Abstract:
We suggest and experimentally investigate a method to construct forecasting algorithms
based on data compression methods (or the so-called archivers). By the example of
predicting currency exchange rates we show that the precision of thus obtained predictions is
relatively high.
Citation:
B. Ya. Ryabko, V. A. Monarev, “Experimental Investigation of Forecasting Methods
Based on Data Compression Algorithms”, Probl. Peredachi Inf., 41:1 (2005), 74–78; Problems Inform. Transmission, 41:1 (2005), 65–69
This publication is cited in the following 10 articles:
Anton Rakitskiy, 2022 IEEE International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON), 2022, 120
Morvai G., Weiss B., “Consistency, Integrability and Asymptotic Normality For Some Intermittent Estimators”, ALEA-Latin Am. J. Probab. Math. Stat., 18:2 (2021), 1643–1667
A. S. Lysyak, B. Ya. Ryabko, “Time series prediction based on data compression methods”, Problems Inform. Transmission, 52:1 (2016), 92–99
Boris Ryabko, Jaakko Astola, Mikhail Malyutov, Compression-Based Methods of Statistical Analysis and Prediction of Time Series, 2016, 1
Amir Sani, Alessandro Lazaric, Daniil Ryabko, 2015 IEEE International Symposium on Information Theory (ISIT), 2015, 1194
Pavel Pristavka, Boris Ryabko, 2012 XIII International Symposium on Problems of Redundancy in Information and Control Systems, 2012, 62
Nechta I.V., “Metod vnedreniya skrytykh soobschenii v ispolnyaemye faily”, Vestnik SibGUTI, 2011, no. 2, 3–10
Boris Ryabko, IEEE Information Theory Workshop 2010 (ITW 2010), 2010, 1
Ryabko B., “Compression-based methods for nonparametric prediction and estimation of some characteristics of time series”, IEEE Transactions on Information Theory, 55:9 (2009), 4309–4315
B. Ya. Ryabko, “Application of Data Compression Methods to Nonparametric Estimation
of Characteristics of Discrete-Time Stochastic Processes”, Problems Inform. Transmission, 43:4 (2007), 367–379