Crispersoft company has developed a solution for the fintech industry – a platform for assessing the company’s attractiveness in the US stock market. Assessment of the company in the short and long term period is carried out by analyzing a large amount of historical data about the company using Artificial Intelligence and machine learning algorithms. The final forecast for the stock of a particular company is calculated on the basis of various fundamental (quarterly reports of the company, news background, calculated by our engineers Piotroski score (F-score), etc.) and technical parameters (simple and exponential moving averages, overbought indices, accumulation zones, etc.)
Reports and news highlights are analyzed by specially developed NLP (Natural Language Processing) neural networks that monitor the mood of publications (sentiment analysis), machine learning algorithms analyze the movement of historical rates, as well as closing prices in different historical periods.
Our AI tool analyzes and ranks companies in four main groups A, B, C, D, where D is the most negative rating and A is the most positive, which signals the investor the profitability of buying this stock.
The platform provides the user with the opportunity to get acquainted with additional information and vast amounts of company statistic data points, our service updates the data for each stock from the main US exchanges NYSE and NASDAQ on a daily basis. For more accurate statistics and evaluating the performance of the forecasting system of our platform, we work with more than three thousand stocks whose intraday volume is at least one million dollars.
Much attention is paid to data visualization, which allows the investor to make the most balanced and optimal decision when buying a particular stock.
The platform user also has access to a personal account and the ability to not only observe, but also create a personal stock portfolio with the ability to group shares by industry, monitor portfolio profitability and compare company stocks and update the investment portfolio depending on market conditions.