Frequency effects on predictability of stock returns

We propose that predictability is linked with profitability in a complex manner. We look at ways to measure predictability of price changes using information theoretic approach and employ them on historical data for NYSE 100 stocks. This allows us to determine whether frequency of sampling price changes affects the predictability of those. We also study relations between price changes predictability and the deviation of the price formation processes from iid as well as the stock's sector. We also briefly comment on the complicated relationship between predictability of price changes and the profitability of algorithmic trading.

[1]  Frans M. J. Willems,et al.  The context-tree weighting method: basic properties , 1995, IEEE Trans. Inf. Theory.

[2]  Klaus Pawelzik,et al.  Limited profit in predictable stock markets , 2005 .

[3]  Chien-Chiang Lee,et al.  Energy prices, multiple structural breaks, and efficient market hypothesis , 2009 .

[4]  David A. Hsieh,et al.  Implications of Nonlinear Dynamics for Financial Risk Management , 1993, Journal of Financial and Quantitative Analysis.

[5]  David Gregg,et al.  An experimental study of sorting and branch prediction , 2008, JEAL.

[6]  Frans M. J. Willems,et al.  The Context-Tree Weighting Method : Extensions , 1998, IEEE Trans. Inf. Theory.

[7]  Florencia Leonardi Some upper bounds for the rate of convergence of penalized likelihood context tree estimators , 2007 .

[8]  劉完淳,et al.  Review of Pacific Basin Financial Markets and Policies , 2006 .

[9]  Faruk Göloglu,et al.  On Lempel-Ziv Complexity of Sequences , 2006, SETA.

[10]  Idan Segev,et al.  The information efficacy of a synapse , 2002, Nature Neuroscience.

[11]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[12]  Xue-Zhong He,et al.  Heterogeneity, Profitability and Autocorrelations , 2005 .

[13]  Jonathon Shlens,et al.  Estimating Entropy Rates with Bayesian Confidence Intervals , 2005, Neural Computation.

[14]  Tobias Zier,et al.  Squeezed Thermal Phonons Precurse Nonthermal Melting of Silicon as a Function of Fluence , 2013 .

[15]  R. Steuer,et al.  Entropy and optimal partition for data analysis , 2001 .

[16]  A. Menkveld High frequency trading and the new market makers , 2013 .

[17]  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 .

[18]  Ioannis Kontoyiannis Asymptotically optimal lossy Lempel-Ziv coding , 1998, Proceedings. 1998 IEEE International Symposium on Information Theory (Cat. No.98CH36252).

[19]  A. Mees,et al.  Context-tree modeling of observed symbolic dynamics. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[20]  Benoist,et al.  On the Entropy of DNA: Algorithms and Measurements based on Memory and Rapid Convergence , 1994 .

[21]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[22]  Cheng-Few Lee,et al.  Efficient Market Hypothesis (EMH): Past, Present and Future , 2008 .

[23]  Yun Gao,et al.  Estimating the Entropy of Binary Time Series: Methodology, Some Theory and a Simulation Study , 2008, Entropy.

[24]  Yanrui Wu,et al.  The Chinese Stock Market: Efficiency, Predictability And Profitability , 2004 .

[25]  W. Jernajczyk,et al.  Zastosowanie metody empirycznej dekompozycji modalnej i złożoności Lempel’a-Ziv’a do analizy EEG chorych na schizofrenię / , 2008 .

[26]  Yuri M. Suhov,et al.  Nonparametric Entropy Estimation for Stationary Processesand Random Fields, with Applications to English Text , 1998, IEEE Trans. Inf. Theory.

[27]  B. LeBaron,et al.  A test for independence based on the correlation dimension , 1996 .

[28]  Shu-Heng Chen,et al.  On Predictability and Profitability: Would GP Induced Trading Rules be Sensitive to the Observed Entropy of Time Series? , 2008, Natural Computing in Computational Finance.

[29]  Yun Gao,et al.  From the Entropy to the Statistical Structure of Spike Trains , 2006, 2006 IEEE International Symposium on Information Theory.

[30]  Serap A. Savari,et al.  On the entropy of DNA: algorithms and measurements based on memory and rapid convergence , 1995, SODA '95.

[31]  Abraham Lempel,et al.  A universal algorithm for sequential data compression , 1977, IEEE Trans. Inf. Theory.

[32]  Albert-László Barabási,et al.  Limits of Predictability in Human Mobility , 2010, Science.

[33]  Frans M. J. Willems,et al.  Context weighting for general finite-context sources , 1996, IEEE Trans. Inf. Theory.

[34]  J. Barkley Rosser,et al.  Econophysics and Economic Complexity , 2008, Adv. Complex Syst..

[35]  Chiranjeev Kohli,et al.  The price is right? Guidelines for pricing to enhance profitability , 2011 .

[36]  Guy Louchard,et al.  Average redundancy rate of the Lempel-Ziv code , 1996, Proceedings of Data Compression Conference - DCC '96.