Research on stock price prediction and trading model using evolutionary computation has been done in recent years. As we know, prediction in the stock market is quite difficult for a number of reasons. First, the ultimate goal of our research is not to minimize the prediction error, but to maximize the profits. Second, the weak relationships among variables tend to be nonlinear, and they may ho...

Portfolio selection represents a challenge where investors look for the best firms of the market to be selected. This research presents a real world application at the Mexican Stock Exchange (La Bolsa) using a set of heuristic algorithms for portfolio selection. The heuristic algorithms (random, genetic, greedy, hill-climbing and simulated annealing) were implemented based on the Markowitz Mode...

This paper presents a model of portfolio choice and stock trading volume with lossaverse investors. The demand function for risky assets is discontinuous and non-monotonic: as wealth rises beyond a threshold investors follow a generalized portfolio insurance strategy. This behavior is consistent with the evidence in favor of the disposition effect. In addition, loss-averse investors will not ho...

The portfolio selection is an important technique to decrease the risk in stock investment. In portfolio selection, the investor’s property is distributed among a set of stocks in order to minimize the financial risk in market downturns. With this in mind, and aiming to develop a tool to assist the investor in finding balanced portoflios, we achieved a generic method for feature clustering with...

In this paper a portfolio optimization algorithm based on Evolution Strategies is presented. This method makes use of artificial trading experts discovered earlier by a genetic algorithm. These experts, consisting of technical analysis rules, are trained to process financial time series and to generate trading advice. Evolution Strategies lead to the optimization of portfolio structures where i...

where u1 is the proportion of the portfolio held in stocks, and u2 is the consumption rate. Evidently it is natural to take 0 ≤ u1 ≤ 1 and u2 ≥ 0, but in fact we shall allow −∞ < u1 <∞. If u1 > 1 then the cash part of the portfolio is negative, so we are borrowing money to buy stocks. If u1 < 0 then the stock part of the portfolio is negative, so we are so called shorting the stock. The goal is...

Pricing of options on stocks that are driven by multi-dimensional coupled price-temporal infinitely divisible fluctuations. We model the price of a stock via a Langévin equation with multi-dimensional fluctuations coupled both in the price in time. We generalise previous models in that we assume that the fluctuations conditioned on the time step are assumed to be compound Poisson processes with...

portfolio theory assumes that investors accept risk. this means thatin the equal rate of return on the two assets, the assets were chosenthat have a lower risk level. modern portfolio theory is accepted byinvestors who believe that they are not cope with the market. sothey keep many different types of securities in order to access theoptimum efficiency rate that is close to the rate of return o...

The de nition of universal portfolio was introduced in the nancial literature in order to describe the class of portfolios which are constructed directly from the available observations of the stocks behavior without any assumptions about their statistical properties. Cover [6] has shown that one can construct such portfolio using only observations of the past stock prices which generates the s...

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...