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American Century (Revolution Analytics Customer Day)
American Century (Revolution Analytics Customer Day)
American Century (Revolution Analytics Customer Day)
American Century (Revolution Analytics Customer Day)
American Century (Revolution Analytics Customer Day)
American Century (Revolution Analytics Customer Day)
American Century (Revolution Analytics Customer Day)
American Century (Revolution Analytics Customer Day)
American Century (Revolution Analytics Customer Day)
American Century (Revolution Analytics Customer Day)
American Century (Revolution Analytics Customer Day)
American Century (Revolution Analytics Customer Day)
American Century (Revolution Analytics Customer Day)
American Century (Revolution Analytics Customer Day)
American Century (Revolution Analytics Customer Day)
American Century (Revolution Analytics Customer Day)
American Century (Revolution Analytics Customer Day)
American Century (Revolution Analytics Customer Day)
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American Century (Revolution Analytics Customer Day)

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Presenters: …

Presenters:
Tal Sansani, CFA (Quantitative Analyst / Portfolio Manager, American Century Investments)
Sampath Thummati (IT Manager / Advisor, American Century Investments)
Presentation Date: February 26, 2013

This presentation is about how American Century Investments revamped their research and production platforms with Revolution R Enterprise.

Published in: Technology
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  • 1. Revolution Analytics Customer DayAmerican Century InvestmentsFebruary 26, 2013Tal Sansani, CFAQuantitative AnalystPortfolio ManagerSampath ThummatiIT Manager/Advisor
  • 2. American Century Investments: Company Overview American Century Investments | Kansas City, MO Notes – Founded in 1958 – $125 billion assets under management* – One of the 20 largest mutual fund companies Quantitative Equity Group | Mountain View, CA – $8.5 billion in assets under management across 22 mutual funds and separate accounts – This group takes an objective, systematic, and disciplined investment approach – Combines quantitative stock-selection models with portfolio optimization procedures, to systematically determine which stocks to buy or sell. – Fully Transparent Process: Stock-selection models are founded on economically sensible ideas and implemented using carefully calibrated statistical methods. The Team – 10 experienced investment professionals with backgrounds in finance, economics, accounting, mathematics, and statistics. – Supported by a team of 4 IT professionals 2
  • 3. About Me: Tal Sansani Quantitative Research Analyst & Portfolio Manager Notes With American Century Investments’ Quantitative Research Team for 7+ years. Research Responsibilities – Research and develop stock-selection signals (alpha) that systematically inform our funds on which names to buy or sell. – Research and develop portfolio construction techniques that help our funds mitigate unintended risks and exposures. – Monitor the performance dynamics of our models and asset positions with proprietary analytics and attribution dashboards – Currently putting research projects aside (briefly) to revamp our research and production platforms:  Helping lead the design and development of an end-to-end quantitative research platform, built atop an internal/collaborative R-package rACI 3
  • 4. Revamping our Research and Production Platforms with RevoR In 2012, after years of pain and suffering, we initiated a move away from our existing infrastructure… Notes Extensive limitations with our pre-existing platform: – A disparate blend of CLOSED 3rd party financial software – Functionally limited and difficult to customize – Restricted to specific data vendors/sources/asset-classes – Difficulty streamlining multi-dimensional processes – Cumbersome and costly In-house Solution: a streamlined, scalable end-to-end quantitative platform  Data Acquisition, Data Cleaning & Model Building – RevoR w/ SQL, populated with variety of data-sources, and proprietary feeds  Portfolio Optimization and Strategy Simulation – RevoR w/ powerful 3rd Party Optimization API  Model Analytics & Performance Attribution – RevoR w/ tableau (and existing R graphics/publishing packages)  Production Processes – Controlled environment, deployment 4
  • 5. rACI: A growing, multi-team, collaborative R-package withinAmerican Century InvestmentsData Feeds Notes Market Data from Thomson American Century Quant Additional 3rd Party Data Reuters (QA-Direct) Proprietary Data Vendors rACI Package (w/ RevoR) Data Acquisition Function Library Model Building Function Library Portfolio Optimization and Simulation API Analytics Function Library Live Analytics PRODUCTION MODEL GENERATION AND TRADING PROCESSES
  • 6. Immediate Research Benefits Gained By Infrastructure Revamp Why Research likes RevoR? Notes – We love R, and all the benefits of the fastest growing open-source statistical programming language, but with $8 billion on the line, we sought a trusted enterprise solution for research and production processes. – Optimized performance: We’ve observed our simulations to be 20x faster than with base-R, vastly improving research turnaround Immediate Results: New RevoR-driven solution is a huge upgrade on our pre-existing platform – With improved analytics and streamlined research processes, we can better understand the behavior of our models and more quickly adapt to material market changes. – Decoupling our investment processes from closed 3rd-party vendors has allowed us to combine and analyze more types of financial assets (not just stocks), leading to new investment products (combining credit instruments, options, commodities, etc.) – We can now leverage all the rapidly evolving libraries of R in our research, leading to more proprietary and cutting-edge quantitative models. 6
  • 7. Example 1: Streamlined Research Simulations/DiagnosticsA 3-Step Process: Notes1) Construct a stock-selection signal and submit it to the database2) Run customized simulations and pre-packaged analytics3) Visit the Quant Research Portal for the results 7
  • 8. Example 2: Opening up Our Research With R’s Rapidly Evolving Open-SourceLibrary By integrating existing financial Notes The Economic datasets with new/unique Ecosystem information, while leveraging a variety of packages available in R, our group can explore new avenues of research. In this example, we use revenues between customers and suppliers, to explore how information travels through an economic network. Note: R’s igraph package was used for much of the internal analysis, while Gephi was used to construct the chart you see on the right. 8
  • 9. About me: Sampath Thummati Responsibilities Notes – Architect and design investment management systems to support quantitative research and portfolio management. – Production support for quant model generation and other investment management processes. – Currently leading the implementation of quant roadmap to build efficient cross- asset class research platform for alpha generation, back-testing and analytics. R Experience – R-user for couple of years now – Integrating applications interfacing with R code  Database, Java Components, Batch Scheduling System and Custom applications – Building configuration functions  Error handling  Application loggingFOR INTERNAL USE ONLY 9
  • 10. Technology’s Role in Innovative Quantitative InvestmentManagement ACCESS TO UNIQUE DATA-SETS Notes – New, innovative investment ideas are the life-blood of our group, and by extension, so too is our ability to process new information. It’s absolutely critical for us to rapidly adapt to complex data-sets and new technologies. COMPUTATIONAL CAPACITY – Controlled risk management and modern portfolio construction techniques require sophisticated optimization toolsets. CUSTOMIZED ANALYTICS – Building proprietary models requires proprietary analytics/feedback into the model ROBUST DATA FORENSICS – Proprietary data quality tools ensure inputs into trading processes go through a battery of tests INDUSTRIAL STRENGTH PRODUCTION PROCESSESFOR INTERNAL USE ONLY 10
  • 11. Immediate Production Benefits Gained By Infrastructure Revamp Why Production likes RevoR? Notes – Open-source tools generally avoided in large-scale money management  Revo support model  Package verification and certification eliminates risks of malicious code – Optimized performance  Enables us to run overnight production processes in time for next business day – Business and production friendly programming language  Research and production now share a common language, reducing risk of errors in code translation  Reduced time to production implementation 11
  • 12. Research-to-Production Transition Notes 12
  • 13. What we did on the production side? Error handling Notes – Intensive ‘try-catch’ use – Storing images at the point of failure Robust logging procedures – Easy to use calls to log – Rolling logs Setup batch jobs – Use of Rscript – Handling return code 13
  • 14. Example Try-Catch Example Notes 14
  • 15. Example Batch example Notes 15
  • 16. What we did on the production side? Interface with dependency management system Notes Controlled processes to stabilize production environment – Third-party packages – Deploying application and modified packages – Use of Rprofile for enterprise settings 16
  • 17. Current Status We are about 75% complete with our transition to RevoR Notes There is growing interest from other parts of the company to contribute and employ rACI So far, we haven’t experienced any setbacks and are very satisfied with what has been accomplished with RevoR 17
  • 18. Q&A Notes Sampath Thummati st8@americancentury.com Tal Sansani t4s@americancentury.com 18

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