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105 articles for “Financial Modelling”
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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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Empowering Banking Operations Through Excel Innovations for Data Precision and Security
Abstract: Excel plays a pivotal role in the banking sector due to its unparalleled versatility and robust data processing capabilities. It serves as a fundamental tool for handling complex financial calculations, data management, risk assessment, and generating comprehensive reports. Its ability to organize, analyze, and visualize vast volumes of financial information empowers banking professionals to make informed decisions crucial for managing investments, determining lending strategies, and optimizing financial portfolios. Excel's adaptability …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 10, Issue 3, 2023 · pp. 15–38 Read article
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Computer and Commerce – Relationship for The Future
Abstract: The relationship between computers and commerce has evolved dramatically over the past few decades, transforming the way businesses operate and how consumers interact with markets. This synergy continues to grow and holds significant potential for the future. Computers, through advancements in artificial intelligence (AI), machine learning, cloud computing, and big data analytics, have revolutionized commerce by enhancing efficiency, improving decision-making, and fostering innovation. In the future, we can expect even …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 2, 2025 · pp. 42–59 Read article
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A Comprehensive Analysis of Classification Methods for Churn Prediction in Financial Services
Abstract: Persistent issues that affect long-term revenue in the banking sector include excessive client attrition. Customary churn models depend on measures related to customer satisfaction, which often result in low predictive accuracy due to their subjective nature. This study proposes an effective early warning model to address customer churn in financial services. Data is preprocessed through cleaning, one-hot encoding, Z-score normalization, and Min-max scaling. To handle class imbalance, the SMOTE algorithm …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 47–61 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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Open Educational Resources and Open Access Publishing in Higher Education: Policies, Challenges, and Collaborative Models
Abstract: Open Educational Resources (OER) and Open Access (OA) publishing are transforming higher education by promoting equitable access to knowledge, reducing costs, and fostering collaborative innovation. While OER focus on openly licensed teaching and learning materials, OA ensures unrestricted online access to scholarly research. Together, they form an integrated open knowledge ecosystem aligned with global policy frameworks such as the UNESCO OER Recommendation (2019) and the Budapest Open Access Initiative. This …
Published in International Journal of Trends in Humanities · Vol. 3, Issue 1, 2026 · pp. 7–12 Read article
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A Comparative Review of Parallel Computing Techniques for High-Performance Computing
Abstract: High-Performance Computing (HPC) has become an essential technology for solving computationally intensive problems in scientific computing, engineering, artificial intelligence, weather forecasting, computational biology, financial modelling, and large-scale data analytics. The increasing complexity and heterogeneity of modern HPC systems have created a strong requirement for efficient parallel computing techniques and portable programming models. Several programming approaches, including Message Passing Interface (MPI), Open Multi-Processing (OpenMP), Compute Unified Device Architecture (CUDA), OpenACC, SYCL, …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 2, 2026 · pp. 16–26 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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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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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article
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Wireless Sensor Networks Simulation
Abstract: The formidable growth of Wireless Sensor Network (WSN) research has raised challenging issues of examining the micro behaviour of proposed protocol and carrying out its performance evaluation. The methodologies to realize this is: mathematical modelling; experimentation and simulation. For WSNs, experimentation has financial constraints and mathematical modelling at times requires deep expertise in mathematics. Thus simulation has become the first choice for research in WSNs. There are several researchers using …
Published in Journal of Electronic Design Technology · Vol. 5, Issue 2, 2014 · pp. 1–8 Read article
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Project Management Maturity Model (PMMM) in Construction Industry
Abstract: Construction industry has a major role in social and economic development. However, high investment and large scale operation are some of the major problems in this industry, which is in sharp contrast with inferior management and low benefit. So project directors are seeking ways to improve their organizational management company's level to complete and control the implementation of their projects efficiently. The competition in the markets of construction industry is …
Published in Journal of Construction Engineering, Technology & Management · Vol. 6, Issue 1, 2016 · pp. 1–13 Read article
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Vehicle Insurance Fraud Detection Using Supervised Neural Network Model
Abstract: Vehicle insurance fraud is a serious problem that causes huge financial losses to insurance companies. In recent years, developing fraud detection models using machine-learning techniques has been of great interest. This study proposes a novel approach for vehicle insurance fraud detection using Supervised Neural network model on the Kaggle Vehicle Insurance Fraud Detection dataset. The initial step in this study involves performing data pre-processing and feature extraction on the dataset, …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 10, Issue 1, 2023 · pp. 32–39 Read article
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Stock Market Forecasting Using Time Invariant Fuzzy Time Series Model
Abstract: Stock market volatility is an important for investment, option pricing and financial market regulation. In recent years a different types of models which apparently predict changes in stock market prices have been introduced. There are many methods in the literature to solve the problem of future prediction. The present study provides a foundation for the development and application of fuzzy time series model for short term investor as well as …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 1, 2018 · pp. 104s–111s Read article
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Unmasking Hallucinations in Large Language Models Using Analysis of the LLAMA 2 Model and RAG Intervention
Abstract: The study describes the creation of a chatbot for financial trading called "TradeBot" and how it uses Retrieval Augmented Generation (RAG) to overcome the problem of producing false or unverifiable information, sometimes known as hallucinations. RAG allows the chatbot to refer to an external data source in addition to its taught knowledge, which increases the accuracy of its responses. The NCFM (NSE's Certification in Financial Markets) book was integrated as …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 76–86 Read article
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The Evolution and Impact of Numbers: From Ancient Tallies to Quantum Computing: Review Article on Numbers
Abstract: Numbers are among the most fundamental constructs in human civilization, serving as the backbone of mathematics, science, technology, and virtually every aspect of daily life. They represent not only quantities and measures but also relationships, structures, and patterns that underpin the fabric of human understanding. From the earliest tallies etched on bones by prehistoric humans to the sophisticated numerical systems embedded in today’s artificial intelligence and quantum computing, the evolution …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 15–19 Read article
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Assessing Performance of Commercial Banks in Pakistan: A Study on Finance Innovation with Camel Model Application
Abstract: For the competitiveness of commercial banks, trade finance innovation is playing an essential role in Pakistan. Currently, modern banking sector is converting into more complex system. Assessing banking sector of Pakistan is a critical and complex task. There are various key factors which need to be addressed while evaluating performance of banks. A sound financial position of banks is extremely important to not only the depositors but also for employees, …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 8, Issue 1, 2018 · pp. 38–45 Read article
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Innovative Risk Aperture Manipulation Model for Risk Management in Mega Project Construction
Abstract: The complexities associated with the technical, managerial and financial interventions in mega project implementation accommodates greater risks, encapsulating the complete project period from inception to closure. Consideration of risks in mega project scope is of paramount importance as it delineates either threat or opportunity in the guise of uncertainty at each and every phase of the project. The absence of innovative and rigorous risk management structure imparts a perplexing scenario …
Published in Trends in Transport Engineering and Applications · Vol. 2, Issue 1, 2015 · pp. 11–24 Read article
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The Contribution of Mathematics to Make Developed India
Abstract: This research paper explores the significant contributions of mathematics to the development of India, tracing its influence from ancient innovations to modern applications across diverse sectors. India has a long-standing mathematical tradition, with foundational achievements such as the invention of zero, the decimal system, and advancements in algebra, trigonometry, and geometry, which profoundly shaped global knowledge systems. These early contributions established India as a pioneering hub of mathematical thought and …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 3, 2025 · pp. 08–15 Read article
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Design and Analysis of a 100 kWp Grid Connected PV Solar Plant at a Coastal Area of Bangladesh
Abstract: In Bangladesh, the usage of electricity is continuously increasing. Govt. is also trying to increase the electricity production by installing new power plants to meet the additional power demands. Most of the power plants are natural gas-based, coal-based or nuclear power-based. Considering the greenhouse effect; solar power plants could be one of the best solutions to meet the additional power demands as well as it has a lot of financial …
Published in Journal of Power Electronics and Power Systems · pp. 33–39 Read article