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 and 20 US dollar exchange rates in terms of their relative efficiency.

[1]  Schuster,et al.  Easily calculable measure for the complexity of spatiotemporal patterns. , 1987, Physical review. A, General physics.

[2]  A. Lo,et al.  THE ECONOMETRICS OF FINANCIAL MARKETS , 1996, Macroeconomic Dynamics.

[3]  F. Hayek The economic nature of the firm: The use of knowledge in society , 1945 .

[4]  E. Fama The Behavior of Stock-Market Prices , 1965 .

[5]  Sanford J. Grossman ON THE EFFICIENCY OF COMPETITIVE STOCK MARKETS WHERE TRADES HAVE DIVERSE INFORMATION , 1976 .

[6]  A Paul,et al.  SAMUELSON, . Proof that properly anticipated prices fluctuate randomly, Industrial Management Review, . , 1965 .

[7]  Gabjin Oh,et al.  Market efficiency in foreign exchange markets , 2007 .

[8]  G. Magenes,et al.  Complexity analysis of the fetal heart rate for the identification of pathology in fetuses , 2005, Computers in Cardiology, 2005.

[9]  S Sidney,et al.  ALEXANDER, . Price Movements in Speculative Markets: Trends or Random Walks, No. 2. Industrial Management Review, , . , 1964 .

[10]  Meredith J. Beechey,et al.  THE EFFICIENT MARKET HYPOTHESIS: A SURVEY , 2000 .

[11]  H. Markowitz,et al.  The Random Character of Stock Market Prices. , 1965 .

[12]  Armin Shmilovici,et al.  Using a Stochastic Complexity Measure to Check the Efficient Market Hypothesis , 2003 .

[13]  Sergio Da Silva,et al.  The Chinese chaos game , 2007 .

[14]  L. Bachelier,et al.  Théorie de la spéculation , 1900 .

[15]  J. Richman,et al.  Physiological time-series analysis using approximate entropy and sample entropy. , 2000, American journal of physiology. Heart and circulatory physiology.

[16]  H. Stanley,et al.  Quantifying signals with power-law correlations: a comparative study of detrended fluctuation analysis and detrended moving average techniques. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  H. Stanley,et al.  Multifractal properties of price fluctuations of stocks and commodities , 2003, cond-mat/0308012.

[18]  G. Viswanathan,et al.  Multifractality and heteroscedastic dynamics: An application to time series analysis , 2007 .

[19]  B. Li,et al.  LZ Complexity Distance of DNA Sequences and Its Application in Phylogenetic Tree Reconstruction , 2016, Genomics, proteomics & bioinformatics.

[20]  Ching-Wei Tan Estimating the Complexity Function of Financial Time series: An Estimation Based on Predictive Stochastic Complexity , 1999 .

[21]  H. Stanley,et al.  Effect of trends on detrended fluctuation analysis. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[22]  Maurice G. Kendall,et al.  The Analysis of Economic Time‐Series—Part I: Prices , 1953 .

[23]  Rosario N. Mantegna,et al.  Book Review: An Introduction to Econophysics, Correlations, and Complexity in Finance, N. Rosario, H. Mantegna, and H. E. Stanley, Cambridge University Press, Cambridge, 2000. , 2000 .

[24]  Sergio Da Silva,et al.  Are pound and euro the same currency , 2007 .

[25]  I. Shmulevich,et al.  Measures of Temporal Pattern Complexity , 2000 .

[26]  S M Pincus,et al.  Approximate entropy as a measure of system complexity. , 1991, Proceedings of the National Academy of Sciences of the United States of America.

[27]  Abraham Lempel,et al.  On the Complexity of Finite Sequences , 1976, IEEE Trans. Inf. Theory.

[28]  Harry V. Roberts,et al.  STOCK‐MARKET “PATTERNS” AND FINANCIAL ANALYSIS: METHODOLOGICAL SUGGESTIONS , 1959 .

[29]  E. Fama EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* , 1970 .