Pre-trade risk

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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 clients 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 serverControl by broker
Client
Trading Venue
Risk Server
Brokers Infrastructure
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Risk serverMulti venues
arbitrage netting obligations higher volumes
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Risk serverVarious risk control models
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Risk serverAssets, currencies, settlement
conditions
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Risk serverFast and scalable
consecutive calculation number of clients number
of transactions drop-copy processing
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Risk calculation approachesGenuine pre-trade
Client
Pre-trade control
Trading Venue
Risk Server
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Risk calculation approachesFast pre-trade
Client
Pre-trade Control Module
Trading Venue
yes / no
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Latency defines approach
Client
Client
Pre-trade Control Module
Trading Venue
Trading Venue
Pre-trade control
Risk Server
Risk Server
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Pre-trade Algo
Pre-trade Control Module
Trading Venue
Algo Engine

Clients
yes
no
Risk Server
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Pre-trade OMS
Brokers OMS
Trading Venue
FIXPreTrade
FIX
FIX
FIX
yes / no
Risk Server
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Risk awareness of clients
monitoring risks what-if calculator closing
positions
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Case studyRetail
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 studyGenuine 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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arqa.ru
Case studyBuy-side
Broker A
Buy-side
Broker B
Trading Venues
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Case studyFast pre-trade for HFT
Client
Trading Venue
FIX2Market
FIX
Exchange protocol
HFT Engine
yes / no
Market data and client operations
Co-location
Risk Server
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Case studyCollaboration with exchange
Workstation
Moscow Exchange
Trading Venue
MICEX bridge
Exchange API
yes / no
Market data and client operations
HFT Engine
Exchange co-location
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?