Portfolio Optimization: A Technical Perspective - GAMS

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26 26 Agenda Introduction Introduction Mathematical Optimization in Finance An illustrative Example: The Mean Variance Model Advanced Portfolio Optimization Models Grid Computing
27 27 Grid Computing loop(pp, #calculate efficient frontier r.fx = minr + (maxr-minr)/(card(pp)+1)*ord(pp); solve var minimizing v using miqcp; rep(pp,'ret') =r.l;rep(pp,'var') = v.l;repx(pp,i)= x.l(i); ); Imagine… .. you have to solve 1.000’s of independent scenarios.. .. and you can do this very rapidly for little additional money… .. without having to do lots of cumbersome programming work.. Grid Computing
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: 25 25 More Theory and Templates The
Page 29 and 30: 29 29 Advantages of Grid Computing
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

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