1. An AI Trading Strategy Platform

2.  Fast strategy simulations over large data sets  Dynamic back-testing without pre-programming setup ideas  Artificial intelligence to find trading methods

3.  Simple tools for data collection and storage  Platform for AI strategy discovery  Rich feature set for analysis

6. Week:Adam (x)Mike (y)Valentina (z) 1: Jan 7Project Idea 2: Jan 14Presentation, More Specific Specs for each part of Project, Learn C# 3: Jan 21 Coleman (layout) Randolph, Database SetupWinthorpe 4: Jan 28Randolph Coleman (layout) 5: Feb 4Coleman (layout) February 6 th : First Demo Day 6:Feb 11 Coleman (graphing) Randolph (database) Coleman (properties) 7: Feb 18Randolph (studies) 8: Feb 25 (spring break) 9: Mar 3Coleman (analysis)RandolphColeman (graphing) 10: Mar 10Demo prep March 15 th : Second Demo Day 11: Mar 17 Coleman (analysis)Randolph (AI engine)Coleman (analysis) 12: Marc 24 13: Mar 31Strategy finding 14: Apr 7Wine tasting April 11 th, Final Demo Day

7.  http://www.dvdbeaver.com/film2/DVDReviews33/trading_places_blu-ray.htm TD Ameritrade StrategyDesk TradersStudioTradingSolutionsMortimer Input specific strategies XXX EOD testing XXXX Neural networks XX AI optimization XX Time frames to <1min bars XXX Time frames to <5sec bars X Relative action indication X

8.  Artificial intelligence backtesting  Breadth of data, speed  Rich analysis

9.  Analyzing more components exponentially increases time  Data integrity and verification  Presenting strategies in meaningful context

10.  Simple, AI-backed strategy searching  Market inefficiency is (probably) exploitable  Find these inefficiencies on a high-frequency level