18Mar14 Find the Hidden Signal in Market Data Noise Webinar

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18Mar14 Find the Hidden Signal in Market Data Noise Webinar

  1. 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. 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. 3. THE R PROJECT AND FINANCIAL APPLICATIONS Revolution Analytics webinar, 2014-03-18
  4. 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. 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. 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. 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. 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. 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. 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. 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. 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. 13. FIND THE HIDDEN SIGNAL IN MARKET DATA NOISE Revolution Analytics webinar, 2014-03-18
  14. 14. Find the Hidden signal in market data noise Director of Solutions at OneMarketData Louis Lovas
  15. 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. 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. 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. 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. 19. QUESTION SESSION Revolution Analytics webinar, 2014-03-18

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