PORTFOLIO OPTIMIZATION IN MEAN VARIANCE AND VARIANCE WITH SKEWNESS RISK MEASURES USING SPIRAL OPTIMIZATION METHOD
This thesis discusses about portfolio optimization using two different risk measures, in mean variance model by Markowitz and variance with skewness model by Tun-Jen Chang et.al. In the mean variance model Markowitz assumed that the distribution of portfolio return is multivariate normal, but in...
Saved in:
| Main Author: | |
|---|---|
| Format: | Theses |
| Language: | Indonesia |
| Subjects: | |
| Online Access: | https://digilib.itb.ac.id/gdl/view/32162 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | This thesis discusses about portfolio optimization using two different risk
measures, in mean variance model by Markowitz and variance with skewness
model by Tun-Jen Chang et.al. In the mean variance model Markowitz assumed
that the distribution of portfolio return is multivariate normal, but in reality the
return of portfolio not follow a multivariate normal distribution and the return has
a degree of skewness. The constraints to construct optimal portfolio in this thesis
are: (1) buy-in-threshold is a constraint to restrict the minimum proportion in
portfolio, (2) cardinlity is a constraint to resctrict the number of assets included in
portfolio, (3) roundlot is a constraint which required investors only transacting in
lots. For the first step, this thesis will discuss about single-objectif (involving an
objective function) portfolio optimization with risk as the objective function and
return be given or return as the objective function and risk be given. After that the
problem developed into a multi-objective (involving two objective function)
optimization problem with risk of portfolio as small as possible and return of
portfolio as large as possible. Portfolio optimization problems will be solved
using spiral method developed by Tamura-Yasuda in 2011. |
|---|