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International Research Journal of Modernization in Engineering Technology & Scienceopenaire +1 more source
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International Scientific Journal of Engineering and Management, 2022
This project develops a machine learning solution for predicting flight ticket prices, aiding users in identifying optimal travel times and cost-effective options. The predictive model is trained on extensive Kayak flight data for various international routes (NYC, PAR, RUH, SVO) from Feb-Apr 2022.
CH. S S YESWANTH, R. BHANU SANKAR
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This project develops a machine learning solution for predicting flight ticket prices, aiding users in identifying optimal travel times and cost-effective options. The predictive model is trained on extensive Kayak flight data for various international routes (NYC, PAR, RUH, SVO) from Feb-Apr 2022.
CH. S S YESWANTH, R. BHANU SANKAR
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Predicting Prescription Prices
New England Journal of Medicine, 1967A DELUGE of articles on prescription-drug pricing has recently issued from both the lay and the professional press.
G E, Hastings, R, Kunnes
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SSRN Electronic Journal, 2021
Abstract We demonstrate that predictable uninformed cash flows forecast market and individual stock returns. Buying pressure from dividend payments (announced weeks prior) predicts higher value-weighted market returns, four times greater on the top quintile of payment days than the lowest.
Samuel Hartzmark, David H. Solomon
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Abstract We demonstrate that predictable uninformed cash flows forecast market and individual stock returns. Buying pressure from dividend payments (announced weeks prior) predicts higher value-weighted market returns, four times greater on the top quintile of payment days than the lowest.
Samuel Hartzmark, David H. Solomon
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2023
In this study, the last two years' hourly opening and closing prices of the banks' stocks traded on BIST-30 were used as the dataset. The research is aimed to predict the closing prices of these stocks in the light of machine learning. In this context, the authors propose a new method containing ensemble learning algorithms and fuzzy clustering ...
Ahmet Tezcan Tekin +2 more
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In this study, the last two years' hourly opening and closing prices of the banks' stocks traded on BIST-30 were used as the dataset. The research is aimed to predict the closing prices of these stocks in the light of machine learning. In this context, the authors propose a new method containing ensemble learning algorithms and fuzzy clustering ...
Ahmet Tezcan Tekin +2 more
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YMER Digital, 2022
Machine learning has many important applications in the stock price prediction. Here, we will discuss about predicting the returns on stocks. This has uncertainties and it is a very complex task. This project will be developed into two parts: First, we will learn how to predict stock price using the Long Short-Term Memory neural networks.
V BIKSHAM +4 more
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Machine learning has many important applications in the stock price prediction. Here, we will discuss about predicting the returns on stocks. This has uncertainties and it is a very complex task. This project will be developed into two parts: First, we will learn how to predict stock price using the Long Short-Term Memory neural networks.
V BIKSHAM +4 more
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2022
Abstract—Gold is often used by investors as a barrier against inflation or adverse economic times. As a result, it is critical for investors to be able to accurately estimate gold prices. This article is based on a study of gold price prediction by relationship between gold price and selected factors influencing it , namely date, stock value, current ...
Liyan Susan Kurian, Merin Chacko
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Abstract—Gold is often used by investors as a barrier against inflation or adverse economic times. As a result, it is critical for investors to be able to accurately estimate gold prices. This article is based on a study of gold price prediction by relationship between gold price and selected factors influencing it , namely date, stock value, current ...
Liyan Susan Kurian, Merin Chacko
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YMER Digital, 2022
Because house prices rise every year, a mechanism to forecast future house values is required. House price prediction can help the developer determine the selling price of a house and can help the customer to arrange the right time to purchase a house. Physical conditions, concept, and location are only a few of the aspects that determine the price of ...
V Vijay Bhasker Reddy +4 more
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Because house prices rise every year, a mechanism to forecast future house values is required. House price prediction can help the developer determine the selling price of a house and can help the customer to arrange the right time to purchase a house. Physical conditions, concept, and location are only a few of the aspects that determine the price of ...
V Vijay Bhasker Reddy +4 more
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eLearning and Software for Education, 2020
E-learning, in most contexts, is becoming a more accessible and efficient method of training through which people could acquire new knowledge. Due the difference between epochs, reading and analysing the growing flow of information has become a very challenging task for financial professionals.
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E-learning, in most contexts, is becoming a more accessible and efficient method of training through which people could acquire new knowledge. Due the difference between epochs, reading and analysing the growing flow of information has become a very challenging task for financial professionals.
openaire +1 more source