Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
Exploring the Quotation Inertia in International Currency Markets. / Мусаев, Александр Азерович; Макшанов, Андрей; Григорьев, Дмитрий Алексеевич.
в: Computation, Том 11, № 11, 209, 24.10.2023.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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TY - JOUR
T1 - Exploring the Quotation Inertia in International Currency Markets
AU - Мусаев, Александр Азерович
AU - Макшанов, Андрей
AU - Григорьев, Дмитрий Алексеевич
PY - 2023/10/24
Y1 - 2023/10/24
N2 - The authors suggest a methodology that involves conducting a preliminary analysis of inertia in financial time series. Inertia here means the manifestation of some kind of long-term memory. Such effects may take place in complex processes of a stochastic kind. If the decision is negative, they do not recommend using predictive management strategies based on trend analysis. The study uses computational schemes to detect and confirm trends in financial market data. The effectiveness of these schemes is evaluated by analyzing the frequency of trend confirmation over different time intervals and with different levels of trend confirmation. Furthermore, the study highlights the limitations of using smoothed curves for trend analysis due to the lag in the dynamics of the curve, emphasizing the importance of considering real-time data in trend analysis for more accurate predictions.
AB - The authors suggest a methodology that involves conducting a preliminary analysis of inertia in financial time series. Inertia here means the manifestation of some kind of long-term memory. Such effects may take place in complex processes of a stochastic kind. If the decision is negative, they do not recommend using predictive management strategies based on trend analysis. The study uses computational schemes to detect and confirm trends in financial market data. The effectiveness of these schemes is evaluated by analyzing the frequency of trend confirmation over different time intervals and with different levels of trend confirmation. Furthermore, the study highlights the limitations of using smoothed curves for trend analysis due to the lag in the dynamics of the curve, emphasizing the importance of considering real-time data in trend analysis for more accurate predictions.
UR - https://www.mendeley.com/catalogue/9a00e90f-aa77-344f-a651-f57715dfc71e/
U2 - 10.3390/computation11110209
DO - 10.3390/computation11110209
M3 - Article
VL - 11
JO - Computation
JF - Computation
SN - 2079-3197
IS - 11
M1 - 209
ER -
ID: 111854584