고려할것

1. managing real-time and historical tick data
2. deriving trade and execution strategies
3. generating research and analytics
4. Calculate your customized or pre-configured analytics at the speed of the market
5. Develop market-making trading strategies
6. Perform real-time market monitoring and regulatory compliance checks
7. Build real-time transaction cost models to decrease execution costs
8. fault tolerance & stream persistence
9. "no tick loss" source mirroring
10. Operational robustness
11. strategy validation
12. Market useA measurable market profile (e.g., volatility) is detected in real-time
13. OMS와의 연계(ex. FIX or faster way)
14. calculate P&L in real-time throughout day
15. Analyze exponentially increasing volume of market data in milliseconds
16. picking the right one and having confidence that you are picking the right one
17. How can you get the best price and how can you prove that you did get the best price?  : run post-trade analysis
18. extensible persistence database
19. REAL-TIME CORRECTION AND FEEDBACK BASED ON POST-TRADE ANALYSIS 
20. TRANSACTION COST ANALYSYS
21. 용량이 컴팩트하고 검색속도를 더 빠르게 하기 위한 저장소
22. Queuing/Event 처리(republish)에는 RabbitMQ, AnyMQ , AnyEvent 등을 사용
23. 분석에는 R, Visualization/charting에는 Protovis( http://vis.stanford.edu/protovis/ )
24. 참조 : http://www.slideshare.net/clkao/trading-with-opensource-tools-two-years-later
25. json-rpc
26. Strategy : GeniusTrader, TradingSpring
27. Analysis : R, protovis
28. Haskell, Smalltalk
29. Kdb
30. http://www.marketcetera.com/ 
31. StreamBase, Marketcetera, Drool
32.   

*로이터는 다음과 같이 다양하고 방대한 데이터를 보유하고 있기 때문에 더욱 다양한 분석 및 전략이 가능할 것이다.
Velocity Analytics integrates a wealth of data repositories from Thomson Reuters, including tick data, corporate actions, exchange metadata, condition codes, direct feeds, etc., as well as other third party data sources (e.g., exchanges, brokers, and market data vendors) and internal proprietary firm data.
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