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, ...

This work aims the development of an enhanced portfolio selection method, which is based on the classical portfolio theory proposed by Markowitz (1952) and incorporates the local Gaussian correlation model for optimization. This novel method of portfolio selection incorporates two assumptions: the non-linearity of returns and the empirical observation that the relation between assets is dynamic...

In this paper, a novel prediction based mean-variance (PBMV) model has been proposed, as an alternative to the conventional Markowitz mean-variance model, to solve the constrained portfolio optimization problem. In the Markowitz mean-variance model, the expected future return is taken as the mean of the past returns, which is incorrect. In the proposed model, first the expected future returns a...

It is important to investigate the different impact factors on establishment of investment portfolio. In order maximize profit a portfolio, this research selects six stocks: Adobe (ADBE), International Business Machines Corp (IBM), Bank America Corporation (BAC), Citigroup (C), Southwest Airlines Co (LUV) and Alaska Air Group Inc. (ALK) as an empirical case conduct decision. This compares resul...

The appearance of Markowitz Model significantly improves the way investors optimize their financial portfolio, allowing them to reduce collective risks different assets and further maximize profitability portfolio. This article aims discuss analyze feasibility in practical cases as definition this mean variance model leans theoretical aspect finance like efficient market rational investors. dat...

The Markowitz mean-variance optimization model is a widely used tool for portfolio selection. However, in order to capture real world restrictions on actual investments, a Limited Asset Markowitz (LAM) model with the introduction of quantity and cardinality constraints has been considered. These two constraints have been modelled by adding binary variables to the Markowitz model, thus resulting...

The Markowitz mean-variance optimization model is a widely used tool for portfolio selection. However, in order to capture real world restrictions on actual investments, a Limited Asset Markowitz (LAM) model with the introduction of quantity and cardinality constraints has been considered. These two constraints have been modelled by adding binary variables to the Markowitz model, thus resulting...

in this paper after a general literature review on the concept of efficient frontier (ef), an important inadequacy of the variance based models for deriving efs and the high necessity for applying another risk measure is exemplified. in this regard for this study the risk measure of lower partial moment of the first order is decided to replace variance. because of the particular shape of the pr...

Asset allocation among diverse financial markets is essential for investors especially under situations such as the financial crisis of 2008. Portfolio optimization is the most developed method to examine the optimal decision for asset allocation. We employ the hidden Markov model to identify regimes in varied financial markets; a regime switching model gives multiple distributions and this inf...