An interactive approach to stochastic programming-based portfolio optimization

Koksalan M., TUNCER ŞAKAR C.

ANNALS OF OPERATIONS RESEARCH, cilt.245, ss.47-66, 2016 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 245
  • Basım Tarihi: 2016
  • Doi Numarası: 10.1007/s10479-014-1719-y
  • Dergi Adı: ANNALS OF OPERATIONS RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.47-66
  • Anahtar Kelimeler: Portfolio optimization, Stochastic programming, Interactive weighted Tchebycheff procedure, RISK, MODELS, SELECTION, PRICES, SYSTEM
  • Hacettepe Üniversitesi Adresli: Evet

Özet

We consider expected return, Conditional Value at Risk, and liquidity criteria in a multi-period portfolio optimization setting modeled by stochastic programming. We aim to identify a preferred solution of the decision maker (DM) by obtaining information on her/his preferences. We use a weighted Tchebycheff program to generate representative sets of solutions. Our approach models the stochasticity of market movements by stochastic programming. Working with multiple scenario trees, we construct confidence ellipsoids around representative solutions, and present them to the DM for her/him to make a choice. With each iteration of the approach, an increasingly concentrated set of ellipsoids around the DM's choices are generated. The procedure is demonstrated with tests performed using stocks traded on Borsa Istanbul.