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Stake is not authorised by Airwallex under Airwallex’s AFSL to arrange for clients to be issued with securities as Airwallex is not authorised under its AFSL for this purpose. 1241398) of Airwallex Pty Ltd (Australian Financial Services Licence No. 337927) ('Sanlam') and an authorised representative (Authorised Representative No. 1241398) of Sanlam Private Wealth Pty Ltd (Australian Financial Services Licence No. Experimental results on stock datasets of the Chinese Stock Market and the American Stock Market demonstrate that the proposed method improves the accuracy of prediction.Stakeshop Pty Ltd, trading as Stake, ACN 610105505, is an authorised representative (Authorised Representative No. Finally, the VML model merges the prediction results of the subseries to obtain the final predicted stock price. The initial parameters enable LSTM to fine tune dynamically to fit the latest data distribution of stock price data, which mitigates the impact of concept drift on prediction accuracy. A method of dividing the decomposed subseries into multiple tasks is proposed for the purpose of utilizing the MAML algorithm to train the initial parameters of the LSTM with good generalization ability. Next, model-agnostic meta-learning (MAML) algorithm and long short-term memory (LSTM) network are applied to predict the subseries.
Unlike existing decomposition-based methods, VML decomposes the window series to solve the data leakage problem. First, the VML model slices the stock price series to obtain multiple window series, then uses variational mode decomposition (VMD) to decompose the window series to obtain multiple subseries. To improve the prediction accuracy and obtain better prediction results, a new stock price prediction model called VML is proposed in this paper. Correct forecasting results can provide valuable guidance to investors and thus reduce the investment risk. Stock price prediction is an important and challenging research topic, which has wide application prospects.
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