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Applications of BoF-PSS2 simulator and
how to use it in agent based models
Workshop on Agent based modeling for banking and finance
Villa Gualino, Torino
10 February 2009
Matti Hellqvist
Oversight of Market Infrastructure division
Financial Markets and Statistics department
Bank of Finland
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 1
Outline
• BoF-PSS2 simulator basics
• Intended applications and examples
• How to use this simulator in agent based models
As usual, the views are those of the speaker and do not
necessarily reflect Bank of Finlands position
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 2
Background of BoF-PSS2
Bank of Finland...
–
–
–
–
National central bank and monetary authority
Member in European System of Central Banks
Long tradition as a research oriented CB
Statutory task to ”participate in maintaining the
reliability and efficiency of the payment system
and overall financial system and participate in
their development”
... Payment system simulator
– BoF-PSS1 was built before Finland joined
European Monetary Union (1.1.1999)
– BoF-PSS2 was released in 2004 (beta 2003)
• Specialised tool for payment system experts
• Easy to use, versatile and modular
• Designed to be shared with others
• Available free of charge for research purposes
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 3
BoF-PSS2 - principles
•
•
Simulations of market infrastructures are often performed with oneoff tailored models or inflexible test environments
BoF-PSS2 in contrast…
– offers a versatile toolbox with most of the common ”building
blocks” needed in a model of a payment system
– has modular design: allows combinations of different blocks
– Is extendable: users have possibility to introduce new modules
– Records various statistics and has ready made reports
– It is designed as an analysis tool
– Is based on widely used free tools – standard interfaces
Laboratory of payment and settlement systems
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 4
From input data to output statistics
by replicating the process logic of real payment system
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 5
What goes in...
• Data
– Transactions, participants, balances, credit or bilateral limits
– i.e. The account structure, bookings and constraints affecting the
settlement process
– Also optional data fields and user defined or meta data
• System definitions
– Type of system: RTGS, continuous netting, deferred netting
– General parameters
– Process logic, which is
• Divided into algorithms classes: Entry, queue release etc.
• Composed by selecting appropriate algorithm for each
needed class.
– Multiple separate and interlinked systems are possible
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 6
What comes out
Output database
•Large number of indicators
recorded during simulation
•Only selected tables are saved
•Has four levels of statistics:
1.General information of executed
simulations
2.Statistics and indicators in the
system level
3.Statsitics and indicators in the
participant/ account level
4.Transaction level
Reports:
•First view summaries
•Time series aggregation tool
•Comparison reports
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 7
Analysis tool aspect
• Data management
– Parallel data sets and projects are possible
– Data files in CSV format and templates for data
– Input or output database can be accessed directly
• Data imports, exports or modifications
• Special queries
– Easy standalone use
• Computational efficiency
– Minimised file i/o compared to real systems
– Simplified process with only the necessary variables
• Based on platform independent and widely used technologies
– Java, MySQL (OEM licence needed)
– Available as PC software for MS operating systems (currently)
• Capability for other analyses from the same data e.g. network
analysis
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 8
User community
•
•
Over 70 granted licences (January 2009) of which 61% in central banks, 24% in
academic institutions, 7% in automated clearing houses (ACH), 3 % in
international organisations, 5% others
Licenced users among others: University of Torino, Banca di Italia, Bank of
England, Banco de Mexico
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 9
Outline
• BoF-PSS2 simulator basics
• Intended applications and examples
• How to use this simulator in agent based models
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 10
Use of BoF-PSS2
• Basic idea:
Model what ever you want related to payment system.
This tool allows you to replicate (closely) realistic
settlement process in your analysis and record a
variety of statistics from it
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 11
Purposes of simulations
(Deepening of)
OVERSIGHT
Scenario analysis
Risk
quantification
Risk
identification
Stress testing
Assesment of
contingency plans
LVPS
operations
Simulations
of market
infrastructure
Testing &
development
Analysis of market
structure and practicies
New policies
& regulations
Efficiency
Simulations are well suited for multiple CB tasks
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 12
Classification of analyses with BoF-PSS2 with
publicly available results*
Oversight
Network
analysis **
Liquidity
analysis
Credit risk
analysis
Delay/queuin
g analysis
2
20
16
14
USA, UK
FIN, UK, SWE, CAN,
AUT, JPN, SUI, HOL,
HUN, DEN, POL,
NOR, BIS
ISL, UK, CAN, FIN,
AUT, JAP, SUI, HOL,
DEN, POL, BIS
DEN, FIN, UK, SWE,
CAN, AUT, JAP,
HOL, HUN, POL
7
4
5
USA, KOR, FIN,
CAN, UK
ISL, CAN, UK, FIN
USA, DEN, CAN, UK,
FIN
2
15
10
13
USA, UK
FIN, KOR, DEN,
SWE, CAN, USA,
UK, POL, NOR
FIN, ISL, DEN, CAN,
USA, UK, POL
FIN, DEN, SWE,
CAN, USA, UK, POL
5
4
4
USA, FIN, JAP, BIS
USA, FIN, JAP, BIS
USA, DEN, FIN
Operational
development
issues
Policy
concerns
Basic
research
The number of unpublished studies is likely much larger
* See extra slides for more details
** studies performed with same network module which is (currently being) integrated in BoF-PSS2
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 13
Typical oversight studies
•
Network analysis
•
Liquidity analysis
•
Credit risk analysis
•
Delay/queuing analysis
–
–
–
–
Which are the most important participants and connections?
Do connections vary during the day and from day to day?
Which are the end-of-day and overnight patterns?
How would the network change in outages?
–
–
–
–
Which are the current liquidity levels and effects of general drainage?
What is the impact of large participants’ liquidity problems or stopping?
Are some participants working with too low liquidity levels?
How large shocks can the current liquidity supply sustain?
–
–
–
–
How large are the current credit risk levels and systemic risk probability?
How much will credit risks grow in crisis situations?
To which extent can participants sustain current credit limits?
What impact will more stringent credit risk requirement have?
– Which effects will large participants’ and system stop have on delays
– Does some participants delay payments more than others?
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 14
Typical policy studies
•
Network analysis
•
Liquidity analysis
•
Credit risk analysis
•
Delay/queuing analysis
– What would be the impact of new participant access criteria?
– What is the current level of tiering and the impact of possible changes?
– What is the network characteristic of prioritised transactions?
–
–
–
–
What is the impact of new liquidity regimes
What would the effects be of new liquidity pricing schemes?
What would be the impact of different prioritising regimes?
What would be the most efficient liquidity/delay levels?
– What would the impact be of new credit risk rules?
– What would be the most efficient credit risk/delay levels?
– What could be the effects of new rush-hour pricing policies?
– Which gridlock resolution algorithms would be most efficient for given
payment flows?
– Which are the effects of bypassing FIFO or other processing order rules?
– Which are the effects of new open hour rules?
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 15
Typical operational studies
• Network analysis
– Which are the current capacity profiles and bottlenecks?
– How would different shocks change the capacity profiles?
– How much capacity does different prioritising schemes for different
system outage scenarios require
• Liquidity analysis
– What effects would different kinds of marked-based syncronisation
and timing rules have?
– What impact would shifting volumes between different systems
have?
– Which are the effects of different types of liquidity bridges?
– How fast should liquidity expansion operations be?
• Credit risk analysis
– How fast need credit limit change procedures to be?
• Delay/queuing analysis
– Which would be effects of introducing prioritising, queueing and
gridlock resolution features?
– How efficiently are current prioritising, queuing and gridlock
resolution features used?
– How would algorithms’ parameter changes affect overall queuing?
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 16
Typical basic research studies
•
Network analysis
•
Liquidity analysis
•
Credit risk analysis
•
Delay/queuing analysis
– Which are current network structures in different systems?
– Are there typical trends in network structure changes?
– Are there differences in marked-driven and society-optimal network
structures?
– Benchmarking liquidity levels across systems and countries?
– Are there typical trends in liquidity provision regime changes?
– Which are the differences between public and private liquidity regimes?
– Are there general warning signals for increased systemic risk?
– How could systemic risk probabilities be best measured?
– Which are the historic correlations between systemic risks and participants
credit risks?
– Which are the efficiency and risk concerns of private vs public credit risks?
– Can general optimality among gridlock algorithms be established?
– Are there differences among service providers’ and customers’
preferences?
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 17
Outline
• BoF-PSS2 simulator basics
• Intended applications and examples
• How to use this simulator in agent based models
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 18
Integration in agent based models
• Common approach with BoF-PSS2 so far has been
deterministic event based simulations
• Alternatives were mentioned
already in 2003
1. Integrate with external
dynamic model
2. Modify the algorithms
and include e.g. Agent
based modeling
elements
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 19
Solution 1, external dynamic model
• Independent agent based model, which creates input
data or parameters: small economy, artificial exchange...
• BoF-PSS2 as a model of the settlement system
– Integration with the external model with data files in specified
locations
– BoF-PSS2 has command line interface
в‡’ automated simulation runs can be started from the external
model
• Benefits
– No limitation for the tool used in the external model
• Disadvantages
– Currently only file based batch run approach is supported
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 20
Solution 2: user module changes
Recall that
•Process logic is splitted
into algorithm classes
•Existing algorithms are
open source code
•Users can easily*
include own modules
Simulator engine: User interface,
process control, all common data
Submission algorithm
Input
DB
Logical place for an agent
based model is in the
submission algorithm:
”What happens next in
the simulated setup”
System X
Transaction?
Settle
directly?
System Y
Entry
Trans- Split
action?
Injection
Entry
Split
Injection
Add to
queue
Settlement
QUE
Settle
directly?
Add to
queue
Found any
settlable?
PNS
Settlement
Bil.Ofs.
Update
balances&
bookings
Update
queue
Update
queue
Found any
settlable?
MNS
QUE
PNS
Bil.Ofs.
MNS
Transaction
queue
End
Account &
bilateral
balances
Transaction
queue
Update
balances&
bookings
Booking
queue
Account &
bilateral
balances
End
Booking
queue
Output
DB
*See the following:
•Algorithm descriptions and user module development guide
•Source code for all algorithms can be found in the simulators home pages or installation folder
Bank of Finland •Step by step demo in the simulator extranet (only for licenced users though)
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 21
User modules solution continued
• Benefits
– Allows the ABM to react on internal state variables of the
settlement system on transaction level
– Use of Java based toolboxes possible
• Repast, Jawa Swarm…
– Succesfull new algorithms can be distributed to wide user
community
– BoF is open for joint project proposals – good track record from
sponsorship projects for enlarging the capabilities of BoF-PSS2
• Disadvantages
– BoF-PSS2 is not fully open source; engine, interfaces and main
data structures can’t be changed by the user
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 22
Summary
• BoF-PSS2 is
– Designed to be an analysis tool
– Flexible and versatile description of payment system process
logics
– Widely used for payment system related oversight or policy
analyses, operational development and research
– Available free of charge for these purposes
– Also compatible with agent based approach
• It is not
– Limited to existing set of algorithms
– Limited to deterministic simulations with historical data
Be the first one to build
an agent based model into this tool!
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 23
Thank you!
Contact details:
Simulator home pages
–
–
–
–
matti.hellqvist(at)bof.fi
bof-pss(at)bof.fi
www.bof.fi/sc/bof-pss
Documentation
Ordering info
List of published studies
Call for papers for the 7th simulator seminar in Aug 09 is open
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 24
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 25
Extras
• Publicly reported studies which have utilised BoF-PSS2
classified into four cathegories (see table on slide 13)
–
–
–
–
Oversight
Policy studies
Operational studies
Basic research
• Works which share strongly aspects from several
cathegories have been listed under each relevant
cathegory
• For more details see the BoF-PSS2 home pages for
– List of published studies
– List of previous simulator seminars and workshops and their
presentations
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 26
Oversight studies I
Finnish BoF-RTGS - assess liquidity effects of introduction of TARGET and the shift to a greater use of RTGS
settlement – results published 1997 in BoF E:14
Iceland’s Sedlabanki - netting vs. real-time gross settlement - setting credit limits for the system, 1999
Bech and Soramäki (2002) �Liquidity, Gridlocks and Bank Failures in Large Value Payment systems’, E-Money
and Payment systems Review (Bech-Soramäki)
Paul Bedford - Stephen Millard - Jing Yang, BoE: Analysing the impact of operational incidents in large-value
payment systems: A simulation approach
Björn Segendorff, Sveriges Riksbank: Liquidity levels and delays in RIX
Darcey McVanel, Bank of Canada: The impacts of unanticipated failures in Canada's Large Value Transfer
System
Matti Hellqvist, Bank of Finland: Stress testing securities settlement systems using simulations
Claus Puhr, Stefan W. Schmitz / Oesterreichische Nationalbank: Risk Concentration and Operational Risk in
Payment Systems – A Simulation Approach
Kei Imakubo, Yutaka Soejima / Bank of Japan: Intraday Settlement Activities in the BOJ-NET RTGS
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 27
Oversight studies II
Ana Lasaosa, Merxe Tudela / Bank of England: Risks and efficiency gains of a tiered structure
in large-value payments: a simulation approach
Matti Hellqvist / Bank of Finland: Stress testing liquidity needs in Finnish retail securities
settlement system
Martina Glaser, Philipp Haene / Swiss National Bank: Simulation of participant-level
operational disruption in Swiss Interbank Clearing
Ronald Heijimans / De Nederlandsche Bank: Stress simulations: A Dutch case
ГЃgnes LublГіy, Eszter Tanai / Magyar Nemzeti Bank: Operational Disruption and the Hungarian
RTGS system VIBER
Neville Arjani and Lana Embree, Bank of Canada: Consolidation in Canada's LVTS: A
Simulation Study
Kristian Sparre Andersen and Irene Madsen, Danmarks Nationalbank: A quantitative
assessment of international best practices in relation to business continuity arrangements in
payment systems
Matti Hellqvist, Bank of Finland: Implicit intraday counterparty limits in large value payment
systems
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 28
Oversight studies III
Jenni Koskinen, Bank of Finland: The liquidity impact of merging bond and equity
settlement systems
Agnieszka Grat-Osinska - Miroslaw Pawliszyn: Liquidity Levels and Settlement
Delays in the Sorbnet System-Simulation-Based Approach With the Application of the
BOF-PSS2 Payment
Asbjorn Enge and Frode Overli: Intraday liquidity and the settlement of large-value
payments: a simulation-based analysis (Economic Bulletin 1/2006, Norges Bank)
Elisabeth Ledrut / Bank for International Settlements: Tit for Tat in Payment
Systems
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 29
Policy studies I
Finnish BoF-RTGS - assess liquidity effects of introduction of TARGET and the shift to a greater use of RTGS
settlement – results published 1997 in BoF E:14
Iceland’s Sedlabanki - netting vs. real-time gross settlement - setting credit limits for the system, 1999
Danmarks Nationalbank 2000 – main focus on gridlock resolution – results published in BoF discussion paper
series 9/2001 and DNB Monetary Review 4/2001
Bank of Korea – alternative liquidity provision, optimisation methods, 2002
Leinonen and Soramäki (1999) �Optimizing Liquidity and Settlement Speed in Payment Systems’, Discussion
Paper, Bank of Finland
Soramäki (2000) �Alternative Liquidity Management Features in an RTGS Environment’, Financial Markets
Department Working Paper
Bech and Soramäki (2002) �Liquidity, Gridlocks and Bank Failures in Large Value Payment systems’, E-Money
and Payment systems Review (Bech-Soramäki)
Björn Segendorff, Sveriges Riksbank: Liquidity levels and delays in RIX
Neville Arjani, Bank of Canada: Examining the Balance between Risk and Efficiency in Canada’s LVTS: A
Simulation Approach
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 30
Policy studies II
Matti Hellqvist, Bank of Finland: Stress testing securities settlement systems using simulations
Morten Bech and Kurt Johnson, Federal Reserve Bank of New York: BoF-PSS 2.0.0 A tool for policy analysis
Kemal Ercevik, John Jackson / Bank of England: Simulating the impact of hybrid functionality on CHAPS
banks
Kristian Sparre Andersen and Irene Madsen, Danmarks Nationalbank: A quantitative assessment of
international best practices in relation to business continuity arrangements in payment systems
Jenni Koskinen, Bank of Finland: The liquidity impact of merging bond and equity settlement systems
Agnieszka Grat-Osinska - Miroslaw Pawliszyn: Liquidity Levels and Settlement Delays in the Sorbnet SystemSimulation-Based Approach With the Application of the BOF-PSS2 Payment System Simulator (SSRN, Financial
Markets and institutions, May 2007)
Neville Arjani: Examining the Trade-Off between Settlement Delay and Intraday Liquidity in Canada's LVTS: A
Simulation Approach (Working Paper 2006-20, Bank of Canada)
Asbjorn Enge and Frode Overli: Intraday liquidity and the settlement of large-value payments: a simulationbased analysis (Economic Bulletin 1/2006, Norges Bank)
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 31
Operational studies
Iceland’s Sedlabanki - netting vs. real-time gross settlement - setting credit limits for the system, 1999
FRB New York – alternative queuing/liquidity concepts – a �Receipt Reactive Gross Settlement’ queue, 2000
Danmarks Nationalbank 2000 – main focus on gridlock resolution – results published in BoF discussion paper
series 9/2001 and DNB Monetary Review 4/2001
Bank of Korea – alternative liquidity provision, optimisation methods, 2002
Soramäki (2000) �Alternative Liquidity Management Features in an RTGS Environment’, Financial Markets
Department Working Paper
Neville Arjani, Bank of Canada: Examining the Balance between Risk and Efficiency in Canada’s LVTS: A
Simulation Approach
Kemal Ercevik, John Jackson / Bank of England: Simulating the impact of hybrid functionality on CHAPS
banks
Neville Arjani: Examining the Trade-Off between Settlement Delay and Intraday Liquidity in Canada's LVTS: A
Simulation Approach (Working Paper 2006-20, Bank of Canada)
Bank of Finland
PAYMENT AND SETTLEMENT SYSTEM SIMULATOR
ABM-BaF 10 February 2009 • 32
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