Portfolio Optimization: A Technical Perspective - GAMS

More documents

Recommendations

Info

28 28 What is Grid Computing? A pool of connected computers managed and available as a common computing resource • Effective sharing of CPU power • Massive parallel task execution • Scheduler handles management tasks • E.g. Condor, Sun Grid Engine, Globus • Can be rented or owned in common • Licensing & security issues
29 29 Advantages of Grid Computing • Solve a certain number of scenarios faster, e.g: – sequential: 50 hours – parallel (200 CPUs): ~15 minutes Cost is $100 (2$ CPU/h) • Get better results by running more scenarios*: * http://www.tc.cornell.edu/NR/shared/Presentations/24Feb04.Garp.pdf
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: 27 27 Grid Computing loop(pp, #calc
Page 31 and 32: 31 31 Simple Serial Solve Loop Loop
Page 33 and 34: 33 33 Results for 4096 MIPS on Cond
Page 35 and 36: 35 35 The End Thank you! … Questi

Portfolio Optimization: A Technical Perspective - GAMS

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?