Akciju cenu prognozēšana, izmantojot Relatīvo Spēka Indeksu un LSTM neironu tīklus
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Latvijas Universitāte
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lav
Abstract
Neironu tīkli akciju tirgus prognozēšanā sāk spēlēt arvien lielāku lomu. Darbā tiks skatīta relatīvā spēka indeksa (RSI) ietekme akciju cenu prognozēšanā, izmantojot garas īslaicīgās atmiņas (LSTM) neironu tīklus. Mērķis ir noskaidrot, vai RSI, LSTM neironu tīklu ievadē, spēj uzlabot nākotnes akciju cenas prognozi.
Neural networks` role in stock market predictions has increased in recent years. This work looks at relative strength index (RSI) influence in stock market predictions using long short-term memory (LSTM) neural networks. The goal of the study is to find out if RSI, as an input of LSTM neural networks, can improve the quality of stock price predictions.
Neural networks` role in stock market predictions has increased in recent years. This work looks at relative strength index (RSI) influence in stock market predictions using long short-term memory (LSTM) neural networks. The goal of the study is to find out if RSI, as an input of LSTM neural networks, can improve the quality of stock price predictions.