sito in aggiornamento
Responsabile scientifico: Prof. Michele Di Cristo
   Home page  Servizi bibliotecari di Ateneo  Risorse elettroniche di Ateneo  Accesso da remoto  Area login  Collezioni digitali di Dipartimento
 
 
 Biblioteca
 Contatti
 Regolamento della Biblioteca
 Patrimonio


 Servizi per gli utenti
 Consultazione
 Prestito
 Prestito intersistemico
Prestito interbibliotecario
 Richiesta articoli con NILDE
 Assistenza bibliografica
 Proposte di acquisto
 Collezioni Digitali: istruzioni per gli autori


 Servizi per le Biblioteche
 Prestito intersistemico
Prestito interbibliotecario
 Fornitura di articoli in copia


  
CodiceQDD 177
TitoloPassive Portfolio Management over a Finite Horizon with a Target Liquidation Value under Transaction Costs and Solvency Constraints
Data2014-04-22
Autore/iBaccarin, S.; Marazzina, D.
LinkDownload full text
AbstractWe consider a passive investor who divides his capital between two assets: a risk-free money market instrument and an index fund, or ETF, tracking a broad market index. We model the evolution of the market index by a lognormal diffusion. The agent faces both fixed and proportional transaction costs and solvency constraints. The objective is to maximize the expected utility from the portfolio liquidation at a fixed horizon but if the portfolio reaches a pre-set target value then the position in the risky asset is liquidated. The model is formulated as a parabolic impulse control problem and we characterize the value function as the unique constrained viscosity solution of the associated quasi-variational inequality. We show the existence of an impulse policy which is arbitrarily close to the optimal one by reducing the model to a sequence of iterated optimal stopping problems. The value function and the quasi-optimal policy are computed numerically by an iterative finite element discretization technique. We present extended numerical results in the case of a CRRA utility function, showing the non-stationary shape of the optimal strategy and how it varies with respect to the model parameters. The numerical experiments reveal that, even with small transaction costs and distant horizons, the optimal strategy is essentially a buy-and-hold trading strategy where the agent recalibrates his portfolio very few times.

Dipartimento di Matematica