TL;DR
This paper proposes a Turing Test-inspired framework to evaluate the intelligence of trading programs in financial markets, emphasizing the role of curiosity and foundational principles in AI development.
Contribution
It introduces a novel test for AI in finance based on the Turing Test concept, focusing on decision-making in trading scenarios.
Findings
A proposed methodology for testing AI trading programs.
Discussion of principles guiding autonomous decision-making.
Application of the test to buy/sell/hold dilemmas in finance.
Abstract
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.
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Taxonomy
TopicsComputability, Logic, AI Algorithms · Economic theories and models · Artificial Intelligence in Games
MethodsTest