Synchronous components of financial time series

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List of references:

  1. С. А. Айвазян, В. М. Бухштабер, И. С. Енюков, Л. Д. Мешалкин. Прикладная статистика. Классификация и снижение размерности. — М: Финансы и статистика, 1989.
    • S. A. Ayvazyan, V. M. Buhshtaber, I. S. Enyukov, L. D. Meshalkin. Applied Statistics. Classification and Reduction of Dimensionality. — Moscow: Finansy i statistica, 1989. — in Russian. — MathSciNet: MR0789433.
  2. А. А. Любушин. Анализ данных систем геофизического и экологического мониторинга. — М: Наука, 2007.
    • A. A. Lyubushin. Analysis of the data from geophysical and ecological monitoring systems. — Mosocw: Nauka, 2007. — in Russian.
  3. А. А. Любушин. Анализ канонических когерентностей в задачах геофизического мониторинга // Физика Земли. 1998. — № 1. — С. 59–66.
    • A. A. Lyubushin. Analiz canonicheskih cogerentnostey v zadachah geofizicheskogo monitoringa // Fizika Zemli. 1998. — no. 1. — P. 59–66. — in Russian.
    • A. A. Lyubushin. Analysis of Canonical Coherences in the Problems of Geophysical Monitoring // Izvestiya, Physics of the Solid Earth. 1998. — V. 34, no. 1. — P. 52–58.
  4. А. А. Любушин. Прогноз Великого Японского землетрясения // Природа. 2012. — № 8. — С. 23–33.
    • A. A. Lyubushin. Prediction of Great Japanese Earthquake // Russian Nature. 2012. — no. 8. — P. 23–33. — in Russian.
  5. А. А. Любушин. Прогностические свойства случайных флуктуаций геофизических характеристик // Биосфера. 2014. — № 4. — С. 319–338.
    • A. A. Lyubushin. Prognostic properties of stochastic variations in geophysical parameters // Biosphere. 2014. — no. 4. — P. 319–338. — in Russian.
  6. А. А. Любушин. Статистики временных фрагментов низкочастотных микросейсм: их тренды и синхронизация // Физика Земли. 2010. — № 6. — С. 86–96.
    • A. A. Lyubushin. Statistiki vremennyh fragmentov nizkochastotnyh microseism: ih trendy i sinhronizaciya // Fizika Zemli. 2010. — no. 6. — P. 86–96. — in Russian.
    • A. A. Lyubushin. The statistics of the time segments of low-frequency microseisms: trends and synchronization // Izvestiya, Physics of the Solid Earth. 2010. — V. 46, no. 6. — P. 544–554. — DOI: 10.1134/S1069351310060091.
  7. А. А. Любушин, В. А. Малугин, О. С. Казанцева. Выделение «медленных событий» в асейсмическом регионе // Физика Земли. 1999. — № 3. — С. 35–44.
    • A. A. Lyubushin, V. A. Malugin, O. S. Kazantceva. Vydelenie “medlennyh sobytiy” v aseismicheskom regione // Fizika Zemli. 1999. — no. 3. — P. 35–44.
    • A. A. Lyubushin, V. A. Malugin, O. S. Kazantceva. Recognition of “Slow Events” in an Aseismic Region // Izvestiya, Physics of the Solid Earth. 1999. — V. 35, no. 3. — P. 195–203.
  8. С. Малла. Вейвлеты в обработке сигналов. — М: Мир, 2005.
    • S. Mallat. Veivlety v obrabotke signalov. — Moskva: Mir, 2005. — in Russian.
    • S. Mallat. A Wavelet Tour of Signal Processing. — San Diego, London, Boston, New York, Sydney, Tokyo, Toronto: Academic Press, 1999. — Second edition. — MathSciNet: MR1614527. — zbMATH: Zbl 0998.94510.
  9. Б. Мандельброт. Фракталы, случай и финансы. — М.–Ижевск: НИЦ «Регулярная и хаотическая динамика», 2004.
    • B. Mandelbrot. Fraktaly, sluchaj i finansy. — Moskva–Izhevsk: Regulyarnaya i haoticheskaya dinamika, 2004. — in Russian.
    • B. Mandelbrot. Fractales, hazard et finance. — Flammarion, 1997. — MathSciNet: MR0785362.
  10. Московская биржа акции [электронный ресурс]. http: //www.finam.ru/analysis/export/default.asp. — дата обращения: 06.02.2017.
  11. В. Ю. Протасов, Ю. А. Фарков. Диадические вейвлеты и масштабирующие функции на полупрямой // Матем. сб. 2006. — Т. 197, № 10. — С. 129–160. — zbMATH: Zbl 1214.42076.
    • V. Yu. Protasov, Yu. A. Farkov. Dyadic wavelets and refinable functions on a half-line // Mat. Sbornik. 2006. — V. 197, no. 10. — P. 129–160. — in Russian. — DOI: 10.4213/sm1126. — Math-Net: Mi eng/sm1126. — MathSciNet: MR2310119. — zbMATH: Zbl 1214.42076.
    • V. Yu. Protasov, Yu. A. Farkov. Dyadic wavelets and refinable functions on a half-line // Sbornik: Mathematics. 2006. — V. 197. — P. 1529–1558. — DOI: 10.1070/SM2006v197n10ABEH003811. — MathSciNet: MR2310119. — zbMATH: Zbl 1214.42076.
  12. Е. А. Родионов. О применениях вейвлетов к цифровой обработке сигналов // Известия Саратовского университета. Сер. Математика. Механика. Информатика. 2016. — Т. 16, № 2. — С. 217–225.
  13. G. E. P. Box, G. M. Jenkins, G. C. Reinsel, G. M. Ljung. Time Series Analysis: Forecasting and Control, 5th Edition. — John Wiley & Sons. Inc, 2016. — MathSciNet: MR3379415.
  14. E. Capobianco. Multiscale analysis of stock index return volatility // Computational Economics. 2004. — V. 23, no. 3. — P. 219–237. — DOI: 10.1023/B:CSEM.0000022834.86489.e5. — zbMATH: Zbl 1066.91079.
  15. H. Cramer. Mathematical Methods of Statistics. — Princeton University Press, 1999. — MathSciNet: MR1816288. — zbMATH: Zbl 0985.62001.
  16. D. L. Donoho, I. M. Johnstone. Adapting to Unknown Smoothness via Wavelet Shrinkage // Journal of the American Statistical Association. 1995. — V. 90, no. 432. — P. 1200–1224. — DOI: 10.1080/01621459.1995.10476626. — MathSciNet: MR1379464. — zbMATH: Zbl 0869.62024.
  17. J. Feder. Fractals. — New York, London: Plenum Press, 1988. — MathSciNet: MR0949210. — zbMATH: Zbl 0648.28006.
  18. V. Fernandez, M. Lucey. Portfolio management under sudden changes in volatility and hetero geneous investment horizons // Physica A: Statistical Mechanics and its Applications. 2007. — V. 375, no. 2. — P. 612–624. — DOI: 10.1016/j.physa.2006.10.004.
  19. M. Gallegati, W. Semmler. Wavelet applications in economics and finance. — Berlin: Springer, 2014. — zbMATH: Zbl 1298.91029.
  20. R. Gilmore. Catastrophe theory for scientists and engineers. — New York: John Wiley and Sons, Inc, 1981. — MathSciNet: MR0622545. — zbMATH: Zbl 0497.58001.
  21. F. In, S. Kim. An introduction to wavelet theory in finance. — Singapore: World Scientific, 2012. — MathSciNet: MR3236382.
  22. J. W. Kantelhardt, S. A. Zschiegner, E. Konscienly-Bunde, S. Havlin, A. Bunde, H. E. Stanley. Multifractal detrended fluctuation analysis of nonstationary time series // Physica A. 2002. — V. 316. — P. 87–114. — DOI: 10.1016/S0378-4371(02)01383-3. — zbMATH: Zbl 1001.62029.
  23. R. L. Kashyap, A. R. Rao. Dynamic stochastic models from empirical data. — New York; San Francisco; London: Acad. Press, 1976.
  24. H. Lee. International transmission of stock market movements: A wavelet analysis // Applied Economics Letters. 2004. — V. 11. — P. 197–201. — DOI: 10.1080/1350485042000203850.
  25. A. Lyubushin. Multifractal Parameters of Low-Frequency Microseisms / Synchronization and Triggering: from Fracture to Earthquake Processes, GeoPlanet: Earth and Planetary Sciences 1. — Chapter 15. — Verlag Berlin Heidelberg: Springer, 2010. — P. 253–272. — V. de Rubeis et al.
  26. A. Lyubushin. Prognostic properties of low-frequency seismic noise // Natural Science. 2012. — V. 4, no. 8. — P. 659–666. — DOI: 10.4236/ns.2012.428087.
  27. A. A. Lyubushin. Dynamic estimate of seismic danger based on multifractal properties of lowfrequency seismic noise // Natural Hazards. 2014. — V. 70, no. 1. — P. 471–483. — DOI: 10.1007/s11069-013-0823-7.
  28. G. Nicolis, I. Prigogine. Exploring complexity, an introduction. — New York: W. H. Freedman and Co, 1989.
  29. J. Perello, J. Masoliver, J.-P. Bouchaud. Multiple time scales in volatility and leverage correlations: A stochastic volatility model // Applied Mathematical Finance. 2004. — V. 11. — P. 27–50. — DOI: 10.1080/1350486042000196155. — zbMATH: Zbl 1093.91537.
  30. I. Osorio, A. Lyubushin, D. Sornette. Automated seizure detection: Unrecognized challenges, unexpected insights // Epilepsy & Behavior. 2011. — V. 22, no. 1. — P. S7–S17. — DOI: 10.1016/j.yebeh.2011.09.011.
  31. J. Ramsey, Z. Zhang. The analysis of foreign exchange data using waveform dictionaries. — C.V. Starr Center for Applied Economics Working paper New York University, 1995.
  32. C. Schleicher. An introduction to wavelets for economists. — Bank of Canada Working Paper, Toronto, 2002.
  33. A. Subbotin. A multi-horizon scale for volatility / CES Working Paper. — University of Paris-1, 2008. — 44 p. — 2008.20.
  34. J. Voit. The statistical mechanics of financial markets. — Berlin: Springer, 2005. — MathSciNet: MR2182114. — zbMATH: Zbl 1107.91055.

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