In this analysis we investigated the reliability of Stochastic Differential Equations (SDE) in forecasting stock prices on a hhort time period in a simplified framework. Four different SDE models were used, each applied on stocks of companies listed on NASDAQ and validated in each month between July 2022 and January 2023. Both the coverage of the confidence intervals estimates and the reliability of the average behaviour estimates were checked. Results show an overall good reliability for stocks with a strong expected percentage increase (above 3%).
Stocks price forecasts using Stochastic Differential Equations: an empirical assessment / Frisardi, Dario; Spuri, Matteo. - (2023), pp. 355-360. (Intervento presentato al convegno SIS 2023 - Statistical Learning, Sustainability and Impact Evaluation tenutosi a Ancona, Italy).
Stocks price forecasts using Stochastic Differential Equations: an empirical assessment
Dario FrisardiCo-primo
;Matteo SpuriCo-primo
2023
Abstract
In this analysis we investigated the reliability of Stochastic Differential Equations (SDE) in forecasting stock prices on a hhort time period in a simplified framework. Four different SDE models were used, each applied on stocks of companies listed on NASDAQ and validated in each month between July 2022 and January 2023. Both the coverage of the confidence intervals estimates and the reliability of the average behaviour estimates were checked. Results show an overall good reliability for stocks with a strong expected percentage increase (above 3%).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
