ECommerce: Stock Market Analysis Blended With Mining and Ann Ever since the advent of the financial industry, experts have attempted to create systems to track and analyze trends in the stock market. These systems have not suitably predicted future trends, limiting the advice given to consumers. Expert opinions are subject to human error and personal bias, which can potentially lead to financial losses to the consumer. Thus, a system devoid of personal bias, providing an accurate prediction is highly beneficial to the consumer, the broker and the corporations involved in financial markets. Such a system, coupled with the automatic trading system, will optimize transactions leading to overall economic growth. The proposed system performs as a basic IO system. The input is the historical market data, and the stock to be predicted. The output is the recommendation on whether to buy or sell the stock and supplemental graphs to aid the consumer. The key modules of the system are the capture, analysis, search and visualisation modules. These feed into the prediction module, which uses the concept of mining based Artificial Neural Networks (ANN) to provide a reliable recommendation. Finally, all these modules represented to the consumer with webpage based convenient format via home screen.

Recursive Stock Price Prediction With Machine Learning And Web Scrapping For Specified Time Period In the finance world inventory trading is one of the most necessary activities. Stock market prediction is an act of attempting to decide the future price of a stock other monetary instrument traded on a financial exchange. The technical and integral or the time sequence evaluation is used with the aid of most of the stockbrokers while making the inventory predictions. This paper explains the prediction of a stock using Machine Learning. The input parameters include open, high, low, close rate, trading volume, Price to Earning Ratio, MA, MACD for more accuracy. The Machine Learning algorithm, Random Forest Regression has been implemented in Python programming language which is used to predict the stock market. The algorithm has been used on the historical stock data along with web scraping technique that has been applied to catch current market data of the stock. The recursive training model take its predicted value as input to predict further long term future stock rates.