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One of our fundamental strategy is diversification. Diversification is the process of allocating capital in a way that reduces the exposure to any one particular asset or risk. A common path towards diversification is to reduce risk or volatility by investing in a variety of securities and assets.

Manually analyzing terabytes of trading data to find new relationships and test their significance would be prohibitively expensive. In this way, AI is clearly more efficient than traditional methods. Regularly updating algorithms, finding new data sources, and analyzing results saves time for retail investors.

For the most part, humans make more mistakes than AI-based systems. Intuitive optimism after a win, or paralyzing regret after a loss, are absent from algorithms. Automated execution also reduces the chance of human error. Rules-based systems never take vacations. This reduces the risk of an inexperienced temporary replacement breaking a policy.

AI advanced data analytics can vastly increase the amount of information used to support investment ideas. AI can process events significantly faster than humans and work 24/7. Imagine a time-constrained analyst having a dashboard that summarizes all available reports and compares earnings calls across time and competitors. AI-assisted analysts will probably be better, much better!