Cloud Based financial market prediction through Genetic Algorithm

Abstract

Stock market prediction is so dynamic and determining its nature that with single formula it is newlinenear to impossible. In a global economy all things are connected to each other irrespective of newlinetheir geographical areas. Genetic Algorithms are one of the best methods to predict the market in newlinevery efficient manner. Scientists are using various methods to predict the market but it s tough to newlinejudge the right methods in the chaotic market. From traditional statistical methods to other data newlinemining tools by using social media tools like prediction of market with twitter accounts, there newlineare long chain of methods has been used over the period of time. Dynamism in the market leads newlineus to develop dynamic trading methods in which method of prediction in a market is being newlinedecided by various factors and its suitability. Algorithm based financial forecasting is one of the newlineconcerned area where researcher deal with stock prices and try to predict the market in different newlinemarket conditions. Next part of the thesis deals with the optimizations portfolio and hedging newlinetools used for portfolio management. Selections of these tools for the optimization are second newlineconcern areas among specialists or investors. Many Artificial Intelligence (AI) tools are newlineavailable for the hedging in stock market. Markowitz and other Artificial Intelligence (AI) newlinemodels are extremely helpful in the portfolio management and predictive analysis of the stock newlinemarket. Integration of data through cloud has opened new avenue in the stock market. newlineOptimization of hedging of risk taken during portfolio creation and management is relatively newlineuntouched in the era of BIG DATA with the extensive use of Artificial Intelligence (AI) models. newlineGenetic Algorithms are more suitable to calculate exact risk during portfolio management newlineprocess and that lead to the hedging. newline