(!****************************************************** Mosel Example Problems ====================== file foliolps.mos ````````````````` Modeling a small LP problem to perform portfolio optimization. -- Using string indices -- (c) 2008 Fair Isaac Corporation author: S.Heipcke, Mar. 2006 *******************************************************!) model "Portfolio optimization with LP" uses "mmxprs" declarations ! Set of shares SHARES = {"treasury", "hardware", "theater", "telecom", "brewery", "highways", "cars", "bank", "software", "electronics"} ! Set of high-risk values among shares RISK = {"hardware", "theater", "telecom", "software", "electronics"} ! Set of shares issued in N.-America NA = {"treasury", "hardware", "theater", "telecom"} RET: array(SHARES) of real ! Estimated return in investment frac: array(SHARES) of mpvar ! Fraction of capital used per share end-declarations RET::(["treasury", "hardware", "theater", "telecom", "brewery", "highways", "cars", "bank", "software", "electronics"])[5,17,26,12,8,9,7,6,31,21] ! Objective: total return Return:= sum(s in SHARES) RET(s)*frac(s) ! Limit the percentage of high-risk values sum(s in RISK) frac(s) <= 1/3 ! Minimum amount of North-American values sum(s in NA) frac(s) >= 0,5 ! Spend all the capital sum(s in SHARES) frac(s) = 1 ! Upper bounds on the investment per share forall(s in SHARES) frac(s) <= 0,3 ! Solve the problem maximize(Return) ! Solution printing writeln("Total return: ", getobjval) forall(s in SHARES) writeln(s, ": ", getsol(frac(s))*100, "%") end-model