EXTENT-2015: Efficient Risk Control - Challenges & Techniques

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

Transcript

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 2012 2013 2013 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 4  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 7  In all asset types  In any currency  For different settlement dates  Flexible rules of calculation Position
9. ARQA approach 8  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 11 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 13 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 17 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 18  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