Detection and forecasting of extreme events in stock price triggered by fundamental, technical, and external factors

Rai, Anish; Luwang, Salam Rabindrajit; Nurujjaman, Md.; Hens, Chittaranjan; Kuila, Pratyay; Debnath, Kanish

doi:10.1016/j.chaos.2023.113716

Cited by 7 publications

(1 citation statement)

References 51 publications

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“…Several studies predict the movement of a company's stock price [19], predictions are made using SVM and generate RMSE of 20,281, as well as research [20] which examines stock prices of shipping companies using linear regression and produces RMSE of 7,522, as well as research [1], [21], [22], [23] which predicts the sentiment of analysts on stock prices that use SVM which produces low data.…”

Section: Introductionmentioning

confidence: 99%

Optimization Selection on Deep Learning Algorithm for Stock Price Prediction in Indonesia Companies

Gunawan,

Andriani,

Anandianskha

et al. 2024

SJI

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Purpose: Share price movements after the COVID-19 pandemic experienced a decline in several sectors, especially in the share prices of the Aneka Tambang Company, which operates in the mining sector, the Wijaya Karya Company in the construction sector, and the Sinar Mas Company, which is a Holding Company. Several factors influence this, including investors' hesitation in investing their money. This research aims to predict stock price movements using a Deep Learning algorithm, which is optimized using Selection optimization at three large companies in Indonesia, namely PT. ANTAM, PT. WIKA, and PT. SINAR MAS. So that it can provide the correct information to investors to avoid losses.Method: research through collecting data from the three companies, preprocessing, and then analyzing research data with several alternatives. The combination of inputs from the three companies using the deep learning method is then optimized using selection optimization to produce the best accuracy and use the results of the RMSE evaluation.Results: The results of this research show that by using the Deep Learning method, the best evaluation results were obtained for the Company PT Wijaya Karya with an RMSE value of 0.432, an MAE value of 0.31505 and an MSE value of 1913.953. These results were then optimized using Selection optimization to obtain an RMSE increase of 0.022, namely 0.410.Novelty: The contribution of this research is to get the best combination of input variables obtained using the windowing process from the three companies, which are then processed using the Deep Learning method to produce the most accurate evaluation results from the three companies, then the results are optimized again using Selection optimization to get the more optimal results.

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