1. Find the Hidden Signal
in Market Data Noise
Revolution Analytics webinar, 2014-03-18
Andrie de Vries
Business Services Director (Europe)
@RevoAndrie
andrie@revolutionanalytics.com
Revolution Analytics Webinar,
13 March 2013

2. Agenda
 Find the Hidden Signal in Market Data Noise
 Louis Lovas
 Onetick
 Revolution Analytics, the R project and Financial
applications
 Andrie de Vries
 Revolution Analytics

3. THE R PROJECT AND
FINANCIAL APPLICATIONS
Revolution Analytics webinar, 2014-03-18

4. - Started by Robert Gentleman &
Ross Ihaka, 1993
- Version 1.0 in 2000
- 2.5 Million Global Users
- 5000+ “Packages”
- R in Universities = New Talent
- Open Source = Access To
Innovation
- Programming Agility
- Huge range of predictive
analytics
Open source R
Revolution Analytics webinar, 2014-03-18
Image source: http://www.quantmod.com/gallery/

5. Poll Question
 What are you connecting to in order to
access your data? (please check all that
apply)
 A) RDBMS
 B) Spreadsheet
 C) Time Series / Tick DB
 D) non-relational / no-SQL database
Revolution Analytics webinar, 2014-03-18

6. Revolution Analytics is a visionary
Revolution Analytics webinar, 2014-03-18
Gartner magic quadrant
Advanced Analytics, 2014
LeadersChallengers
VisionariesOther players
Source: http://inside-bigdata.com/2014/02/25/gartner-reveals-magic-quadrant-advance-analytics/

7. Big Data In-memory bound Hybrid memory & disk
scalability
Operates on bigger volumes
& factors
Speed of
Analysis
Single threaded Parallel threading Shrinks analysis time
Enterprise
Readiness
Community support Commercial support Delivers full service
production support
Analytic Breadth
& Depth
5000+ innovative
analytic packages
Leverage open source
packages plus Big Data
ready packages
Supercharges R
Commercial
Viability
Risk of deployment of
open source
Commercial license Eliminate risk with open
source
Enhancing R for Enterprise deployment
Revolution Analytics webinar, 2014-03-18

8. Poll Question
 What is your usual hardware set up?
 A) Workstation
 B) Server
 C) Grid / Cluster
 D) GPU (graphical processing unit)
 E) Hadoop
Revolution Analytics webinar, 2014-03-18

9. Revolution R Enterprise
Revolution Analytics webinar, 2014-03-18
Language
Interpreter and
Standard R
Algorithm Suites
Development &
Deployment Tooling
Big Data Distributed
Execution Platform
R+CRAN
RevoR
DistributedR
ConnectR
ScaleR
DevelopR
Deploy
R
Revolution R Enterprise
 Big Data Big Analytics Ready
– Enterprise readiness
– High performance analytics
– Multi-platform architecture
– Data source integration
– Development tools, Deployment tools

10. ScaleR: high performance analytics
Revolution Analytics webinar, 2014-03-18
• Text formats
• SAS
• SPSS
• Teradata
• Netezza
• Greenplum
• Hadoop
• ODBC
• DataStep
• Clean
• Transform
• Refactor
• Sort
• De-duplicate
• Split
• Merge / Join
• Cube
• Summarise
• Significance
test
• Histogram
• Parallelise
(rxExec)
• Regression
• Logistic
Regression
• GLM’s
• Clustering
• Decision trees /
Forests
• Classification
trees
• Predict
• Residual
analysis
• ROC (cum
gain curve)
• Simulation
• Online
• Web API
• BI tools
• Export to
database
• Score in-
database
Import Pre-process Analyse Model Score Deploy
Distil / combine structured and unstructured
Build models that where legacy apps can’t
Iterate and innovate at speed
Operate on bigger data – work inside Hadoop with no M/R programming
More effective models = Better business decisions

11. R and empirical finance
 The CRAN Taskview (Empirical Finance)
 a rich source of recommendations for tools and packages in the field of
finance
 Topics include:
 Regression models
 Time series
 Finance
 Risk management
 Data and date management
 Other relevant task views:
 Econometrics
 Optimization
 Time Series
 Social sciences
 Robust statistical methods
Image source:
http://timelyportfolio.github.io/rCharts_time_series/history.html

12. Poll Question
 What is your preferred statistical
programming platform?
 A) MATLAB
 B) STATA
 C) SAS
 D) R / RRE
 E) NAG (Numerical Algorithm Group)
 F) C++, JAVA, PYTHON
Revolution Analytics webinar, 2014-03-18

13. FIND THE HIDDEN SIGNAL IN
MARKET DATA NOISE
Revolution Analytics webinar, 2014-03-18

14. Find the Hidden signal in market data noise
Director of Solutions at OneMarketData
Louis Lovas

15. © 2014 OneMarketData LLC1
ONE TICK®
Accelerating Quant Research and Trading
About OneMarketData, LLC
Founded in 2005, Profitable in 2008
 Self-Funded & Self-Directed.
 No venture capital / Cash-flow positive
Our Pedigree
 President and Founder, Leonid Frants
 Technology Built by Wall Street experts –
Leader in Financial Data Management Technology – OneTick™
 Comprehensive solution financial big data management
90+ Clients Worldwide
 Hedge Funds/Prop Traders, Banks & Brokers, Market Makers,
Marketplaces & Exchanges
Broad range of financial use cases
 Trading model back-testing & Quant Research,
Pricing Models, Pre/Post Trade TCA, …
Bloomberg

16. © 2014 OneMarketData LLC2
ONE TICK®
Accelerating Quant Research and Trading
About ONETICK
X
CEP & Database
Engine
Tick Server Clients
Programming APIs
C++ C# Java
Business Intelligence
Spotfire / Tableau
Visual Dashboards
Panopticon
Analytics
R language
Reporting
ODBC/SQL
Analytics
filter
enrich
aggregate
transform
correlate
Historical
Data
In-memory
Database
Reference
Data
Historical
Data
 Trading
Systems,
 Web Portals,
 Messaging
 Biz Intelligence,
 Programming
 100+ Built-In High Performance/High Precision Analytical Operators +
 Direct support for Corporate Actions , Corrections, Cancels, Symbol Maps,…
Historical
Data
Real-Time
Feeds
 Price & Volume Analytics, Historical Volatility, …
 Pricing modeling, Spread Trading signaling, Portfolio Analytics, …
Consolidated (Reuters,
Bloomberg, etc).
Exchange feeds.
ASCII/Binary/SQL sources
3rd party(NYSE TAQ,
CME, …)

17. © 2014 OneMarketData LLC3
ONE TICK®
Accelerating Quant Research and Trading
Delivering on timely business insights from market analysis
True price discovery, volume and trading patterns…
 Revealing unique observations and patterns
 Deriving precise analytics
 Market Data Quality is Key to outcomes
... result in improved trade & pricing models
x
Historical
Data
Reference
Data
Historical
Data Market Data + Analytics ( Equities, Options )  Pricing/Trading models
Markets…
ONETICK
Time Series Database and CEP
Market Analysis from
Streaming data
Equity Underliers – analytical models
Option pricing and risk models
… Predictive Models
Effective Market Analytics and Quantitative Research
Analytics

18. © 2014 OneMarketData LLC4
ONE TICK®
Accelerating Quant Research and Trading
Industry Advantages Where Your Success Counts
ONETICK Product Demonstration
Introduction to …
 OneTick Analytical Query Design
 Integration with R analytics
 Using OneTick and R for Options

19. QUESTION SESSION
Revolution Analytics webinar, 2014-03-18