Evaluation reveals great accuracy of k-Nearest Neighbors regression in forecasting Jakarta Composite Index, indicating its potential in financial time series prediction.
This paper aims to evaluate the accuracy of the k-Nearest Neighbors regression method in predicting the Jakarta Composite Index (JCI), thus adding evidence of the application of k-NN regression in predicting noisy financial time series data. The dataset consists of daily data from several time series variables in 2022. The result suggests that the accuracy of k-NN regression in predicting JCI fluctuation is very good, indicated by Mean Absolute Percentage Error (MAPE) being less than 2% for k = 2, 3, …, 10.
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Najibullah et al. (2024) studied this question.
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