Gold, Cryptocurrency and Oil Adaptive Analysis and Forecasting

DOI

10.2991/assehr.k.210322.136How to use a DOI?

Keywords

Juglar cycles, Adaptive correlation coefficient, Cryptocurrency, Gold, Oil

Abstract

The work is devoted to identifying and tracking development trends, structural shifts in the economy under the influence of world markets, represented by non-stationary time series of gold, bitcoin and oil prices. The heuristic potential of the concept of the long and medium wave is used for forecasting purposes. The analysis of financial time series using the adaptive correlation coefficient is carried out. The dynamics of the traditional coefficient appears to be a significantly smoothed graph, which prevents sufficient qualitative analysis of the data. The results obtained are analysed to identify wave fluctuations, to determine the phases of growth, prosperity, recession and stagnation in the economy. An overview of the situation on the world markets for gold, bitcoin and oil based on the considered time series is presented. Based on the identified trends in the dynamics of these markets, short-term forecasting was carried out using ARIMA models and neural networks. The statistical calculations R environment is used.

Copyright

© 2021, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ilvira Khasanova
AU  - Lubov Orlik
AU  - Galina Zhukova
PY  - 2021
DA  - 2021/03/30
TI  - Gold, Cryptocurrency and Oil Adaptive Analysis and Forecasting
BT  - Proceedings of the VIII International Scientific and Practical Conference 'Current problems of social and labour relations' (ISPC-CPSLR 2020)
PB  - Atlantis Press
SP  - 345
EP  - 350
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.210322.136
DO  - 10.2991/assehr.k.210322.136
ID  - Khasanova2021
ER  -