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

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

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

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

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

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

E-INVESTORS First Portfolio

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

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

E-INVESTORS Last Portfolio

E-INVESTORS Portfolio management over time

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

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

E-INVESTORS  Best Portfolio: diversified Covariance matrix

E-INVESTORS Excel Solver: Step by step

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

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

E-INVESTORS Surprise 1-Mad Money Outcome

E-INVESTORS Surprise 2 - Vice vs Virtue

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

E-INVESTORS Vice: Virtue: WMT: 2, NOC: -1, KBR: -1, AGP:-4, WBS: PLL: 2, , Surprise 2 - Vice vs Virtue Outcome

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

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

E-INVESTORS Neural Networks Result rule WBS

E-INVESTORS Neural Networks Result PerformancePRC MSE NMSE MAE Min Abs Error Max Abs Error r Predicted Volatility well, but not magnitude of changes and price level WBS

E-INVESTORS Neural Networks Result AGP Best NetworksTrainingCross Validation Epoch #501 Minimum MSE Final MSE

E-INVESTORS Neural Networks Result Predicted Price Level better, not Volatility. AGP PerformancePRC MSE NMSE MAE Min Abs Error Max Abs Error r Reason: Input Factors

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

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

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)

E-INVESTORS Glitch

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

E-INVESTORS Last Portfolio

E-INVESTORS Thank you ! Questions