NEAICVLGJun 3, 2021

Convolutional Neural Network(CNN/ConvNet) in Stock Price Movement Prediction

arXiv:2106.01920v13.05 citations
Originality Synthesis-oriented
AI Analysis

This is an incremental application of an existing method to a new domain (stock market prediction).

The paper tackles stock price movement prediction by constructing and training a convolutional neural network (CNN) on past stock price data, aiming to predict whether prices will rise or fall, but no concrete results or numbers are provided.

With technological advancements and the exponential growth of data, we have been unfolding different capabilities of neural networks in different sectors. In this paper, I have tried to use a specific type of Neural Network known as Convolutional Neural Network(CNN/ConvNet) in the stock market. In other words, I have tried to construct and train a convolutional neural network on past stock prices data and then tried to predict the movement of stock price i.e. whether the stock price would rise or fall, in the coming time.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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