Purpose – In this two-part series, this paper seeks to consider certain intriguing aspects of randomness, the basic mathematical concept used to model financial risk and other unknown quantities in the physical world. Design/methodology/approach – Part 1 applies concepts from quantum physics and algorithmic information theory to distinguish between knowable complexity and unknowable complexity. Findings – In Part 1, it is found that Heisenberg's uncertainty principle can be used to provide concrete examples of random variables, and that the Kolmogorov/Chaitin notion of algorithmic complexity can be used to define the formal concept of randomness. Originality/value – The two-part series explores the underlying nature of randomness in terms of both its physical/mathematical properties and its role in human cognition.
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