Deep Learning for Equity Time Series Prediction

MNi, Alonso; Batres-Estrada, Gilberto; Moulin, Aymeric

doi:10.2139/ssrn.3735940

Cited by 2 publications

(2 citation statements)

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“…It was discovered that the predicted price fit the actual price more closely when historical data and economic indicators were used as input [25]. A comparative study was conducted using Deep Feed Forward Neural Networks (DNN), Long Short Term Memory Networks (LSTM), Gated Recurrent Unit Networks (GRU), and Recurrent Neural Networks (RNN) deep learning models out of which LSTM performed better than others [26].…”

Section: Literature Reviewmentioning

confidence: 99%

A Comparative study of the Envisaged and Definite Stock Prices of BSE SMEs Using RNN during the COVID-19 Pandemic

Kaur,

Munde,

Goyal

2024

jour

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The stock market is unstable, but the use of machine learning algorithms allows to predict its future dynamics before spending. The most popular area of scientific research right nowadays is machine learning, which involves enabling computers to perform tasks that often require human intelligence. The purpose of this paper is to construct a model using a network of Long-Short Term Memory model (LSTM) to forecast future stock market values. The paper presents the advantages and disadvantages of machine learning for assessing and forecasting the stock market. A review of literature on the application of machine learning models in key areas of finance using methodological model assessment and data manipulation is also available. This paper focuses on the losses of the SME sector due to COVID-19 by doing a comparative study using secondary data collection between the predicted closed stock prices and actual stock prices of the BSE SME IPO index for the period from 1 January 2018 to 30 April 2021.The LSTM network of Recurrent Neural Networks (RNNs) most effective deep learning model, is used to predict stock prices. The study provides insight and direction on where lockdown has a massive impact on the stock prices of BSE SME IPOs. The authors developed a model for predicting the future value of stock in the market, the application of which gave some positive results, demonstrating the need for machine learning and how it can change the world of finance. The novelty of the study is that in India, machine learning and deep learning methods in the field of finance are used much less often than in other countries.

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Section: Literature Reviewmentioning

confidence: 99%

A Comparative study of the Envisaged and Definite Stock Prices of BSE SMEs Using RNN during the COVID-19 Pandemic

Kaur,

Munde,

Goyal

2024

jour

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“…Therefore, the combination of AI and finance is undoubtedly a very attractive thing. Up to now, many countries and enterprises have begun to combine finance and AI and give full play to the characteristics of AI [3]. The high computing and working ability of artificial intelligence has become a very good substitute for human labor.…”

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confidence: 99%

The Combination of AIs Powerful Data Algorithm Capability and Finance

Huang

2023

AEMPS

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The way many industries function is changing as a result of the advancement of artificial intelligence technology. Under the influence of the digital revolution, the financial industry has seen significant changes and advancements. This paper will explore some specific impacts on the financial data industry from the role of AI in modern society and the expansion of various industries. It is mainly used to explore whether AI really plays an irreplaceable role in the field of finance and related data, as well as its advantages and disadvantages. Through the practical application of AI-related technology, as well as the reflection of the industry being used by people today, the importance of AI is explored by some examples. AI's role in today's world, especially in related fields such as finance, is undoubtedly very important, but there are still many risks that people need to pay attention to.

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Deep Learning for Equity Time Series Prediction

Cited by 2 publications

References 0 publications

A Comparative study of the Envisaged and Definite Stock Prices of BSE SMEs Using RNN during the COVID-19 Pandemic

A Comparative study of the Envisaged and Definite Stock Prices of BSE SMEs Using RNN during the COVID-19 Pandemic

The Combination of AIs Powerful Data Algorithm Capability and Finance

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