With The Best
AI With The Best hosted 50+ speakers and hundreds of attendees from all over the world on a single platform on October 14-15, 2017. The platform held live talks, Insights/Questions pages, and bookings for 1-on-1s with speakers.
In the talk, emphasis will be made on the proposed deep learning strategies applied to design algorithm for the implementation of High Frequency Trading. The deep learning concept applied was achieved by training the neural network with the current date, hour and minute, time series analysis, standard deviations an predictor indicator for predicting the next minute’s stock price. It is seen that the stock prices prediction cannot be made just based on the trend analytics, the prices may vary because of other parameters of the market as well. In order to have a more precise analysis, market situation needs to be understood. For the purpose, text analysis of the Twitter data is done. The prediction model for the HFT involves both quantitative data of the previous minutes’ data as well as quantitative data from Twitter. The analysis is done on the Amazon.com Inc (AMZN) data, from March 2017 to August 2017; the prices seem to have a constant increase since March. Soon after the acquisition of Whole Foods during June second week, the Amazon’s stock market hit a high of 1082.65 on July 27, 2017; which made Jeff Bezos the richest man in the world with Amazon’s stake hit the high of $86.5bn. The research is the first of its kind to take into consideration both qualitative and quantitative data for stock prediction.
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