FinBrain Technologies has attended the AI in Finance Summit which was held on Sep. 6-7, 2018 in New York. The purpose of the event was to bring the Data Scientists, Machine Learning Engineers and the people from Startup Companies and Large Financial Institutions who work on Artificial Intelligence Technologies for Finance, together. With more than 200 participants and 30 speakers attending the summit, FinBrain attracted many professionals at the Startup Exhibition Space and with our CEO’s presentation at the second day.
FinBrain had taken its place at the Startup Exhibition Area, attracting developers, engineers and scientists from a wide range of Investment Banks, Universities, Startups and Hedge Funds. During the 2-Day Event, we have informed the sector professionals about our technologies and services, made connections with large investment banks and hedge funds, and explored the collaboration opportunities further.
On the second day of the summit, our CEO Ahmet Salim Bilgin has presented about our work and technologies, explaining further about the mathematical concepts behind applying the Deep Learning Technologies to financial analysis and prediction under the presentation title “Deep Learning for Modeling The Future Price Movements of the Assets“.
The main topics of FinBrain’s presentation covered a brief information about our company, the real world financial analysis problems we focus on and the Neural Network approach to the Financial Prediction. Our CEO has mentioned the challenges of the traditional Fundamental and Technical Analysis methods, and why they are not applicable to today’s computer driven financial world. Mr. Bilgin also explained how Deep Neural Networks can handle complex tasks by analyzing large datasets and “learning” from them to predict the future price movements of the financial assets.
Mr. Bilgin also mentioned FinBrain’s “One Algorithm To Predict Them All” approach, where a single algorithm architecture can collect, analyze, learn from large amounts of data for thousands of Stocks, Commodities, Crypto and Foreign Currencies and predict the future price movements.
The Deep Neural Architecture developed by FinBrain incorporates a number of different mathematical approaches to process the financial datasets, optimize the learning process, adjust the Neural Network hyperparameters, increase the prediction performance on unseen data and prevent overfitting to the present data. This way, the market movements and individual stock/commodity/currency movements can be understood, the patterns, relations and dependencies can be extracted. The future price movements can be modeled from what the Neural Networks have learned from the large datasets. The inputs to the Neural Network can be the asset daily Open, High, Low, Close values, Technical Indicators and market/trader sentiment data.
You can watch the video of our CEO Ahmet Salim Bilgin’s presentation at the AI in Finance Summit New York, below :
FinBrain Technologies, 2018