Efficient Risk Control - Challenges and Techniques Vladimir Kurlyandchik, ARQA Technologies 11 November 2015 Trading Technology Trends & Quality Assurance Conference in St. Petersburg

1. Efficient risk control —
challenges and
techniques.
ARQA's case study
Vladimir Kurlyandchik
director, business development

2. FLASH CRASH
Introduction
1
$31.7 mln $100 mln $440 mln
201220132013
May 2010

3. Typical risk models
2
For equities:
 counterparty limits
 size of order
 frequency of orders (in some cases)
For derivatives:
 fixed amount of dollars (rubles, euros) per contract including options
For FX:
 full prefunding for corporates
 leverage 1:100 and higher for private investors
For bonds:
 counterparty limits

4. Client needs
3
Private investor: One account to trade any asset type
HFT client: Different types of arbitrage strategies
Institutional client: Effective risk management

5. Gap reasons
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 Trading platform fragmentation — broker uses different platforms for different
asset types and exchanges
 Risk control works as defense against fear
 Risk management department is not a business but a support unit of sell-side
company
 Latency reasons — people don’t want to affect latency by complex risk checks

6. How to solve the problem?
5
Level 1 Changing the attitude to risk management
Level 2 Clear understanding of client groups (trading patterns and
requirements)
Level 3 Easily adapted risk management solution architecture
Level 4 Quality of implementation of risk management solution

7. ARQA approach
6

8. ARQA approach
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 In all asset types
 In any currency
 For different settlement dates
 Flexible rules of calculation
Position

9. ARQA approach
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 Different sources:
• trading venues (LSE, LSE derivatives, Turquoise, CME, Eurex, EBS ICAP,
WSE, MOEX)
• market data vendors (Thomson Reuters, SunGard, S&P Capital IQ)
• FX liquidity pools
 As fast as possible
Market Data

10. ARQA approach
9
 Full prefunding
 Several margin trading models (one leverage for all assets, different discounts for
different assets, etc.)
 Classical prop-trading limits (limit on short, long, net in a particular asset)
 Netting opposite positions in correlated instruments (stock against single stock
futures, currency pair against corresponding futures, local stock against GDR)
 SPAN-like methodology
RISQ models

11. ARQA approach
10
 Flat fee
 Fixed amount of money per contract
 Commission scale
 Minimum and maximum commission amount
Pre-trade and post-trade calculating
Fees

12. ARQA approach
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Multi-currency
 Multi-currency support
 Different scenarios
 Business advantages for different client groups
 Full risk control

13. ARQA approach
12
RISQ terminal
Main tasks
 show real-time position from different angles
 show real-time information about risk parameters for client position
 what-if calculators
Automate some procedures
 margin calls
 position termination
 obligation rollover

14. Infrastructure cases
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Example 1: Servicing retail clients
Gateways
Replicator
End clients
RISQ/EMS
server 1
RISQ/EMS
server 2
End clients
Gateways
Exchanges

15. Infrastructure cases
14
Example 2: Servicing HFT client
Black box
RISQ server
Transactions
RISQ filter module
Yes/No Exchange
Drop copy
Gateway

16. Infrastructure cases
15
Example 2: Servicing HFT client
Black box
RISQ server
QUIK KillSwitch
Yes/No
Exchange
Gateway
Trigger exchange KillSwitch

17. Infrastructure cases
16
Example 3: Extending existing
infrastructure by advanced risk checks
End clients
Broker’s EMS
RISQ server
FIX
adapter
FIX
order router
Exchange
Gateway
Transactions
Drop copy

18. Numbers
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Capacity
 Number of positions – 2 million
 Number of orders – 30 million
 Number of trades – 2 million
Latency
 RISQ server, margining on stocks with discounts – 1 ms per transaction
 RISQ server portfolio margining – 2-3 ms per transaction
 FIXPreTrade RISQ filter for Windows, any model – 100 mcs
 FIXPreTrade RISQ filter for Linux (tcp off load), any model – 30 mcs

19. Development and testing
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 Dedicated business analysis staff
 Enrichment of internal expertize by internal and external seminars
 Cooperation of inside development team and technical support
 Delivery new versions for testing with special cases from developers and analysts
 Specially developed environment to run automated tests
 Investigations of new releases before go live dates