Imitation in the Imitation Game
This work addresses the challenge of assessing AI decision-making in finance, though it appears incremental as it adapts an existing test framework to a specific domain.
The paper proposes a Turing Test-inspired benchmark for evaluating the intelligence of automated trading systems in financial markets, focusing on the buy/sell/hold decision-making dilemma.
We discuss the objectives of automation equipped with non-trivial decision making, or creating artificial intelligence, in the financial markets and provide a possible alternative. Intelligence might be an unintended consequence of curiosity left to roam free, best exemplified by a frolicking infant. For this unintentional yet welcome aftereffect to set in a foundational list of guiding principles needs to be present. A consideration of these requirements allows us to propose a test of intelligence for trading programs, on the lines of the Turing Test, long the benchmark for intelligent machines. We discuss the application of this methodology to the dilemma in finance, which is whether, when and how much to Buy, Sell or Hold.