Quant Factory

Quant Factory forecasts and analyzes stocks as investments using time-series models, large language models, neural networks, and other algorithms. These tools enable the processing of vast amounts of data with limited resources. Human input remains an essential part of quality control and the forecasting of financial statement data. The process is not entirely independent of human oversight.

Financial data is standardized into a quarterly format. Consequently, data reported on a semi-annual basis is allocated across two quarters. For companies with non-standard fiscal years or quarterly schedules, data has been aligned with Quant Factory’s process as closely as possible. Furthermore, since not all companies disclose every data point on a quarterly basis, some figures are based on estimates.

Valuation relies on machine learning, utilizing a neural network trained on realized market values ​​and financial statement data. The AI-generated target price and market value form the basis for SELL, HOLD, or BUY recommendations. Typically, the target price is updated following the integration of quarterly financial data, while the recommendation is usually updated two times per day.

The aim is to update the share price twice daily: once approximately three hours after trading begins and again roughly two hours after trading closes. A new analysis may be published before trading ends; such updates are visible on the fron page. Quant Factory’s primary goal is not to be the sole factor influencing investment decisions. Rather, the aim is to facilitate the investment process and help identify interesting investment opportunities from a large pool of stocks. In addition to the analysis, it is always advisable to review the companies' own financial reports and other news.