivatives market going-concern scenario at-deault scenario number o reorting banks number o reorting banks number o banks in the strongly connected subtensor number o banks in the strongly connected subtensor stability condition or 0 (no regulatory surcharges imlemented) stability condition or 0 (no regulatory surcharges imlemented) 13

14 ormulation and emirical simulation o scenarios in the derivatives market institution i A B C D rank at 0, (going-concern (not articiating in strongly-connected 7 systemic dynamics) subtensor) rank at 0, (at-deault systemic dynamics) at % 3.01% 0% 4.00% at % 5.09% 4.03% 0.81% systemic stability and quality can be achieved trough targeting dierent institutions to a dierent extent under the two scenarios: one surcharge: ( systemic-resilience measures, 8th IFC Conerence on, BIS Set 2016 ) 14

15 theoretical ormulation, domain interretation, and emirical evaluation o the tensor-multilex and tensormonolexes, and the corresonding multile-market vs single-market centralities o institutions in the wider system incororating banks, non-bank inancial institutions, non-inancial cororations, central banks, governments, and suranational organisation (over 1,500 institutions) 15

16 8th IFC Conerence on, BIS Set 2016 emirical: wider system rior to introducing the multilex structure 16

17 exosures due to the ixed-income market exosures due to the securities-inancing market exosures due to the derivatives market emirical: wider economic system as multilex structure 8th IFC Conerence on, BIS Set

18 ,, derivatives market (D): a three-dimensional decomosition o size o exosures, where the exosed institutions are in market D securities-inancing market (SFT): a three-dimensional decomosition o size o exosures, where the exosed institutions are in market SFT,, ixed-income market (FI): a three-dimensional decomosition o size o exosures, where the exosed institutions are in market FI Multilex: Four-dimensional decomosition o inter- and intra-market magnitudes o exosure W 8th IFC Conerence on, BIS Set 2016 It catures the magnitudes o exosures among institutions within each inancial market and between any air o markets. 18

19 emirical evaluation or the wider economic system 8th IFC Conerence on, BIS Set

20 emirical evaluation or the wider economic system 8th IFC Conerence on, BIS Set

21 theoretical ormulation and domain interretation o the tensor-multilex model a link between two nodes may be reresented through a binary number, a scalar, a vector, a tensor o rank 2, or a tensor o rank 4 - each o these mathematical constructs, in that order, rogressively catures and communicates more comlex and realistic inormation the structure is not just the magnitudes o the exosures themselves but also the tension within the system due to the behaviour o institutions with otential to change exosures behavioural tendencies o institutions are art o the tensorial structure through the basis and dual-basis vectors 21

22 ormulation and domain interretation o the tensormultilex model or the structure o inter-institutional exosures within the wider economic system (1,500 institutions o dierent tye) l l l Γ,, l, l l or l 0 i l l 0 i l l 22

23 emirical evaluation or the wider economic system multilex centrality institution average rank weighted rank tensor rank (Katz vector) (Katz vector) (Katz tensor) XLI XLII XLIII XLIV XLV Katz-tensor centrality is mathematical extension o the original deinition the aggregation is erormed within the calculation and does not require any heuristic choice, as it is already accounting or the whole interconnected structure. 23

24 8th IFC Conerence on, BIS Set 2016 ormulation and emirical evaluation o inluence-tensor among inancial stability actors in the orthonormal reerence rame o their rincial comonents (the selected actors are o regulatory signiicance or detecting early warning signals o system-wide vulnerabilities) actors as vectors in the reerence rame o actors rincial comonents tensor roduct as a link (inluence) between two actors m c m c c m 1, 1,,1 k c c m k m k c v q v k c c m k m k q c v q v m q m q m k q m q q v q v q c F F ,, 1 1,,,1,,,,,1,1,

25 Conclusions (slides 4-5) Questions 25