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Advanced Trading Bot Using Deep Learning

  • Unique Paper ID: 155690
  • Volume: 9
  • Issue: 1
  • PageNo: 1566-1571
  • Abstract:
  • The Era of Training Data through Machine Learning processes is a popular and effective way to deduce the future outcome of things with variable data plots. Trading with trading algorithms commonly known as trading bots have been in the market for a few years now, Algorithmic Trading accounts for a surprising 35.1% of the stocks that are listed in the USA stock exchange, which is much higher than that of the assets managed by consumer traders. Machine learning with its specifications in deep learning is a remarkable way for data analytics and prediction of future plots, hence leveraging the vast data of historic prices and the predicting capabilities we plan to create a trading bot for the industry. Trading is a very old concept of commerce; the origin of trading is the barter system, having a fixed price of a commodity depending on the price of a superior commodity well described as cross elasticity in economics. The first stock exchange in this world is the “Amsterdam Stock Exchange” which was established in the year 1602. The volatility in the market prices of stocks/indexes may seem random but it is caused by an event or simple demand-supply changes. There are two main stock exchanges in India: NSE- National Stock Exchange and BSE- Bombay Stock Exchange. The historic trading data of each stock/Index is available on BSE and NSE websites and you can also use a private paid service for live in market data. The dataset consists of the opening and closing prices of the stocks/ indexes from 1994 to date. The use of multiple algorithms on the same data sets to get and find the accuracy for each of the algorithms and then a way to use reinforced learning to improve the accuracy by cross-referencing the prediction with different algorithms. The method we are proposing involves multiple algorithms and one deep learning model, in order to get the highest accuracy, we are using some indicator functions of the values EMA – Exponential moving average over discreet time periods, Stochastic RSI- Relative Strength Index from the set ranges of. So we will be making a combination of these and other significant indicators to help increase the accuracy of the model.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 9
  • Issue: 1
  • PageNo: 1566-1571

Advanced Trading Bot Using Deep Learning

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Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

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