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31 Broadway
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Dry Ridge, Ky 41035

859-824-3335 (Office)
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Links 824-3335 City of Dry Ridge 824-9158 Dry Ridge Fire Department 824-9403 Grant County Animal Shelter 823-5091 Grant County Attorney 824-3322

Case study: Portfolio Optimization with Expectiles

Maximize Avg_g (maximizing the expected return of financial instruments)
subject to
expectile —————————————————————

# of Variables # of Scenarios Objective Value Solving Time, PC 3.14GHz (sec)
Dataset 1 4 10000 0.00094986 0.06
Environments
Run-File Problem Statement Data Solution
Matlab Toolbox Data
Matlab Matlab Code Data
R R Code Data

PROBLEM 2: minimizing expectile risk subject to bounded from below expected returns

Minimize expectile (minimize negative expectile risk of the portfolio)
subject to
Avg_g >= Const1 (constraint on the expected return of financial instruments)
Linear = Const2 (budget constraint)
Box constraints (box constraints for individual positions)
——————————————————————–
Avg_g = Average Gain
Box constraints = constraints on individual decision variables
——————————————————————–

# of Variables # of Scenarios Objective Value Solving Time, PC 3.14GHz (sec)
Dataset 1 4 10000 0.02447960 0.01
Environments
Run-File Problem Statement Data Solution
Matlab Toolbox Data
Matlab Matlab Code Data
R R Code Data

PROBLEM 3: maximizing the expected return subject to bounded negative expectile risk

Maximize Avg_g (maximizing the expected return of financial instruments)
subject to
expectile = Const1 (constraint on the expected return of financial instruments)
Linear = Const2 (budget constraint)
Box constraints (box constraints for individual positions)
——————————————————————–
Avg_g = Average Gain
Box constraints = constraints on individual decision variables
——————————————————————–

Case study: Portfolio Optimization with Expectiles Maximize Avg_g (maximizing the expected return of financial instruments) subject to expectile ————————————————————— # of Variables