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Our goal is to create a portfolio of financial assets that yields a positive return even at market corrections.We develop a platform that uses Bayesian statistics and AI knowledge (primarily neural networks) to effectively rebalance the portfolio of business strategies (taking into account all aspects of risk management, such as portfolio engagement based on mutually correlated titles, currency, business strategy – all in order to rebalance the portfolio according to the given requirements).

The platform will be able to identify situations where there is low / high liquidity on the market and, in the light of this, to disable / deploy some trading strategies, modify money management, or avoid trading completely.

Output is a bot – an actively managed portfolio that exhibits lower risk (measured by maximum drawdown) with higher yield stability, without active trader / developer intervention. The potential of the platform is to work in multiple versions of the user’s IT capability – from a very variable user environment, where the programmer can create and manage a tailor-made portfolio to a black box (lite version) where the user chooses from several preferred criteria and the bot will, according to selected criteria, compose the portfolio itself.

Jiří Fuchs