Using R/S analysis for forecasting stock quotes with ARMA and ARIMA methods : доклад, тезисы доклада

Stupina Alena; Zinenko Anna

Дополнительные ссылки: eLibrary · Источник статьи

База данных: Каталог библиотеки СФУ

Библиографическое описание: Using R/S analysis for forecasting stock quotes with ARMA and ARIMA methods : доклад, тезисы доклада / A. A. Stupina, A. A. Zinenko. - [S. l. : s. n.], 2025. - Текст : непосредственный // ITM Web of Conferences : III International Workshop / Hybrid Methods of Modeling and Optimization in Complex Systems (HMMOCS-III 2024) (2024 ; 02.12 - 04.12 ; Krasnoyarsk). - Krasnoyarsk, 2025. - P. 4009. - This work was supported by the Ministry of Science and Higher Education of the Russian Federation (Grant No.075-15-2022-1121). - DOI 10.1051/itmconf/20257204009.

Аннотация: The article observes the methods of forecasting time series Autoregressive Moving Average Model (ARMA) and Integrated Autoregressive Moving Average Model (ARIMA). The ARIMA model differs from the ARMA model only in that forecasting is performed not on absolute values of series levels, but on differences of order d, which makes it possible to apply to non-stationary time series. Financial time series are traditionally considered non-stationary. However, the Hurst exponent less than or equal to 0.5 indicates a random or anti-persistent nature of time series. The paper assumes that for random or anti-persistent time series according to Hurst, there is no need to take differences and it is sufficient to apply the ARMA model for forecasting. To test the hypothesis, we carried out forecasts of leading world indices stocks and currency pairs with the Hurst exponent less than or equal to 0.5 for 10 years using the ARMA and ARIMA methods and compared the results using the MAPE metric. According to the ARMA method forecasts, in most cases the error was smaller, that confirmed the initial hypothesis.

Год издания: 2025

Авторы: Stupina Alena , Zinenko Anna

Издательство: Krasnoyarsk

Источник: ITM Web of Conferences

Номера страниц: 4009

Держатель оригинала документа: Siberian Federal University

Мероприятие: Hybrid Methods of Modeling and Optimization in Complex Systems (HMMOCS-III 2024) (Krasnoyarsk, 2024 ; 02.12 - 04.12)

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Using R/S analysis for forecasting stock quotes with ARMA and ARIMA methods : доклад, тезисы доклада
доклад, тезисы доклада, статья из сборника материалов конференций

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