Stock market prediction using artificial neural networks in python /
Title
Stock market prediction using artificial neural networks in python /
Subject
Stock Market
Description
Patent Number: 202231052415, Applicant: Dr. Rashel Sarkar.
When the issue of forecasting time series is mentioned, the reader, listener, or observer instantly considers forecasting stock prices. This should help individuals determine when to sell and when to purchase more. On occasion, we encounter resources that explain how this is possible. Throughout Deep Learning with Python, Chollet cautions against using time series prediction algorithms to estimate market values. You should not attempt to predict how the stock market will behave in the future based on past performance. Due to the design of the martingale system, the present price of a share of stock is the most accurate indicator of its future price (in terms of the error associated with estimation).
When the issue of forecasting time series is mentioned, the reader, listener, or observer instantly considers forecasting stock prices. This should help individuals determine when to sell and when to purchase more. On occasion, we encounter resources that explain how this is possible. Throughout Deep Learning with Python, Chollet cautions against using time series prediction algorithms to estimate market values. You should not attempt to predict how the stock market will behave in the future based on past performance. Due to the design of the martingale system, the present price of a share of stock is the most accurate indicator of its future price (in terms of the error associated with estimation).
Creator
Ganguly, Deeksha Gupta.
Publisher
Intellectual Property India
Date
2022
Language
English
Type
Patent
Collection
Citation
Ganguly, Deeksha Gupta., “Stock market prediction using artificial neural networks in python /,” CHRIST (Deemed To Be University) Institutional Repository, accessed December 23, 2024, https://archives.christuniversity.in/items/show/2773.