1. IT in IT in Financial Markets IT in Financial Markets IT in Financial Markets E-investors Ali Javed Adrienne Fernandez Ekaterina Ianovskaia

2. E-INVESTORS Agenda  Top-down approach to security analysis  First portfolio vs. last portfolio  Tools used  Surprise 1  Surprise 2  Neural Networks  Challenges and risk mitigation  Lessons learned

3. E-INVESTORS Introduction  Modern Portfolio Theory  Don’t put all your eggs in the same basket!  use of diversification strategy  diversify across industries and companies  choose large market capitalization stocks  Avoid risks

4. E-INVESTORS Strategy: Top-down approach to security analysis Step 1: Economic Analysis Step 2: Industry Analysis Step 3: Fundamental analysis

5. E-INVESTORS Step 1: Economic Analysis  Research and data mining:  Online  Offline  TV  Newspapers  discussions with professors  Popularity hypothesis by Keynes: Find what stocks will be popular among other investors  Community based social investing websites like Zecco  Findings:  High economic instability  Don’t invest in Japan  U.S. low dollar stimulates exports and economic growth

6. E-INVESTORS Step 2: Industry Analysis Historical trends show that the most performing current industries are:  Information Technology  Financials  Energy  Industrials  Health care  Consumer Services Fidelity.com

7. E-INVESTORS First Portfolio

8. E-INVESTORS Step 3: Fundamental Analysis  Teamwork: Search different websites, use Google docs to post findings  Technical analysis: look at stock patterns and analyzing the potential of growth of these stocks.  Choose many stocks performing better than the benchmark S&P500 over the past  To diversify some of the risk, choose several stocks with more steady returns, which are far less volatile  High earnings per share  Mixed high and low betas

9. E-INVESTORS Stock Sector and Industry Target Investment Amount QuantityWeights 1CBSConsumer Services: Media Conglomerates294,642.86 12,1007% 2SIX Six FlagsConsumer services: movies/entertainment294,642.86 4,7187% 3 HMIN Home Inns & Hotels Management Inc, ADR Consumer services: Hotels/Resorts/Cruiselines, ADR 200000 5,3224% 4AAPLElectronic tech computer processing hardware339285.7143 9448% 5LMT Lockheed MartinElectronic tech: aerospace and defence339285.7143 4,2008% 6RIMMElectronic tech: telecom eqiupment339285.7143 4,9578% 7CVX ChevronEnergy Minerals: integrated oil517,857.14 4,97012% 8 ALRN American Learning Corp Finance: insurance, brokers, services18,073.76 6,3640% 9AXP American ExpressFinancial conglomerates: Finance428,571.43 9,67410% 10GS Goldman Sachs Group IncFinance: Investment Banks/Brokers410,497.67 2,4969% 11JAZZ PharmaceuticalsHealth technology: pharmaceuticals196,428.57 7,4804% 12PFE PfizerHealth technology: pharmaceuticals196,428.57 9,9364% 13NVS NovartisHealth technology: pharmaceuticals196,428.57 3,4364% 14EP El Paso corpIndustrial services: oil and gaz214,285.71 11,7105% 153M Producer Manufacturing : Industrial conglomerates 214,285.71 2,3095% 16TTM TATA MotorsProducer manufacturing: Machinery, ADR250,000.00 9,5716% 17ALU Alcatel Lucent SATelecom equipment, Electronic technology, ADR50,000.00 11,4421% First Portfolio

10. E-INVESTORS Last Portfolio

11. E-INVESTORS Portfolio management over time

12. E-INVESTORS Tools used  CompuStat  CRSP  Data mining, stock charts  CAPM  Matlab  Most useful tool : Excel solver

13. E-INVESTORS  Step 1 : Define what we need to find:  maximum return  minimum variance  Step 2 : Prepare the Spreadsheet  Data and Constraints  Step 3 : Solve the model with the Solver  Find optimal portfolio Excel Solver: Step by step

14. E-INVESTORS  Best Portfolio: diversified Covariance matrix

15. E-INVESTORS Excel Solver: Step by step

16. E-INVESTORS Surprise 1-Mad Money  Followed recommendations  Chose stocks according to our analysis  Diversification:  According to days of recommendation  Outcome: positive!

17. E-INVESTORS Surprise 1-Mad Money Outcome SKS : Monthly SKS : DailyORCL : Daily ORCL : MonthlyMCD : Monthly MCD : Daily

18. E-INVESTORS Surprise 1-Mad Money Outcome

19. E-INVESTORS Surprise 2 - Vice vs Virtue

20. E-INVESTORS Surprise 2 - Vice vs Virtue Outcome AGP: -$4,395.47 WBS: +$487.20PLL: +$2,844.60 WMT: +$2,740.75NOC: -$1,143.84KBR: -$1,255.68

21. E-INVESTORS Vice: Virtue: WMT: 2,740.75 NOC: -1,143.84 KBR: -1,255.68 341.23 AGP:-4,395.47 WBS: 487.2 PLL: 2,844.60 -1,063.67 Surprise 2 - Vice vs Virtue Outcome

22. E-INVESTORS Neural Networks  Trial version : Limited number of inputs

23. E-INVESTORS Neural Networks in stock price forecast  Data: 250 observations (1 year period) of WBS daily stock prices and market indicators from Compustat  Indicators:  Fundamental: Returns, Volume  Technical: Moving averages (30) (90)  Market Index: S&P 500 WBS

24. E-INVESTORS Neural Networks Result 50-50-50 rule WBS

25. E-INVESTORS Neural Networks Result PerformancePRC MSE1.961558161 NMSE2.969163734 MAE1.274166299 Min Abs Error0.144731369 Max Abs Error2.386955525 r-0.048827027 Predicted Volatility well, but not magnitude of changes and price level WBS

26. E-INVESTORS Neural Networks Result AGP Best NetworksTrainingCross Validation Epoch #501 Minimum MSE0.0305597980.442329399 Final MSE0.0305597980.69339859

27. E-INVESTORS Neural Networks Result Predicted Price Level better, not Volatility. AGP PerformancePRC MSE68.69420555 NMSE39.35646708 MAE8.182435557 Min Abs Error5.198936887 Max Abs Error10.70313759 r0.052262509 Reason: Input Factors

28. E-INVESTORS Neural Networks Result Not all factors that affect one stock affect the other Bank Prime Loan Rate Sensitivity To The Market

29. E-INVESTORS Event Analysis  We did Event Analysis using Eventus  Walmart dividend increase announcement for April 1 st  Assuming markets are efficient or semi-efficient  Traders can react to news faster than we can.  Was not useful in picking stocks

30. E-INVESTORS Challenges and risk mitigation  Difficulty to use some portfolio analysis tools (Matlab)  Difficulty to understand tools (Neuro Solutions)  Selling Stocks (Glitches, time limit)  Availability issues for our team (Google)

31. E-INVESTORS Glitch

32. E-INVESTORS Lessons learned  New stock portfolio investment tools  Never use one tool in isolation  Market is quicker than we are  Instinct Vs Hope  Timing is Key  Market Efficiency? Eventus Vs Mad Money  Detailed Analysis = Computer Power

33. E-INVESTORS Last Portfolio

34. E-INVESTORS Thank you ! Questions