Algorithmic Relative Complexity

Algorithmic Relative Complexity

Information content and compression are tightly related concepts that can be addressed through both classical and algorithmic information theories, on the basis of Shannon entropy and Kolmogorov complexity, respectively. The definition of several entities in Kolmogorov’s framework relies upon ideas from classical information theory, and these two approaches share many common traits. In this wor...

Algorithmic complexity theory and the relative efficiency of financial markets

Financial economists usually assess market efficiency in absolute terms. This is to be viewed as a shortcoming. One way of dealing with the relative efficiency of markets is to resort to the efficiency interpretation provided by algorithmic complexity theory. We employ such an approach in order to rank 36 stock exchanges, 37 individual company stocks, and 19 US dollar exchange rates in terms of...

Algorithmic Folding Complexity

How do we most quickly fold a paper strip (modeled as a line) to obtain a desired mountain-valley pattern of equidistant creases (viewed as a binary string)? Define the folding complexity of a mountain-valley string as the minimum number of simple folds required to construct it. We first show that the folding complexity of a length-n uniform string (all mountains or all valleys), and hence of a...

Algorithmic “Kolmogorov” Complexity

The information content or complexity of an object can be measured by the length of its shortest description. For instance the string ‘01010101010101010101010101010101’ has the short description “16 repetitions of 01”, while ‘11001000011000011101111011101100’ presumably has no simpler description other than writing down the string itself. More formally, the Algorithmic “Kolmogorov” Complexity (...

Algorithmic Randomness and Complexity