Portfolio Optimization: A Technical Perspective - GAMS

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32 32 GRID Specific Enhancements 1. Submission of jobs 2. “Grid Middleware” – Distribution of jobs – Job execution 3. Collection of solutions 4. Processing of results
33 33 Results for 4096 MIPS on Condor Grid • Submission started Jan 11,16:00 • All jobs submitted by Jan 11, 23:00 • All jobs returned by Jan 12, 12:40 – 20 hours wall time, 5000 CPU hours – Peak number of CPU’s: 500 Talk: Thursday, 08:30 “Chemie-Hörsaal 1”
Page 1 and 2: 1 1 Portfolio Optimization: A Techn
Page 3 and 4: 3 3 Agenda Introduction Mathematica
Page 5 and 6: 5 5 Agenda Introduction Mathematica
Page 7 and 8: 7 7 Portfolio Optimization Models -
Page 9 and 10: 9 9 Modeling Approaches - Programmi
Page 11 and 12: 11 11 MV Model Algebra Variance of
Page 13 and 14: 13 13 Modeling Issues Basic MV-Mode
Page 15 and 16: 15 15 More Complex Business Rules R
Page 17 and 18: 17 17 GAMS Formulation Variables xi
Page 19 and 20: 19 19 Efficient Frontier and Portfo
Page 21 and 22: 21 21 Stochastic Programming (SP) S
Page 23 and 24: 23 23 Challenges Deterministic equi
Page 25 and 26: 25 25 More Theory and Templates The
Page 27 and 28: 27 27 Grid Computing loop(pp, #calc
Page 29 and 30: 29 29 Advantages of Grid Computing
Page 31: 31 31 Simple Serial Solve Loop Loop
Page 35 and 36: 35 35 The End Thank you! … Questi

Portfolio Optimization: A Technical Perspective - GAMS

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