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EXANTE Algorithmic Trading: Practical Aspects

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Slides for speech of EXANTE Managing Partners Vladimir Maslyakov and Anatoliy Knyaze , entitled "Practical aspects of algorithmic trading and high-frequency trading", on TradeTech Russia 2011

Presentation highlights the problems associated with the development of a model (pre-trade analysis), the launch of the strategy (trading) and the post-trade analysis, as well as an overview of the algorithmic trading in general, and a small glimpse into the future.

Published in: Economy & Finance, Business

EXANTE Algorithmic Trading: Practical Aspects

  1. 1. Algorithmic trading: practical aspects EXANTE Ltd. exante.com.mt info@exante.com.mtMoscow 2011
  2. 2. I. Algorithmic tradingII. Develop the modelIII. Launch the strategyIV. Analyze the resultsV. Trends
  3. 3. Algorithmic trading Automated trading HFT
  4. 4. Arbitrage Pricing Automated trading Buy-side Sell-sideTrendfollowing Smart order routingStat arbitrage Market Making / HFT VWAP
  5. 5. I. Algorithmic tradingII. Develop the modelIII. Launch the strategyIV. Analyze the resultsV. Trends
  6. 6. Data Hypothesis Model Testing
  7. 7. Historical Data Width Depth CorrectnessInstruments Past period Splits and divs Venues Resolution GapsCorp. actions Order book Timestamps News Counterparties Validation
  8. 8. Data Hypothesis Model Testing
  9. 9. A priori knowledgeFundamental Empirical Gut feeling
  10. 10. Visualization Datavolume Math Speed Иллюстрация с panopticon.com
  11. 11. RTS Index and S&P Index, 2010-10-11 RTSI SPX16:40 16:50 17:00 17:10 17:20 17:30 17:40
  12. 12. Data Hypothesis Model Testing
  13. 13. ModelAlpha Risks Transaction costs
  14. 14. EDGE ?
  15. 15. Model: math Prototype
  16. 16. Our experience: RDomain Libraries Open and free Slow No realtime Open and free
  17. 17. Data Hypothesis Model Testing
  18. 18. TestingData Prototype Results• Historical data • R / Python/ • Alpha• Modeling Java • Risks market impact • Cluster / cloud • Transaction and order flow • GPU costs• Realtime
  19. 19. I. Algorithmic tradingII. Develop the modelIII. Launch the strategyIV. Analyze the resultsV. Trends
  20. 20. Инфраструктура
  21. 21. Realtime data Speed Depth Coverage Low-latency L1 AmericasUltra low-latency L2 EuropeSub millisecond Raw Asia
  22. 22. Strategy Language Infrastructure ControlHigh-level (C++, Java, Client Manual C#, etc) DSL (Slang, etc) Server Automatic Visual (diagrams) Cloud GUI Strategy sandbox Data OrdersNYSE MFG Robot 1 Robot 2 Robot 3 Robot 4 LSE JP
  23. 23. Arbitrage example London Server (Telehouse) Arbitrage strategyGAZPRU On new tick: LIMIT (LSE)(MICEX) ogzd_rub = convert(ogzd, usd_rub) spread = normalize(ogzd_rub/gazpru) Filled (size) changedSpread() OGZD (LSE) On change spread: if (spread > threshold) MARKET (MICEX) place_limit(OGZD, price, size)USD/RUB Filled (price)(FOREX) On limit fill: If (limit_is_filled) place_market(GAZPRU, size) Parameters: threshold
  24. 24. VWAP example Moscow Server (MacomNet) VWAP strategySBER bid/ask On new tick:(MICEX) vwap = recalculateVwap(trades) execute_vol = recalculate(average_volume, volume) MARKET (MICEX)SBER volume executeOrder(execute_vol)(MICEX) Filled (size) on market fill:SBER trades(MICEX) our_vwap = update(price, size) vwap_delta = our_vwap - vwap Parameters: average_volume
  25. 25. I. Algorithmic tradingII. Develop the modelIII. Launch the strategyIV. Analyze the resultsV. Trends
  26. 26. Gather results dataMarket snapshot Orders Data Latency Strategy parameters
  27. 27. Export the results data Excel R, Matlab ExportVisualization Model
  28. 28. Compare with the model
  29. 29. Optimize the parameters Model Results Testing Trading
  30. 30. I. Algorithmic tradingII. Develop the modelIII. Launch the strategyIV. Analyze the resultsV. Trends
  31. 31. Adoption100 FORTS CME GLOBEX Vol, % Msgs, % 90 E-mini S&P 500 Futures 51.66 69.9390 EuroFX Futures 69.32 83.4180 Eurodollar Futures 51.29 64.4670 60 Crude Oil Futures 35.34 71.2460 Algorithmic Trading and Market Dynamics July 15, 20105040 Foreign Exchange Buy-side, % Sell-side, %30 Order Routing 25 9220 Time-slice 25 1510 Liquidity 42 46 0 Alpha 92 39 Vol, % Msg, % FX Hedging 25 39 Estimated by FORTS 09.2011 Streambase 2011 Special Report on FX
  32. 32. Dodd-Frank Swap Execution Facility.SEC 15c3-5 Eliminate naked access to exchange.MiFID II Crossing networks, derivatives, HFT.
  33. 33. Algotrader: a new breed MathematicsTechnology Finance
  34. 34. Strategies Multi-assetULL DMA HFT trading Buy-side or sell- FX, Eqty, Debt, 5μs / km side? Derivs Market making Europe, USA, Asia< 100μs / algo Liquidity search Feeds and and aggregation execution106 msg / sec Fast and reliable Stat arb data
  35. 35. TechnologiesSoftware Overclocking FPGAMulti-core GPGPU Cloud x32 x200 x30000
  36. 36. Our experience: cloud Power Diversity Cost controlEngineering Compliance Latency
  37. 37. Service!
  38. 38. Anatoliy Knyazev ak@exante.com.mtVladimir Maslyakov vm@exante.com.mt

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