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.
Part 1 applies concepts from quantum physics and algorithmic information theory to distinguish between knowable complexity and unknowable complexity.
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.
The two‐part series explores the underlying nature of randomness in terms of both its physical/mathematical properties and its role in human cognition.
