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Recurrence Interval Analysis of Financial Time Series [Hardback]

(East China University of Science and Technology), (East China University of Science and Technology), (East China University of Science and Technology)
  • Formāts: Hardback, 86 pages, height x width x depth: 235x160x10 mm, weight: 273 g, Worked examples or Exercises
  • Sērija : Elements in Econophysics
  • Izdošanas datums: 21-Mar-2024
  • Izdevniecība: Cambridge University Press
  • ISBN-10: 1009486616
  • ISBN-13: 9781009486613
Citas grāmatas par šo tēmu:
  • Hardback
  • Cena: 74,22 €
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  • Formāts: Hardback, 86 pages, height x width x depth: 235x160x10 mm, weight: 273 g, Worked examples or Exercises
  • Sērija : Elements in Econophysics
  • Izdošanas datums: 21-Mar-2024
  • Izdevniecība: Cambridge University Press
  • ISBN-10: 1009486616
  • ISBN-13: 9781009486613
Citas grāmatas par šo tēmu:
This Element aims to provide a systemic description of the techniques and research framework of recurrence interval analysis of financial time series. The authors also provide perspectives on future topics in this direction.

Extreme events are ubiquitous in nature and social society, including natural disasters, accident disasters, crises in public health (such as Ebola and the COVID-19 pandemic), and social security incidents (wars, conflicts, and social unrest). These extreme events will heavily impact financial markets and lead to the appearance of extreme fluctuations in financial time series. Such extreme events lack statistics and are thus hard to predict. Recurrence interval analysis provides a feasible solution for risk assessment and forecasting. This Element aims to provide a systemic description of the techniques and research framework of recurrence interval analysis of financial time series. The authors also provide perspectives on future topics in this direction.

Papildus informācija

Provides a detailed description of the techniques and research framework of recurrence interval analysis of financial time series.
1. Introduction;
2. Recurrence interval distributions;
3. Memory effects;
4. Risk estimation and forecasting;
5. Empirical results and theoretical analyses;
6. Final remarks; References.