Artificial-Intelligence-Driven Management: Autonomous Real-Time Trading and Testing of Portfolio or Inventory Strategies

Abstract

“Artificial-Intelligence-Driven Management” (AIDM) replaces the Deming cycle with the Artificial Intelligence-assisted Plan-Predict-Act cycle. Collaborative LeanBots for an industrial base and Trading- or StockExBots for trading or financial institutions and their clients, use this paradigm shift to perform cyber-secure, sophisticated decision-making processes (transactions) autonomously and in real-time at large scale, at low cost, and with minimal energy consumption. Recursively utilized gains reinforce and accelerate growth. Expanding on modern portfolio management, autonomous TradingBots diversify portfolios like inventories not only in terms of asset weighting, but also with respect to holding periods and moreover, do so in real-time. TradingBots can also be deployed to test automation, collaboration, portfolio, and inventory strategies. Metrics from modern portfolio management used show that StockExBots are able to outperform high-ranking index and actively managed funds. Five use cases are presented for leveraging the properties of StockExBots commercially. TradingBots can be deployed with a wide range of non-proprietary and proprietary (IoT or IIoT) devices or as software services, supporting decentralized, redundant, and localized transaction processes in proprietary (e.g., financial or trading institutions) and non-proprietary smart (home) environments. Linking both environments improves the scalability of proprietary ones and enables the migration and dispersion of complex real-time decision-making processes for mutual benefit.