Machine Learning Based Prediction of Stock Exchange on NASDAQ 100: A Twitter Mining Approach

Harguem, Saida; Chabani, Zakariya; Noaman, Samar; Amjad, Muhammad; Alvi, Muhammad Bux; Asif, Muhammad; Mehmood, Muhammad Hassaan; Al-Kassem, Amer Hani

doi:10.1109/iccr56254.2022.9996008

Cited by 6 publications

(7 citation statements)

References 37 publications

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“…In the automotive sense for example, the fundamental variety uses to mix architectures, configurations, and body types, to include the number of subassemblies available, for example the number of engine / transmission variations, and to choose choices for peripheral variants without impacting key designs such as seats, the sun roof and electric mirrors. (Alzoubi, H MAlhamad et al, 2021;Harguem et al, 2022) shows that each automaker's customization has been listed as leading to pure standardization (PS) Segmented standardization, Customized standardi zation, tailored customization, or pure customization. The concept of PS has been described as providing standard products with predefined design options.…”

Section: Operational Performance Dimensionsmentioning

confidence: 99%

“…Operational Performance (Alzoubi, H MAlhamad et al, 2021;Harguem et al, 2022) indicates that variety in products have a huge positive effect on consumer quality, competitive benefit and market share. But even more so, in technical problems such as R&D expense and design/change costs for engineering, the product variety did have a major negative impact.…”

Section: Relationship Between Product Variety Andmentioning

confidence: 99%

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Exploring the impact of Customization Strategy, Product Variety on Operational Performance in Automotive Manufacturing Industry

Bibi,

Tareq Al-Ibbini,

Alzoubi

2023

Int. J. BAS

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This research has three big contributions to car manufacturing companies in China. Firstly, it defines how an improvement in product variety impacts operational performance. Second, it explains the impact on operational performance of customization strategies practices. Thirdly, the thesis identifies the relative differences of impact by five types of customisations of the product variety on specific aspects of operating performance. It includes a comprehensive analysis of the literature associated with the effects of product variety and customisation as well as techniques for coping with trade-offs between product variety and operating performance. By adopting a quantitative research method, a survey of 12 car manufacturing sector companies from China was conducted. The objectives and questions of this research is clearly defined and outlines the difference the research is to bring to information. This also establishes theories that take into account the relationship between product variety, customisation and operational efficiency. The project focuses on data collection methods and a questionnaire is designed to be submitted to Chinese car manufacturing companies. This gives the empirical results of this study a detailed debate. Finally, the research is concluded by providing a summary of the results of the work and of the study's theoretical contributions. Effective mass customisation and customer-driven development will offer Chinese carmakers a variety of benefits. The basic results, therefore, have significant management consequences for Chinese car producers to pursue numerous strategies under different product design profiles.

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Section: Operational Performance Dimensionsmentioning

confidence: 99%

Section: Relationship Between Product Variety Andmentioning

confidence: 99%

Exploring the impact of Customization Strategy, Product Variety on Operational Performance in Automotive Manufacturing Industry

Bibi,

Tareq Al-Ibbini,

Alzoubi

2023

Int. J. BAS

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“…Economy: Smart cities promote creation of a flexible labor maker, support for innovation and entrepreneurship, especially for women and young people (Aljumah et al, 2021b;Gaytan et al, 2023). Government and Political Participation: Smart cities encourage the adoption of transparent decision -making, promotion of political participation, creation of accessible online services (Ahmed and Nabeel Al Amiri, 2022;Almasaeid et al, 2022;Lee et al, 2023;Mat (Alzoubi et al, 2020;Harguem et al, 2022) explore the role of quality assurance mechanisms in digital services and the importance of continuous improvement to meet evolving citizen needs. Moreover, the concept of smart cities has gained significant attention worldwide as urbanization continues to accelerate Blooshi et al, 2023) (Amiri et al, 2020;Mubeen et al, 2022).…”

Section: Six Axes Of the Smart Citiesmentioning

confidence: 99%

Smart Cities in UAE: Governance, Innovation and Quality

El Khatib,

Al Maazmi,

Alhosani

et al. 2023

Int. J. BAS

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This article is a trail to investigate and evaluate the quality and innovation in the governance of the smart cities of UAE. It will highlight 3 major issues: the current governance of the smart cities of UAE, the need and the role of the quality and innovation in smart cities, the need of a framework to achieve the vision of the smart cities through innovative governance. Quantitative technique is used to collect the primary data from the target audience. The target audience are high level business/management positions and technology professionals working under the governance system of smart city of UAE at different positions. The article concludes that current governance approaches of the smart cities of UAE are not much effective to cater to the current challenges of the smart city such as maximum use of the resources and attain sustainability. Some governance approaches of the smart cities of UAE need to be modified or upgraded to be able to cater to the current problems of the smart cities. There is need to upgrade or innovate the approaches of the governance to achieve the best use of resources and provide quality of life through sustainable development. The study recommended that governance of the smart cities should provide solution at a centralized single platform, the flow of information to maximize the use of resource and minimize the waste, establish digital leadership, digital learning platform and collaboration between the stakeholders.

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“…Few studies have ventured into using sentiment analysis for predicting stock market trends [9][10][11], but they often run into the problem of imbalanced data, which can compromise their effectiveness. To address this, strategies are put in place at both the data handling and algorithmic stages [12].…”

Section: Introductionmentioning

confidence: 99%

Stock Market Prediction With Transductive Long Short-Term Memory and Social Media Sentiment Analysis

Peivandizadeh,

Hatami,

Nakhjavani

et al. 2024

IEEE Access

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In an era dominated by digital communication, the vast amounts of data generated from social media and financial markets present unique opportunities and challenges for forecasting stock market prices. This paper proposes an innovative approach that harnesses the power of social media sentiment analysis combined with stock market data to predict stock prices, directly addressing the critical challenges in this domain. A major challenge in sentiment analysis is the uneven distribution of data across different sentiment categories. Traditional models struggle to accurately identify fewer common sentiments (minority class) due to the overwhelming presence of more common sentiments (majority class). To tackle this, we introduce the Off-policy Proximal Policy Optimization (PPO) algorithm, specifically designed to handle class imbalance by adjusting the reward mechanism in the training phase, thus favoring the correct classification of minority class instances. Another challenge is effectively integrating the temporal dynamics of stock prices with sentiment analysis results. Our solution is implementing a Transductive Long Short-Term Memory (TLSTM) model that incorporates sentiment analysis findings with historical stock data. This model excels at recognizing temporal patterns and gives precedence to data points that are temporally closer to the prediction point, enhancing the prediction accuracy. Ablation studies confirm the effectiveness of the Off-policy PPO and TLSTM components on the overall model performance. The proposed approach advances the field of financial analytics by providing a more nuanced understanding of market dynamics but also offers actionable insights for investors and policymakers seeking to navigate the complexities of the stock market with greater precision and confidence.

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Machine Learning Based Prediction of Stock Exchange on NASDAQ 100: A Twitter Mining Approach

Cited by 6 publications

References 37 publications

Exploring the impact of Customization Strategy, Product Variety on Operational Performance in Automotive Manufacturing Industry

Exploring the impact of Customization Strategy, Product Variety on Operational Performance in Automotive Manufacturing Industry

Smart Cities in UAE: Governance, Innovation and Quality

Stock Market Prediction With Transductive Long Short-Term Memory and Social Media Sentiment Analysis

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