Transcript Pre-trade risk control – a unified solution for various trading

Pre-trade risk – a unified approach for various
trading infrastructures
Vladimir Kurlyandchik
Director of business development
arqa.ru
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Sources of financial errors
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Key factors to succeed
understanding the client’s trading model
mathematical tools of risk management
taking into account peculiarities of
particular markets
understanding of various infrastructure
options
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Risk server requirements
control by broker
multi venues
various risk control models
multi asset, multi currency and portfolios
with different settlement conditions
fast and scalable
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Risk server
Control by broker
Trading Venue
Risk Server
Broker’s Infrastructure
Client
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Risk server
Multi venues
arbitrage
netting obligations
higher volumes
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Risk server
Various risk control models
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Risk server
Assets, currencies, settlement conditions
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Risk server
Fast and scalable
consecutive calculation
number of clients
number of transactions
drop-copy processing
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Risk calculation approaches
Genuine pre-trade
Client
Trading Venue
Pre-trade
control
Risk Server
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Risk calculation approaches
Fast pre-trade
Client
Trading Venue
Pre-trade Control
Module
yes / no
Risk Server
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Latency defines approach
Client
Trading Venue
Pre-trade
control
Trading Venue
Pre-trade Control
Module
Risk Server
Market data latency
2-3 ms
risk server at
co-location
≤5 ms risk server in
broker’s data center
Risk Server
Client
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Pre-trade & Algo
Trading Venue
Pre-trade Control
Module
Algo Engine
Clients
yes
no
Risk Server
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Pre-trade & OMS
Broker’s OMS
Trading Venue
FIXPreTrade
FIX
FIX
yes / no
Risk Server
FIX
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Risk awareness of clients
monitoring risks
what-if calculator
closing positions
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Case study:
Retail
150 000
clients’ accounts
400 000
positions in cash and equities
40 000
positions in derivatives
0.9 - 5 ms
pre-trade check latency
0.4 ms
position adjustment after trade
~10 mln
processed transactions per day
~1.5 mln
processed trades per day
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Case study:
Genuine for HFT
15 mln
transactions per day
30%
of all transactions at Stock market of
Moscow exchange
450
transactions per second - average speed
800
transactions per second - peak speed
≤5.6 ms average transaction latency
2-3 ms
risk server overhead
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Case study:
Buy-side
Broker A
Buy-side
Risk Server
Risk Server
Broker B
Trading Venues
Risk Server
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Case study:
Fast pre-trade for HFT
Client
Trading Venue
FIX2Market
Exchange
protocol
FIX
yes / no
HFT Engine
Market data and
client operations
Co-location
Risk Server
≤30 mcs checks per
transaction
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Case study:
Collaboration with exchange
Moscow
Exchange
Workstation
Trading Venue
MICEX bridge
Exchange API
Market data and
client operations
Exchange co-location
yes / no
3 mcs checks per
transaction
HFT Engine
Risk Server
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Three actionable takeaways
1. Effective risk control starts with a trading pattern, employs mathematic models and
appropriate infrastructure options while taking into account market peculiarities.
2. A fast and scalable risk server must be controlled by the broker. The server applies
various risk control models simultaneously to cope with multiple instruments and
portfolios with different settlement conditions at many trading venues.
3. The choice between full pre-trade and fast pre-trade is dictated by the latency
requirement of a particular trading technique (algo, OMS, retail, buy side, HFT).
There are options to implement risk controls for maximum benefits.
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Thank You!
Questions?