The Predictive AI In Stock Market is being driven by Increasing availability and integration of alternative data
The Predictive AI In Stock Market is expected to grow at a CAGR of 21.8% during 2024 and 2029. During this period, the market is also expected to show a growth of USD 1632.2 million. In the realm of Predictive AI in the stock market, a groundbreaking development is the fusion of generative AI and sophisticated Large Language Models (LLMs) into investment analysis and strategy generation. This marks a pivotal shift from the conventional use of Natural Language Processing for rudimentary sentiment analysis towards a far more intricate and sophisticated form of qualitative data extraction and synthesis. LLMs, renowned for their advanced contextual understanding, semantic comprehension, and ability to decipher complex financial narratives, are increasingly being employed to process and decipher vast volumes of unstructured text data, previously deemed intractable or only superficially analyzable. This encompasses sources such as quarterly earnings call transcripts, intricate regulatory filings like 10-K and 10-Q reports, central bank meeting minutes, and real-time global news feeds.
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The market is segmented based on
According to Technavio, There are several factors that are causing the market to flourish during the forecast period, which are as follows:
However, the market also witnesses some limitations, which are as follows:
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Market Scope |
|
Report Coverage |
Details |
Page number |
239 |
Base year |
2024 |
Historic period |
2019-2023 |
Forecast period |
2025-2029 |
Growth momentum & CAGR |
Accelerate at a CAGR of 21.8% |
Market growth 2025-2029 |
USD 1632.2 million |
Market structure |
fragmentation |
YoY growth 2024-2025(%) |
19.3 |
Key countries |
US, China, India, UK, Canada, Germany, Japan, France, South Korea, and Australia |
Competitive landscape |
Leading Companies, Market Positioning of Companies, Competitive Strategies, and Industry Risks |
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In the realm of Predictive AI for the stock market, key performance indicators include forecast accuracy metrics like Mean Absolute Error. Other factors such as stockout costs, holding costs, service level, and fill rate, influence inventory management. Data quality assessment, model validation techniques, parameter tuning, and model explainability ensure model reliability. Data preprocessing, feature engineering, model deployment, model retraining, algorithm selection, data governance, data security, performance monitoring, API integrations, real-time dashboards, data pipelines, cloud computing platforms, database management, data warehousing, business intelligence tools, and predictive modeling techniques are essential components of a robust and effective stock market predictive AI system. Causal inference adds value by identifying the underlying causes of market trends.
In the dynamic realm of business and technology, Predictive AI in the Stock Market represents a significant sub-segment of the vast IT software industry. This domain encompasses companies specializing in machine learning algorithms, demand forecasting models, and inventory optimization, utilizing deep learning networks to enhance financial predictions. The application of these advanced technologies in stock market analysis falls under the broader category of application software, a segment of the IT software market. According to Technavio, the IT software market size is determined by the consolidated revenue of companies providing all types of software, including cloud-based solutions. This market scope encompasses enterprise and technical software, excluding entities classified under the interactive home entertainment or systems software sub-industries.. Industries are leveraging the products belonging to the market for customer engagement, transactional notifications, and promotional offers.
Technavio Research
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