I. Introduction
Financial market is a fundamental part of economy and many actors are involved with, from individual investors to central banks. The movements of global financial markets are influenced by a very complex net of factors which make it a very challenging task to take advantage from those movements and make profit from them. Stock markets play an important role in the financial markets: companies can finance its operations and hedge its debts against currency fluctuations, all kinds of investors can diversify its capital allocation and speculators can make profit from short term movements. Stock prices are volatile and can move up or down in response to political, macro or micro economy events. A change in interest rates can affect all stock market, and an event of a company can affect beside its own stock, stocks of other companies that have any kind of business relation. In this context, it is a very difficult task to predict all the events that can influence the price movement of a stock, which is based on the supply and demand of that stock, and furthermore, how the market will respond to these events. Investors often rely on strategies that help them to determine how and when to buy or sell a stock. Many trading strategies can be found on literature and researchers are constantly testing, adapting and developing new tools that can be used in trading strategies. An important approach to operate in the stock market is the Technical Analysis (TA), which is defined in [8] as “the study of market action for the purpose of forecasting future price trends”. TA is based on the analysis of market patterns, supply and demand of stock shares and is highly supported by technical indicators. Technical indicators are constructed using information of stock prices and are argued to determine which way a stock is most likely to go. To choose an indicator among all available is not a trivial task and once one or a set of indicators are chosen, the adjustment of the indicator's parameters can determine the success or failure of a given strategy. Investors can adjust the parameters by experience with the analysis of past movements or arbitrarily pick a set of parameters recommended from literature or other investors. In the first case, the adjustment of parameters can be biased by investor's behavior and in the second case a set of parameters that had once worked well, could not still profitable or could not fit to a given stock. To overcome those issues an approach to adjust technical indicator parameters based on multi-objective optimization (MOO) is presented. TA and the indicators evaluated in this paper are explained in section II. In section III some features of MOO procedures are discussed and section IV explain the conditions that guides the experiments performed in this work. In Section V the results obtained are presented and discussed and finally, in section VI, conclusions and directions for future development end this work.