Identifying Indian Stock Market for Monthly Based by using Apriori Algorithm

Market analysis is an important component of analytical system in retail organizations to improve determine the placement of goods, designing sales promotions for different segments of customers satisfaction to improve customer satisfaction and hence the profit of the supermarket. These issues for a leading supermarket are addressed here using frequent itemset data mining. The frequent itemsets are mined from the market basket database using the efficient K-Apriori algorithm and then the association rules are generated. The stock market is a non-linear, unpredictable system that is extremely difficult to improve these model with any reasonable accuracy. Investors have been trying to find a currect way to predict stock prices and to find the right stocks and right timing to buy or sell. To achieve this goal, the techniques of fundamental analysis as well as technical analysis are used. Fundamental Analysis is based on the study of factors external to the trading markets which affect the supply and demand of a stock market. It mainly focuses on factors like technological invention, growth of the company, PE ratio, weather, government strategies, financial and political events and prospects of business. It strongly believes that by monitoring such factors for a stock market a state of potential disequilibrium of stock market conditions may be recognized before the state has been reflected in the share price of the company. Technical analysts strongly believe that the current price of company share completely replicates all fundamental information. As all the fundamental information is already replicated in the price, technical analysts consider the current price as the fair value and strongly believe that current price should form the basis for the research. It refers to the various techniques that aim to predict future price movements using past stock prices and volume information.