Execution algorithms refer to the algorithms used during the execution process in order to transact the purchase/sale once the trading decision has been made. They are designed to reduce market impact and minimize execution costs.
Products are getting increasingly correlated on different exchanges or across assets, resulting in skyrocketing market data rates which increase the cost and complexity of data capture, processing, and storage. It is now even more critical to find data and tools that work across all these issues while saving cost, hence the demand for normalized data from multiple sources.
High-performance, low-latency technology are becoming a basic necessity for the ways in which most trading firms assess opportunities, execute trades and manage risk.

HOW VELOCITY ANALYTICS MEETS THESE NEEDS
Thomson Reuters enterprise Platform for Velocity Analytics helps clients with low latency market data collection, normalization and analysis. It fixes the problem of overloaded algorithm trading engines, stores massive amounts of data with instantaneous retrieval, and collects and analyzes full order books including consolidation of order books from multiple venues. data heavy computing can be offloaded to Velocity Analytics and the results sent to the algo trading engine.
Velocity Analytics is easy to manage and maintain, as well as scalable to keep up with ever-increasing load. It is easy to build interfaces between Velocity Analytics and EMS/OMS systems. It allows for flexible summarization and publishing and rich pre-programmed analytics (VWAP, TWAP, etc.). clients can add custom analytics into the server using Velocity Analytics plug-in framework. the system also supports corporate actions, cancellations and corrections. 

MARKET USE
If you are a sell-side algo execution desk or if you are actually looking to develop your own algorithms on the buy-side, it is very important to make sure that you pick the right algorithms to most effectively fill your orders. so once an order has been decided or once you have made a buy or sell decision, how do you go about executing that order?  
that’s where execution algorithms come in. there are hundreds and hundreds of different types of algorithms; picking the right one and having confidence that you are picking the right one is very important. you can marry Velocity Analytics with our data in order to ensure that you are picking the one that meets the market conditions.
For the buy-side, it’s important from an algo execution perspective to be able to compare and contrast the different algorithms that are being provided by the sell-side, therefore having the right tools to conduct this testing on your own is a key advantage. 

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Posted by karlsen
HigH Frequency Data ManageMent and Analytics

실시간, 히스토리컬 tick 데이터를 관리
trade and execution 전략 수행
research and analytics
시장 속도에 맞추어 미리 설정된 분석을 계산할 수 있음
=> 시장 상황의 변화에 대응할 수 있으며, 전략이 효율적으로 수행될 수 있도록 함

Velocity Analytics를 이용하여 
market-making trading strategies을 개발할수 있으며
실시간 시장 모니터링, 규제 컴플라이언스 체크를 수행하고
실시간 트랜젝션 코스트 모델을 만들어 execution costs를 줄일 수 있다.

글로벌 헤지펀드, proprietary arbitrage trading desks, brokerage firms, exchanges, regulatory agencies, third party transaction cost analysis firms, algo execution desks, and many other types of businesses in the trading community가 사용한다.

VA는 톰슨 로이터의 데이터 저장소에 접근가능하다: 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
=> 모든 데이터 분석의 표준화가 가능하다

Low Latent, Best in Quality execution capabilities 
Velocity Analytics seamlessly integrates into your trading environment, supporting real-time distribution of streaming trade signals to multiple in-house or third party applications simultaneously. For example, Velocity Analytics can generate trade signals to your order Management system (OMS), facilitating program trading based on algorithmic strategies, so you can respond very quickly to short-lived market discrepancies and opportunities, and then 
accept executed trade data or other types of derived data back into the platform.

Examples of smarter, faster Execution:
• A new strategy is validated in Velocity Analytics before being deployed in production
• A measurable market profile (e.g., volatility) is detected in real-time by Velocity Analytics, triggering an alert to the OMS/execution platform to deploy a particular strategy that is typically 
successful in a volatile market
• A proprietary benchmark developed in Velocity Analytics is matched by realtime market data; it sends a Fix message directly to your OMS, which then forwards the Fix message for execution

-------------------------
DATA integration
The right technology for managing high velocity executions must not only be fast and reliable but also seamless in integrating different types of content sets. Maintaining data quality throughout the trading lifecycle is a major hurdle. Velocity Analytics is your strategic solution for bringing together multiple types of datasets (e.g., tick data and corporate actions data) for real-time and historical analytics, thereby giving you a complete time series for research and signal generation.

streaming global cross-asset data – real-time feeds, corporate actions and tick History: 

Thomson Reuters has the best-in-class global cross-asset content. our ultra-low latent data feeds, tick history and corporate actions reference data are brought together with the Velocity Analytics solution.
our solution enables you to run quantitative research and analysis on deep history, coupled with corporate action reference data to indentify market anomalies or correlations that you can leverage. We bring together historical and real-time content to offer a comprehensive platform for quantitative trading and transaction cost analysis.
 
internal and third party data sources:
 
Many of our customers are already using Thomson Reuters enterprise platform for Real-Time. it is an ultra-low latency market data integration platform providing resilience, permissioning and publishing infrastructure to banks, brokers and hedge funds worldwide. Velocity Analytics integrates with the enterprise platform to access internal and third party data. Thomson Reuters enterprise platform for Real-Time permissioning also enables tracking and compliance. Velocity Analytics leverages the enterprise platform distribution to publish streaming analytics to multiple downstream applications.

Hosted offering
Thomson Reuters has hosted data centers around the world. Velocity Analytics can be hosted in any of these data centers as a dedicated service and add-on to your firm’s infrastructure. connectivity to any of our real-time low latency direct exchange feeds and historical tick and reference data can be completely managed by Thomson Reuters.

Testing Algorithms And Third party integration
Trade and quote history from the Thomson Reuters Tick History service is integrated into Velocity Analytics, complementing streaming market data. This creates comprehensive market views, allowing you to develop and test strategies without being slowed down by querying traditional databases that are not optimized for market data.
our platform allows historical trade data to be queried and analyzed ‘on the fly’, uncovering historical trends. using these trends, you can build trading strategies that react to discrepancies in current markets. Buildingblock analytics allow you to get started or quickly create your own proprietary approach.
With accurate market data captured and easily accessible, you can build new algorithmic trading strategies, choosing from our library of application programming interfaces (Apis) and scripting. in addition, Velocity Analytics provides ODBC and JDBC connectivity to allow integration with statistical packages such as excel, MATLAB and s-PLUS.
And with easy integration to third party or proprietary customer-developed analytics, you can backtest these strategies as well.
-써드파티와의 연계는 고려하지 않아도 될듯

DATABASE CAPABILITIES
• capture and store every tick of data – global cross-asset class
• capture streaming real-time ticks and integrate historical ticks
• Lose zero ticks with fully resilient fault tolerant system
• store and apply corporate actions 
• store raw data formats and derived data analytics
• Apply data compression to reduce total cost of ownership
• enable faster time to production with easy installation
 
CUSTOM AND PRE-BUILT ANALYTICS
• send trade alerts to order management systems and execution platforms
• publish streaming analytics such as Volume Weighted Average price (VWAP) or TWAP to trading desks and applications
• consolidate multiple venues to create custom National Best Bid Offer (NBBO) data
• Leverage order book analytics
• calculate P&L in real-time throughout day
• generate underlying asset prices intraday
• Query historical data against real-time data to simulate new trading strategies
• plug into existing content, analytics and execution platforms 

INTEGRATED PLATFORM
• Analyze exponentially increasing volume of market data in milliseconds
• ensure accuracy and compatibility with Thomson Reuters or hundreds of other third party data feeds
• plug in Thomson Reuters Tick History for global cross-asset, full tick data back to 1996
• plug in corporate actions from Thomson Reuters or other third party sources
• Leverage Thomson Reuters enterprise platform for Real-Time for content integration, permissioning and publishing streaming analytics
• easily process cancellations and corrections, symbol maps, futures rolls, etc. 


PRIMARY BUSINESS USE CASES
• Alpha generation and Arbitrage
• Transaction cost Analysis
• Algorithmic execution
• compliance and surveillance

THOMSON REUTERS 24X7 SERVICE
Thomson Reuters global presence means that our support is world-class. Thomson Reuters global service centers can meet your 24x7 support needs, and Thomson Reuters account teams are local and available to respond rapidly to any of your concerns. We can provide one-stop problem resolution for Velocity Analytics, as well as the associated data and platforms.

 













 

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Posted by karlsen

2011. 8. 10. 10:25 Market Data

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.
=> 어떠한 우위를 점할 수 있을까?


 

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Posted by karlsen

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Pricing, hedging, risk-managing a complex derivative product
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