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TECHNOLOGY
PREVIEW
Complex Event Processing


                           CONFIDENTIAL
Introduction : AlphaBOX

 About AlphaBOX
 We have experienced a very wide variety of customers in our past allowing us to notice the complete spectrum
 of issues and nuances of almost all trading(quant) desks . We also noticed that each hedge fund or CTA begins
 with same sets of IT assumptions and tools before beginning their operations. Once they reach a certain
 maturity, it is common for them to have some custom development over their tools.

 The above practice is heavily harmful to future projects as several different tools are used which may or may
 not be designed for the same purpose.

 AlphaBox is a suite of data-centric algorithmic trading applications which is flexible enough to support trading
 styles like HFT (High frequency trading) , Statistical Arbitrage, Scalping , Swing trading etc.
 We have designed the core to be quick, lightweight and scalable. Our entire architecture is specialized for
 asynchronous ,real time ,low latency data processing commonly known as CEP (complex event processing)




                                                     CONFIDENTIAL
Product Architecture : Outline


                                                                                                                     QuoteCANVAS




                                                                                                                                                           Low Latency Order Management
                                                                                                                     Real-time Charting




                                                    Database & Event Broadcast
  STOCK
  EXCHANGE




                                                                                                                                              TradeSERVO
                        Data Adapters
                                                                                                                     AlgoANALYTICS



                                        DataRIVER
                                                                                                                   Backtesting and Analysis
                                                                                                                                                                                          STOCK
                                                                                                                                                                                          EXCHANGE
                                                                                 AlphaINVENTOR                         AlgoWRITER
           RTTime
           Real
                                                                                 Complex Events Studio             Development Environment

  MARKET
  DATA
                                                                                     TradeBOT
           HiD
           Historical
                                                                                     Auto-Trading




                                                                                      AlphaBOX FRAMEWORK




                                                                                                    CONFIDENTIAL
Complex Event Processing : Introduction


 • Event : An event is a piece of data that represents that
   something happened in the real world. Events flow in streams
   within any ordered data set
 • Example : 100 Shares of IBM were Bought, IBM price changed
   by X points, a client A accessed server B.
 • Complex Events : (a) IBM share falls 1 point and rises 4 points
   in 5 seconds. (b) 4 charges against same credit card from
   different companies within 1 minute.
Complex Event Processing : Introduction



                                              Event
                                            Processor
           Database
                                              Stores
      Stores Ordered Data                    Queries



        Stores Data                     Stores Queries
        Handles Queries                 Handles Data
        Request/Response Model          Subscribe/Notify “Push” Model
        Synchronous                     Asynchronous
        Static Data                     Continuous Data
Complex Event Processing : Introduction

 • Key Advantages
     – Process data “in-stream” without any requirement to store. Same
       difference between PUSH email and POP3
     – Handle “imperfections” in the stream instantaneously
     – Distributed & Scalable : think of data streams which can flow and
       merge at pre-designated nodes.
     – Dynamic Runtime Querying is possible
     – High Speed Pattern Recognition via Rete type algorithms




                                   CONFIDENTIAL
Complex Event Processing : Trading Example

  • DBMS based approach to Data Mining & Analysis

         RTTime
         Real
                      INSERT                             Q
MARKET                                                   U
DATA                                                         TRADE   BUY/SELL   STOCK
                                     DB                  E   LOGIC              EXCHANGE
         HiD
         Historical
                      INSERT                             R
                                                         Y

                                    UPDATE




                               Major Bottleneck

    Market data is stored first and then a query is run from the trade logic, very slow !
                                              CONFIDENTIAL
Complex Event Processing : Trading Example

 • Event Stream based approach to Data Mining & Analysis

                                                               TRADE                       STOCK
                                                               EVENT
                                                                        BUY/SELL           EXCHANGE

           RTTime
           Real
                          INSERT
  MARKET                            Data       Event
  DATA
                                   Stream     Stream
           HiD
           Historical
                          INSERT                                         Post Processing


                                                                DB

                                                               UPDATE


                        Trade gets executed as soon as a “Trade” event arrives !
                                                CONFIDENTIAL
Complex Event Processing : Trading Example

Sample Trading Algorithm
• If last traded price of IBM falls below the average price of last
  highest(5 seconds,5 trades) then buy 1000 shares IBM.
• Close the trade after 10 seconds.

We will walk through this example using conventional approach
and the CEP approach



                                CONFIDENTIAL
Trading Example (DBMS based approach)

              Tick Table        Second Table
                --                  --
                                                                    Query : last 5 records       Compute Average (a1)
                --                  --




                                               Wait for DB update
                --                  --
                                                                    Query : last 5 records       Compute Average (a2)
                --                  --

                --                  --

                --                                                  Query : last record (LR)
A Trade
                --
Occurs
                --

                --                                                                                             Was this
                                                                                       IS LR <
                                                                                                               false last
                                                                                       max(a1                               BUY
                                                                                                               instance
                                                                                         ,a2)
                                                                                                                   ?


          Store Trade in Tick    Compress
          Table                  ticks to a
                                 seconds
                                 table
                                                                    CONFIDENTIAL
Trading Example (CEP based approach)

                                                         AVG()
                               Buffer SEC (5 Length)

                                Buffer TICK (5 Length)   AVG()


             newSecond                                   MAX()


A Trade   Event Stream                  Stream Processor         Trade()   BUY
Occurs


              newTick




                            CONFIDENTIAL
Trading Example (CEP based approach)

                                                                  Event Processors/ Handlers
                                                            •   OnNewBar()      • OnNewLow()
         RTTime
         Real
                      INSERT                                •   OnClose()       • OnTick()
MARKET                          Data     Event              •   OnPattern1()    • OnVolumeSpike()
DATA                           Stream   Stream
                                                            •   OnPattern2()    • Etc …
         HiD          INSERT
         Historical                                         •   OnOpen()
                                                            •   OnNewHigh()

 •   As you can see each event stream can generate any type and number of events.
 •   Those events are processed and handled at each level.
 •   This way, as the data flows through the structure, processing occurs
     instantaneously and asynchronously.
 •   This approach makes pattern recognition highly efficient
                                                 CONFIDENTIAL
AlphaBOX

 • Key Advantages
    –   CEP based scalable structure
    –   Low Latency Message driven Processing
    –   Hybrid Stream + DBMS system
    –   In-Memory Processing
    –   Multicore utilization
    – Applicable to almost ANY type of real-time data streams
    – Highly extensible
    – Real – Time Application in truest sense

                                  CONFIDENTIAL

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AlphaBox Technology Overview

  • 2. Introduction : AlphaBOX About AlphaBOX We have experienced a very wide variety of customers in our past allowing us to notice the complete spectrum of issues and nuances of almost all trading(quant) desks . We also noticed that each hedge fund or CTA begins with same sets of IT assumptions and tools before beginning their operations. Once they reach a certain maturity, it is common for them to have some custom development over their tools. The above practice is heavily harmful to future projects as several different tools are used which may or may not be designed for the same purpose. AlphaBox is a suite of data-centric algorithmic trading applications which is flexible enough to support trading styles like HFT (High frequency trading) , Statistical Arbitrage, Scalping , Swing trading etc. We have designed the core to be quick, lightweight and scalable. Our entire architecture is specialized for asynchronous ,real time ,low latency data processing commonly known as CEP (complex event processing) CONFIDENTIAL
  • 3. Product Architecture : Outline QuoteCANVAS Low Latency Order Management Real-time Charting Database & Event Broadcast STOCK EXCHANGE TradeSERVO Data Adapters AlgoANALYTICS DataRIVER Backtesting and Analysis STOCK EXCHANGE AlphaINVENTOR AlgoWRITER RTTime Real Complex Events Studio Development Environment MARKET DATA TradeBOT HiD Historical Auto-Trading AlphaBOX FRAMEWORK CONFIDENTIAL
  • 4. Complex Event Processing : Introduction • Event : An event is a piece of data that represents that something happened in the real world. Events flow in streams within any ordered data set • Example : 100 Shares of IBM were Bought, IBM price changed by X points, a client A accessed server B. • Complex Events : (a) IBM share falls 1 point and rises 4 points in 5 seconds. (b) 4 charges against same credit card from different companies within 1 minute.
  • 5. Complex Event Processing : Introduction Event Processor Database Stores Stores Ordered Data Queries  Stores Data  Stores Queries  Handles Queries  Handles Data  Request/Response Model  Subscribe/Notify “Push” Model  Synchronous  Asynchronous  Static Data  Continuous Data
  • 6. Complex Event Processing : Introduction • Key Advantages – Process data “in-stream” without any requirement to store. Same difference between PUSH email and POP3 – Handle “imperfections” in the stream instantaneously – Distributed & Scalable : think of data streams which can flow and merge at pre-designated nodes. – Dynamic Runtime Querying is possible – High Speed Pattern Recognition via Rete type algorithms CONFIDENTIAL
  • 7. Complex Event Processing : Trading Example • DBMS based approach to Data Mining & Analysis RTTime Real INSERT Q MARKET U DATA TRADE BUY/SELL STOCK DB E LOGIC EXCHANGE HiD Historical INSERT R Y UPDATE Major Bottleneck Market data is stored first and then a query is run from the trade logic, very slow ! CONFIDENTIAL
  • 8. Complex Event Processing : Trading Example • Event Stream based approach to Data Mining & Analysis TRADE STOCK EVENT BUY/SELL EXCHANGE RTTime Real INSERT MARKET Data Event DATA Stream Stream HiD Historical INSERT Post Processing DB UPDATE Trade gets executed as soon as a “Trade” event arrives ! CONFIDENTIAL
  • 9. Complex Event Processing : Trading Example Sample Trading Algorithm • If last traded price of IBM falls below the average price of last highest(5 seconds,5 trades) then buy 1000 shares IBM. • Close the trade after 10 seconds. We will walk through this example using conventional approach and the CEP approach CONFIDENTIAL
  • 10. Trading Example (DBMS based approach) Tick Table Second Table -- -- Query : last 5 records Compute Average (a1) -- -- Wait for DB update -- -- Query : last 5 records Compute Average (a2) -- -- -- -- -- Query : last record (LR) A Trade -- Occurs -- -- Was this IS LR < false last max(a1 BUY instance ,a2) ? Store Trade in Tick Compress Table ticks to a seconds table CONFIDENTIAL
  • 11. Trading Example (CEP based approach) AVG() Buffer SEC (5 Length) Buffer TICK (5 Length) AVG() newSecond MAX() A Trade Event Stream Stream Processor Trade() BUY Occurs newTick CONFIDENTIAL
  • 12. Trading Example (CEP based approach) Event Processors/ Handlers • OnNewBar() • OnNewLow() RTTime Real INSERT • OnClose() • OnTick() MARKET Data Event • OnPattern1() • OnVolumeSpike() DATA Stream Stream • OnPattern2() • Etc … HiD INSERT Historical • OnOpen() • OnNewHigh() • As you can see each event stream can generate any type and number of events. • Those events are processed and handled at each level. • This way, as the data flows through the structure, processing occurs instantaneously and asynchronously. • This approach makes pattern recognition highly efficient CONFIDENTIAL
  • 13. AlphaBOX • Key Advantages – CEP based scalable structure – Low Latency Message driven Processing – Hybrid Stream + DBMS system – In-Memory Processing – Multicore utilization – Applicable to almost ANY type of real-time data streams – Highly extensible – Real – Time Application in truest sense CONFIDENTIAL