This is a small graphical program that plots the efficient frontier of Markowitz' portfolio selection problem with the two objectives return and risk. More...

Variables
str	markowitz.GAMS_MODEL

sys	markowitz.sys_dir = sys.argv[1] if len(sys.argv) > 1 else None

GamsWorkspace	markowitz.ws = GamsWorkspace(system_directory=sys_dir)

GamsWorkspace	markowitz.job = ws.add_job_from_string(GAMS_MODEL)

GamsWorkspace	markowitz.opt = ws.add_options()

	markowitz.all_model_types

GamsWorkspace	markowitz.cp = ws.add_checkpoint()

GamsWorkspace	markowitz.mi = cp.add_modelinstance()

GamsWorkspace	markowitz.l = mi.sync_db.add_parameter("lambda", 0, "")

list	markowitz.data_points = []

	markowitz.value

GamsWorkspace	markowitz.min_ret = mi.sync_db["ret"].first_record().level

GamsWorkspace	markowitz.max_ret = mi.sync_db["ret"].first_record().level

float	markowitz.gap = 0.02

list	markowitz.intervals = [((0.0, min_ret), (1.0, max_ret))]

list	markowitz.i = intervals.pop()

	markowitz.min_l

	markowitz.max_l

tuple	markowitz.l_val = (min_l + max_l) / 2

GamsWorkspace	markowitz.cur_ret = mi.sync_db["ret"].first_record().level

	markowitz.key

list	markowitz.ret = [x[0] for x in data_points]

list	markowitz.var = [x[1] for x in data_points]

	markowitz.marker

	markowitz.markersize

Detailed Description

This is a small graphical program that plots the efficient frontier of Markowitz' portfolio selection problem with the two objectives return and risk.

The example utilizes the GamsModelInstance class to solve the parameterized objective max lambda*return - (1-lambda)*risk in the most efficient way. This example requires the Python package matplotlib to be installed.

Definition in file markowitz.py.

Variables

Detailed Description