In this notebook, we will discover and explore data from the stock market, particularly some technology stocks (Apple, Amazon, Google, and Microsoft). We will learn how to use yfinance to get stock information, and visualize different aspects of it using Seaborn and Matplotlib. we will look ...
This paper presents the extension and application of three predictive models to time series within the financial sector, specifically data from 75 companies on the Mexican stock exchange market. A tool, which generates awareness of the potential benefits obtained from using formal financial services, ...
Hybrid Intelligent Systems for Stock Market Analysis The predicted stock values are further fed to a neuro-fuzzy system to analyze the trend of the market. The forecasting and trend prediction results using the proposed hybrid system are promising and certainly warrant further research and... A ...
Stock market decision making is a very challenging and difficult task of financial data prediction. Prediction about stock market with high accuracy movement yield profit for investors of the stocks. Because of the complexity of stock market financial data, development of efficient models for prediction...
The generation of profitable trading rules for stock market investments is a difficult task but admired problem. First stage is classifying the prone direction of the price for BSE index (India cements stock price index (ICSPI)) futures with several technical indicators using artificial intelligence ...
Chapter 4 Stock Market Prediction from Sectoral Indices using an Adaptive Network Based Fuzzy Inference SystemThe effect of different variables on the stock ... 被引量: 0发表: 2018年 A Smart Antenna Module Using OMNeT++ for Wireless Sensor Network Simulation We introduce a smart antenna (SA) mo...
Today I said a prediction in advance: the Shenzhen Composite Index will rise for two months, October and November. We'll verify it in two months. In February, I predicted that the stock market woul...
Secondly, Support Vector Machine is used in analyzing the relationship of these factors and predicting the stock performance. Our results suggest that SVM is a powerful predictive tool for stock predictions in the financial market. 展开 关键词: multivariate classification stock classification data mining...
The stock market contains rich, valuable and considerable data, and these data need careful analysis for good decisions to be made that can lead to increases in the efficiency of a business. Data mining techniques offer data processing tools and applications used to enhance decision-maker decisions...
The research presented in this work focuses on financial time series prediction problem. The integrated prediction model based on support vector machines (SVM) with independent component analysis (ICA) (called SVM-ICA) is proposed for stock market prediction. The presented approach first uses ICA tec...