TECHNOLOGY PREVIEW

Complex Event Processing

CONFIDENTIAL

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

STOCK EXCHANGE

MARKET DATA

RT Real Time

HiD Historical

STOCK EXCHANGE

Dat

aRIV

ER

Dat

abas

e &

Eve

nt

Bro

adca

st

AlgoWRITER Development Environment

AlphaINVENTOR Complex Events Studio

AlgoANALYTICS Backtesting and Analysis

QuoteCANVAS Real-time Charting

TradeBOT Auto-Trading

Trad

eSE

RV

O

Low

Lat

ency

Ord

er M

anag

emen

t

Dat

a A

dap

ters

AlphaBOX FRAMEWORK

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

Database Stores Ordered Data

Event Processor

Stores Queries

Stores Data Handles Queries Request/Response Model Synchronous Static Data

Stores Queries Handles Data Subscribe/Notify “Push” Model Asynchronous Continuous Data

CONFIDENTIAL

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

MARKET DATA

RT Real Time

HiD Historical

DB INSERT

INSERT

UPDATE

TRADE LOGIC

QUERY

BUY/SELL STOCK EXCHANGE

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

MARKET DATA

RT Real Time

HiD Historical

DB

INSERT

INSERT

BUY/SELL STOCK EXCHANGE

Data Stream

Event Stream

TRADE EVENT

UPDATE

Post Processing

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)

--

--

--

--

--

--

--

--

--

A Trade Occurs

Store Trade in Tick Table

--

--

--

--

--

Tick Table Second Table

Compress ticks to a seconds table

Compute Average (a1) Query : last 5 records

Query : last 5 records Compute Average (a2)

IS LR < max(a1

,a2)

Query : last record (LR)

Was this false last instance

?

BUY

Wait fo

r DB

up

date

CONFIDENTIAL

Trading Example (CEP based approach)

A Trade Occurs BUY

Event Stream

newSecond

newTick

Stream Processor

Buffer SEC (5 Length)

Buffer TICK (5 Length) AVG()

AVG()

Trade()

MAX()

CONFIDENTIAL

Trading Example (CEP based approach)

• 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

MARKET DATA

RT Real Time

HiD Historical

INSERT

INSERT

Data Stream

Event Stream

• OnNewBar() • OnClose() • OnPattern1() • OnPattern2() • OnOpen() • OnNewHigh()

• OnNewLow() • OnTick() • OnVolumeSpike() • Etc …

Event Processors/ Handlers

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