Dynamically-generated electronic database for portfolio selection

A system for autonomously creating one or more investment portfolios of selected financial instruments, sharing the investment portfolios, and executing trade instructions thereof, comprising:

• a selector engine comprising a first computer processor configured for:
• creating selection parameters used in selections of financial instruments according to a statistical model representing selection desirability of financial instruments combined with entered user selection preferences for the selections of financial instruments;
• creating the one or more investment portfolios of financial instruments selected based on the selection parameters, a factor weight to each of the selection parameters, and a weighting of each of the financial instruments selected in each of the investment portfolios;
• and
• converting the investment portfolios data to output data representing the trade instructions of financial instruments;
• wherein input to the selector engine for setting the selection parameters created comprising one or more of financial data, analysts' reports, accounting data, news data, corporate data, trading data, and sustainability factor data;
• an execution platform comprising a second computer processor configured for receiving the output data of the selector engine and autonomously executing the trade instructions represented by the output data;
• an investment sharing and democratization module comprising a third computer processor configured for:
• accessing one or more invention portfolio data of other users of the system to generate a specified target investment portfolio adjustable by a degree of imitation of the one or more invention portfolio data of the other users;
• and
• generating from the specified target investment portfolio an additional input to the selector engine for setting the selection parameters;
• a sustainable investing module comprising an eighth computer processor configured to provide the sustainability factor data as input to the selector engine for setting the selection parameters so to optimize the investment portfolios in terms of sustainability and returns on investment while minimize transaction costs and risks;
• and
• a deep learning decision engine configured to optimize the investment portfolios by estimating one or more of the factor weights to the selection parameters and the weightings of the financial instruments selected for the investment portfolios;
• wherein the deep learning decision engine comprises a Heirarchical Risk Parity (HRP) model employed in the estimation of the weightings of the financial instruments selected for the investment portfolios.