We consider a financial market with one bond and one stock. The dynamics of the stock price process allow jumps which occur according to a Markov-modulated Poisson process. We assume that there is an investor who is only able to observe the stock price process and not the driving Markov chain. The investor’s aim is to maximize the expected utility of terminal wealth. Using a classical result fr...

there have been several efforts in the literature to extract as much information as possible from the financial networks. most of the research has been concerned about the hierarchical structures, clustering, topology and also the behavior of the market network; but not a notable work on the network filtration exists. this paper proposes a stock market filtering model using the correlation - ba...

The influence of changing economic environment leads the distribution of stock market returns to be time-varying. This requires a dynamic adjustment of the asset allocation in order to enjoy a conditionally optimal investment. In this context, we examine the improvement of the portfolio performance by simulating portfolio strategies that are conditioned on the Markov regime switching behavior o...

The paper presents results of computer-assisted portfolio management simulation based on using a DEACascor mathematical model. The model uses the Data Envelopment Analysis (DEA) ratio as a neuron with memory and combines it with Cascade Correlation Neural Network (Cascor) to forecast stock prices. The model is designed for using in high-frequency stock trading. It utilizes ability of DEA to con...

This paper analyzes the relations among firm-level stock option portfolio incentives, investment, and firm value based on a sample of Finnish firms during the time period 1987 – 2000. Utilizing exact and complete information regarding stock option portfolio characteristics, we find some evidence that firm investment is increasing in the incentives to increase stock price (delta) and risk (vega)...

Identification of useful patterns in price movement of a stock in stock market needs tremendous analytical skills and effort. Careful analysis of the available technical indicators will help finding the right timing of trading of a stock to maximize the gains. To help investors manage their portfolios, we propose a tool for clustering and classification of stock market data using an unsupervise...

portfolio selection is considered a critically significant decision, firms have to make. as such, much research has been focused on the selection of a portfolio with a controlled level of risk and high expected return. this paper uses a new definition of risk for portfolio selection whereby risk taking is taken as a curve instead of a specific value. in this paper, a genetic algorithm is presen...

The purpose of this study is to develop portfolio optimization and assets allocation using our proposed models. The study is based on a non-parametric efficiency analysis tool, namely Data Envelopment Analysis (DEA). Conventional DEA models assume non-negative data for inputs and outputs. However, many of these data take the negative value, therefore we propose the MeanSharp-βRisk (MShβR) model...