PEMBENTUKAN PORTOFOLIO OPTIMAL MENGGUNAKAN MODEL MARKOWITZ

Markowitz Model for Robust Edge Detection

For many image processing applications, the aim is to detect a certain event or occurrence in a noisy data set. Several algorithms may exist that solve the detection problem. An example is the detection of edges. The subsequent difficulty then is how to select a proper weighting scheme for the algorithms so that the results are combined optimally. To achieve proper fusion of detection outputs, ...

Improving the Markowitz Model using the Notion of Entropy

The Mean-variance framework proposed by Markowitz is the most common model for portfolio selection problem. The most important concept in his theory is diversification. Diversification means designing an investment portfolio that reduces exposure risk by combining a variety of investments. But actually, the portfolios’ weights are often extremely concentrated on few assets when using mean-varia...

Determination the Parameters of Markowitz Portfolio Optimization Model

The main purpose of this study is the determination of the optimal length of the historical data for the estimation of statistical parameters in Markowitz Portfolio Optimization. We present a trading simulation using Markowitz method, for a portfolio consisting of foreign currency exchange rates and selected assets from the Istanbul Stock Exchange ISE 30, over the period 2001-2009. In the simul...

Sparse and stable Markowitz portfolios.

We consider the problem of portfolio selection within the classical Markowitz mean-variance framework, reformulated as a constrained least-squares regression problem. We propose to add to the objective function a penalty proportional to the sum of the absolute values of the portfolio weights. This penalty regularizes (stabilizes) the optimization problem, encourages sparse portfolios (i.e., por...

Introduction to the Markowitz Model (first Draft, Likely to Change)