1. Pre-trade risk – a unified approach for various trading infrastructures Vladimir Kurlyandchik Director of business development arqa.ru

2. Sources of financial errors

3. 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 arqa.ru

4. 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 arqa.ru

5. Risk server Control by broker Trading Venue Client Risk Server Broker’s Infrastructure arqa.ru

6. Risk server Multi venues arbitrage netting obligations higher volumes arqa.ru

7. Risk server Various risk control models arqa.ru

8. Risk server A ssets, currencies, settlement conditions arqa.ru

9. Risk server Fast and scalable consecutive calculation number of clients number of transactions drop-copy processing arqa.ru

10. Risk calculation approaches Genuine pre-trade Pre-trade control Risk Server Trading Venue Client arqa.ru

11. Risk Server Risk calculation approaches Fast pre-trade yes / no Pre-trade Control Module Trading Venue Client arqa.ru

12. Latency defines approach Risk Server Trading Venue Client Risk Server Trading Venue Client Pre-trade Control Module Pre-trade control 2-3 msrisk server at co-location ≤ 5 ms risk server in broker’s data center Market data latency arqa.ru

13. Pre-trade & Algo Trading Venue Pre-trade Control Module Risk Server yes Algo Engine + no Clients arqa.ru

14. Pre-trade & OMS FIXPreTrade Trading Venue yes / no Risk Server FIX Broker’s OMS FIX arqa.ru

15. Risk awareness of clients monitoring risks what-if calculator closing positions arqa.ru

16. Case study: Retail 150 000 clients’ accounts 400 000 positions in cash and equities 40 000 positions in derivatives 0.9 - 5 mspre-trade check latency 0.4 msposition adjustment after trade ~ 10 mlnprocessed transactions per day ~ 1.5 mlnprocessed trades per day arqa.ru

17. 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 msaverage transaction latency 2-3 msrisk server overhead arqa.ru

18. Trading Venues Buy-side Risk Server Case study: Buy-side Broker B Broker A Risk Server arqa.ru

19. FIX2Market FIX Trading Venue Client Co-location HFT Engine yes / no Risk Server Exchange protocol Market data and client operations Case study: Fast pre-trade for HFT ≤ 30 mcschecks per transaction arqa.ru

20. Workstation HFT Engine yes / no Risk Server Market data and client operations Exchange co-location Trading Venue MICEX bridge Exchange API Case study: Collaboration with exchange Moscow Exchange 3 mcschecks per transaction arqa.ru

21. Three actionable takeaways arqa.ru 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.

22. Thank You! Questions? arqa.ru