High volatile markets analysis with using Berg method and Chebyshev type II filters, and statistical modeling of the risk of loss for its tools. (Russian. English summary) Zbl 1449.62268
Summary: We describe the method of technical analysis of highly volatile markets in the framework of signal processing theory, which uses Chebyshev filter. Berg method is used to estimate spectral density of the signal power. The algorithm of optimal AR-model order calculation is given. The method for profit rate estimation based on artificial noise generation, preserving its structure, is developed.
MSC:
62P20 | Applications of statistics to economics |
62M20 | Inference from stochastic processes and prediction |
62M15 | Inference from stochastic processes and spectral analysis |
References:
[1] | Kravchuk V. K., “New Adaptive Method of Following the Tendency and Market Cycles”, Valyutny Spekulyant, 2000, no. 12, 50-55 |
[2] | Kravchuk V. K., “Spectral Analysis of EUR/USD Currency Rate Fluctuation Based on Maximum Entropy Method”, Valyutny Spekulyant, 2001, no. 11, 14-17 |
[3] | Marple A. L, Digital Spectral Analysis and its Applications, Mir, Moscow, 1990, 547 pp. |
[4] | Shakhtarin B. I, Kovrigin V. A., Methods of spectral estimation of random processes, Gelios ARV, Moscow, 2005, 248 pp. |
[5] | Wentzell E. S., Theory of Probability, Vyssh. shk., Moscow, 2006, 575 pp. |
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.