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17 articles for “stock market”
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Stock Market Analysis Using Data Science
Abstract: Stock market prediction using data science has become a popular area of research and application in recent years. This is because the stock market is a complex system with many variables and factors that affect its behavior, making it difficult to predict with certainty. The stock market has always been the aggression of buyers and sellers of stocks, therefore in the global finance market, stock trading is one of the …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 1, 2024 · pp. 1–4 Read article
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Stock Market Prediction Using Machine Learning: Techniques, Challenges, and Future Directions
Abstract: The continuous advancement of machine learning (ML) technologies has significantly transformed the field of financial forecasting, particularly in the area of stock market prediction. The ability to accurately forecast stock price movements and market trends plays a crucial role in supporting informed investment strategies and effective risk management. This paper provides a comprehensive review of recent developments in the application of ML techniques for predicting stock market behavior. It classifies …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 1, 2026 · pp. 10–16 Read article
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Designing an AI-Based Platform for Stock Market Prediction
Abstract: The AI-Based Platform for Stock Market Prediction is an advanced tool designed to forecast stock prices and market trends using artificial intelligence. This platform combines machine learning algorithms, real-time financial data, and sentiment analysis to provide investors with actionable insights. The platform uses advanced predictive techniques like Long Short-Term Memory (LSTM) networks and Gradient Boosting Machines to generate precise and reliable forecasts. Additionally, it incorporates interactive visualizations and portfolio optimization …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 3, 2025 · pp. 14–19 Read article
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A Linear Regression Model Used to Analysis the Tesla Stock Price Prediction Using Machine Learning
Abstract: The stock market is a fascinating sector of the economic research. It comes in a number of varieties. Several specialists have been examining and investigating the several patterns that the stock market experiences fluctuations. Predicting the stock values of different companies using historical data has been one of the primary research projects. Stock price prediction can help people a great deal by helping them understand where and how to invest, …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 2, 2024 · pp. 8–13 Read article
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Sustaining Investing with SIP: Nurturing Wealth and a Better Future
Abstract: Sustainable Investing with SIP encapsulates the idea of aligning financial goals with responsible investing practices for a more sustainable and prosperous future. SIP (Systematic Investment Plan) signifies a disciplined and systematic approach to investing, where individuals commit to regular contributions towards mutual funds at set intervals, fostering a sustainable and long-term investment strategy. Wealth accumulation implies the gradual growth and nurturing of wealth over time through SIP, emphasizing the patient …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 1, 2024 · pp. 30–35 Read article
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Exploring the Efficiency of Leading and Lagging Indicators in Algorithmic Trading
Abstract: This paper details a comparison of the overall performance of leading and lagging technical indicators used in algorithmic trading over an extended period. While much of the prior research focuses on index price forecasting and some on statistical arbitrage derived from these predictive techniques, there is a scarcity of studies that assess and evaluate trading strategies. The strategies considered for the study were tested on historical data of the 50 …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 8–18 Read article
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Risk Return Analysis Of Pharmaceuticals Companies During Covid-19
Abstract: An unknown disease (COVID-19) is spreading globally, impacting people and economies very negatively. The virus, which was first discovered in a small part of China in December 2019, has since grown fast across more than 175 countries. The virus is very contagious, thus in order to stop it, certain measures have been put in place, such as a national shutdown, air traffic control, and the wearing of masks, avoidance of …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 1, 2024 · pp. 1–6 Read article
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Curbing Speculation vs. Market Participation: A Study of SEBI’s 2024 Derivatives Measures
Abstract: The derivative market has become a cornerstone of India’s financial ecosystem, complementing the traditional stock market by enabling risk management, price discovery, and liquidity enhancement. However, with the rapid growth of this segment, concerns over speculative activities have prompted regulatory intervention. On October 1, 2024, the Securities and Exchange Board of India (SEBI) introduced significant reforms aimed at curbing speculation, protecting retail investors, and fostering market stability. While these changes …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 2, 2025 · pp. 28–43 Read article
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Enhancing Mutual Fund Investment Decision-making Using Machine Learning: A Survey
Abstract: In India, a significant portion of individuals save a part of their income for a secure future. Government and various public sector financial companies also provide some saving schemes through banks, post offices, and Life Insurance Corporation (LICs) such as Recurring Deposit (RD), Public Provident Fund (PPF), Sukanya Samridhhi Account (SSA) fixed deposits, etc. Over the past decade, many individuals have shifted their saving schemes to vigorously searching for investment …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 1, 2024 · pp. 43–51 Read article
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Harnessing Machine Learning for Stock Movement Prediction: A Review of Current Approaches
Abstract: Stock price prediction is a crucial task in financial analysis, aiding investors and traders in making informed decisions. This study investigates the use of deep learning methods, particularly Long Short-Term Memory (LSTM) networks, for predicting stock prices based on historical market data. The dataset, sourced from Yahoo Finance, consists of time-series stock price data, which is preprocessed, feature-engineered, and visualized to improve prediction accuracy. The model's performance is assessed using …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 29–40 Read article
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 Read article
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Fundamental Analysis of Mid-Cap Stocks in the Indian IT Sector
Abstract: Fundamental analysis is also needed for the classification of financial assets (stocks, bonds, and currencies) using economic indicators or valuation methods to determine their true value. The present study focuses on mid-cap stocks in the information technology (IT) sector of the Indian market, which includes sectors such as software development, hardware manufacturing, semiconductors, IT services, internet and e-commerce, telecommunications, cybersecurity, and cloud computing. Mid-cap stocks may offer a good mix …
Published in Current Trends in Information Technology · Vol. 15, Issue 1, 2025 · pp. 1–11 Read article
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Analysis of Gold Price Trend Using the Hidden Markov Model
Abstract: This study aims to analyze the behavior of gold prices in India through a two-state Hidden Markov Model (HMM). We first formulated crucial parameters, such as the Transition Probability Matrix (TPM), Initial Probability Vector (IPV), and Emission Probability Matrix (EPM). Subsequently, we constructed a hidden Markov probability distribution and evaluated Pearson’s coefficients to gauge the correlations separately for each state. The goodness of fit of the developed model was assessed …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 2, 2024 · pp. 7–16 Read article
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Deep Learning Architectures for Predictive Modeling in Financial Time Series
Abstract: This study investigates the application of deep learning architectures, particularly convolutional neural networks (CNNs), to the challenging task of financial time series forecasting. Financial markets are inherently complex and influenced by a range of factors, making accurate prediction of price movements a difficult problem. In this research, historical financial data including stock prices, volumes, and other relevant indicators are used to train CNN models aimed at capturing the underlying patterns …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 45–55 Read article
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E-Commerce and AI: Product Recommendation and Pricing
Abstract: E-commerce has evolved from a simple online storefront to a complex ecosystem driven by data and demanding personalized experiences. In this highly competitive environment, businesses are continuously looking for new ways to entice and keep customers. Artificial intelligence is growing as an effective instrument, offering a multitude of applications that are transforming the e-commerce industry. This study will look at the important areas wherein AI is having a substantial impact, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 37–45 Read article
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Ration Distribution with RFID and Mobile OTP Verification using Raspberry Pi
Abstract: The governmental provision of essential domestic commodities at subsidized rates to economically disadvantaged households in developing nations such as India serves as a crucial means of fulfilling basic needs. However, the current mechanism employed in ration shops relies heavily on manual processes for measuring commodities and maintaining transaction records, leading to various challenges including instances of diversion of food grains to the open market. The proposed project, titled " Ration …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 1, 2024 Read article
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A Sustainable EOQ Model for Declining Products Incorporating Cubic Demand, Variable Deterioration, Partial Backlogging, and Carbon Emission Optimization
Abstract: In this paper proposes a sustainable Economic Order Quantity (EOQ) model for inventory systems involving decaying items under cubic time-dependent demand, variable decaying rates, and partial backlogging while absolutely considering carbon emission costs. The model reflects practical market actions where demand initially increases and afterwards declines over time, and decay depends on the age of the item. To demonstrate the current model's applicability as well as evaluate the trade-off between …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article