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Stock Prediction Using NLP and Deep Learning
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StocksNeural.net - Stock prices analysis and prediction using Deep Learning

StocksNeural.net is a service which analyzes and predicts stock prices using Deep Learning and provides useful trade recommendations for the individual traders and asset management companies. In the world where risk-free assets like banking deposits have close to zero or even negative returns, investors are seeking for ways to save and grow their assets.

Predictive models are at the heart of our service. We constantly improve them, try new models and new scientific approaches. We believe our model are more accurate than competitors have and our service is much easier to use by either novice or experienced traders. We are communicating with some of the professional quant traders, and working together to make our system better.

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StocksNeural.net - Stock prices analysis and prediction using Deep Learning

  1. 1. Stock prices analysis and prediction using Deep Learning Dmitry Lukovkin, Petr Permyakov
  2. 2. Problem • Total financial assets of households – USD 250 trillion • USD 58.7 trillion are belong to High Net Worth Individuals • USD 106 trillion expected by 2025 • 600 000 000 of private investors worldwide (165 mln in US only) • Banking deposits rates are close to 0 => investors seek for profitable yet low risk instruments and strategies • Quantitative Analysis is not available to the ‘casual’ investor or too complicated for him 2/11
  3. 3. Product: https://StocksNeural.net Deep Learning-based stock prices predictions and trading recommendations published daily on the Web 3/11
  4. 4. How does it work? 4/11 Load data Preprocess Train neural networks Backtest Predict Publish
  5. 5. How does it work? 5/11
  6. 6. Results 6/11 • Top 50 models: • Average APR – 25.5% • Average % of successful deals – 75% • Average Sortino ratio – 4.67 • Ahead of S&P 500 • Tracking by the independent trader: 8.8% of return for the 7 weeks • Maximal position opened by our client according to our recommendations: $500K • It was profitable
  7. 7. Technology & Features • Deep Learning-based models: • Recurrent (RNN) and convolutional (ConvNet) neural networks • Daily re-training and adaptation to the changing market • Financial instruments covered • S&P 500 constituents • Currency pairs • Commodity futures Premium data feeds are being used • Web-service • Daily predictions and trade recommendations • Screening by models accuracy and performance 7/11
  8. 8. Customer traction • > 1000 registered users • Mostly males, 25-44 • Avid investors • Got covered in the business media – RBC.Money, Financial One • Cooperation & collaboration with experienced individual traders and institutions: • Hedge funds/asset management firms – Russia, US, France • Traders from Canada, Germany, US and Russia • Energy company from TX, US 8/11
  9. 9. Business Model • Subscription model for the individual investors • Partnership with brokers: • Lead generation • Integrated trading – share of commissions • Partnership with institutions: • Hedge funds, asset management firms – share of management fee • Tailored models for specific products and markets 9/11
  10. 10. Team Dmitry Lukovkin • More than 15 years of IT experience. Serial entrepreneur. • Projects: DavaiSravnim, Berry.Travel, Za Rabotoy • Project Management, Web-development, Data Science • Focusing on machine learning problems during last 3 years. Has a long term trading experience. Petr Permyakov • IT infrastructure specialist with over 9 years hands-on experience in analysis,architecture design, development, and project management • Has an experience as an IT Infrastructure Architect in the one of the leading invest banks, providing and managing grid computing environment for core business applications 10/11
  11. 11. AI and Deep Learning will change the people’s lives. Join us! http://stocksneural.net Dmitry Lukovkin lukovkin@stocksneural.net Skype: dmitry.lukovkin T: +7 (903) 750 29 76
  • PancrazioAuteri

    Feb. 20, 2018
  • SemBarang1

    Dec. 31, 2017

StocksNeural.net is a service which analyzes and predicts stock prices using Deep Learning and provides useful trade recommendations for the individual traders and asset management companies. In the world where risk-free assets like banking deposits have close to zero or even negative returns, investors are seeking for ways to save and grow their assets. Predictive models are at the heart of our service. We constantly improve them, try new models and new scientific approaches. We believe our model are more accurate than competitors have and our service is much easier to use by either novice or experienced traders. We are communicating with some of the professional quant traders, and working together to make our system better.

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