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23 results for “Price Prediction”
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Research ArticleOpen accessIn the abstractA Dynamic Lifelong Learning Network for Real-Time Stock Prediction With Reinforcement TuningTalent Mawere, Selvaraj Rajalakshmi, Venu Madhav Kuthadi, Otlhapile DinakanyaneCompanies and investors require accurate market forecasting to make more informed decisions. Traditional methods for predicting stock market performance have become less useful considering the dynamic and volatile nature that characterizes stock markets today. In this paper, we propose an innovative Dynamic Lifelong Learning Network for stock market prediction. The model incorporates a hybrid convolutional long short-term memory with an … …Journal of Computer Science, Vol. 22, Issue 2 · 20 Feb 2026 · 1,822 accessesView PDFCite
Research ArticleOpen accessIn the abstractIraqi Stock Market Prediction using Proposed Model of Convolution Neural NetworkSama Hayder Abdulhussein, Nashaat Jasim Al-Anber, Hayfaa Abdulzahra AteeThe stock market, sometimes known as the share market, is a marketplace for stock sellers and buyers. A stock exchange is defined as a mechanism through which stockbrokers can purchase and sell shares, bonds, and other assets. Many businesses, regardless of their industries or domains, make their shares or stocks available on the stock exchange. For value investors, predicting the … …Journal of Computer Science, Vol. 18, Issue 5 · 23 May 2022 · 6,530 accessesView PDFCite
Research ArticleOpen accessIn the abstractModel Comparison for the Prediction of Stock Prices in the NYSEVictoria Switlyk, Junfeng ShangThe stock market is an integral part of investments as well as the economy. The prediction of stock prices is an exciting and challenging problem that has been considered by many due to the complexity and noise within the market and to the potential profit that can be yielded from accurate predictions. We aim to construct and compare models used … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 26 Sep 2019 · 7,475 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandom Forest Based Feature Selection of Macroeconomic Variables for Stock Market PredictionIsaac Kofi Nti, Adebayo Felix Adekoya, Benjamin Asubam WeyoriA firm’s equity price on the stock-market is reported to be closely related to the Macroeconomic Variable (MVs) of the country in which the firm trades. For this reason, researchers, market traders, financial analysts and forecasters to examine the association between MVs and stock-price have carried out numerous studies, using time-series statistical analysis methods like Autoregressive Integrated Moving Average (ARIMA), … …American Journal of Applied Sciences, Vol. 16, Issue 7 · 31 Jul 2019 · 10,234 accessesView PDFCite
EditorialOpen accessIn the abstractProtecting crop species from biotic and abiotic constraints in the era of Global Change: are we ready for this challenge?Marco Landi, Giovanni BenelliReliable and affordable supply of food is of crucial importance to the progress and stability of human societies. During the last century, we have assisted to an extraordinary increase of crop yields, especially for the most widespread and consumed crop species, such as rice, wheat, corn and soybean. The Broadbalk experiment, one of the oldest continuous agronomic experiments in the … …American Journal of Agricultural and Biological Sciences, Vol. 11, Issue 2 · 4 Jun 2016 · 8,399 accessesView PDFCite
Literature ReviewOpen accessIn the abstractOverview and Future Opportunities of Sentiment Analysis Approaches for Big DataNurfadhlina Mohd Sharef, Harnani Mat Zin, Samaneh NadaliThe ability to exploit public sentiment in social media is increasingly considered as an important tool for market understanding, customer segmentation and stock price prediction for strategic marketing planning and manoeuvring. This evolution of technology adoption is energised by the healthy growth in big data framework, which caused applications based on Sentiment Analysis (SA) in big data to become common … …Journal of Computer Science, Vol. 12, Issue 3 · 26 Apr 2016 · 10,313 accessesView PDFCite
Research ArticleOpen accessIn the abstractFUZZY MODEL OPTIMIZATION FOR TIME SERIES DATA USING A TRANSLATION IN THE EXTENT OF MEAN ERRORNurhayadi, Subanar, Abdurakhman, Agus Maman AbadiRecently, many researchers in the field of writing about the prediction of stock price forecasting, electricity load demand and academic enrollment using fuzzy methods. However, in general, modeling does not consider the model position to actual data yet where it means that error is not been handled optimally. The error that is not managed well can reduce the accuracy of … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 2 Jun 2014 · 6,733 accessesView PDFCite
Research ArticleOpen accessIn the abstractEURO-USD PREDICTION APPLICATION USING WEIGHTED MOVING AVERAGE ON MOBILE DEVICEAfan Galih Salman, Ro’fah Nur Rachmawati, HendryInvestments in foreign exchange (forex) promise lucrative profits, thus inviting a lot of attention for researcher sand traders to create a system or indicator in trading. All indicators or system is reliable and has proven hat can bring profit for traders. Basically all indicator are reliable and tested which able to bring some profit to traders. Ironically there are many … …Journal of Computer Science, Vol. 10, Issue 9 · 17 Apr 2014 · 7,457 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance of Multiple Linear Regression and Nonlinear Neural Networks and Fuzzy Logic Techniques in Modelling House PricesSiti Amri, Gurudeo Anand TularamHouse price prediction continues to be important for government agencies insurance companies and real estate industry. This study investigates the performance of house sales price models based on linear and non-linear approaches to study the effects of selected variables. Linear stepwise Multiple Regression (MR) and nonlinear models of Neural Network (NN) and Adaptive Neuro-Fuzzy (ANFIS) are developed and compared. The … …Journal of Mathematics and Statistics, Vol. 8, Issue 4 · 18 Dec 2012 · 8,430 accessesView PDFCite
Research ArticleOpen accessIn the abstractDesign and Implementation of Novel Artificial Neural Network Based Stock Market Forecasting System on Field-Programmable Gate ArraysMd. Syedul Amin, Md. Mamun, Fazida Hanim Hashim et al.Problem statement: Multiagent system is very proficient and has rules well-suited for financial forecast with its neural network. In financial forecasting, the approach for rules extractions is less pertinent and involves algorithms which are complex. The unsupervised network method lacks in comprehensibility and leads to ambiguity. Approach: The application of neural network technology to real-time processing of financial market analysis … …American Journal of Applied Sciences, Vol. 8, Issue 10 · 12 Sep 2011 · 7,627 accessesView PDFCite