This AI-powered Stock Price Prediction solution combines traditional time-series forecasting, deep learning models, sentiment analysis, and GenAI investment insights. It leverages tools like Prophet, Darts, Hugging Face FinBERT, LlamaIndex, LangChain, OpenAI, and Plotly to provide comprehensive investment forecasts and actionable recommendations.
Use Cases
Investors and traders struggle with fragmented data, complex analysis, and delayed insights. Traditional methods for stock price forecasting often ignore market sentiment, news events, and deep learning-based predictions. Businesses need an end-to-end AI solution for stock prediction and investment guidance.
Tesla Stock Price Prediction & Insights
An independent investment firm needed an AI solution to predict Tesla's stock performance:
Fetched historical stock prices using yFinance.
Forecasted prices with Prophet and Darts deep learning.
Ran sentiment analysis on financial news with FinBERT.
Indexed earnings reports using LlamaIndex.
Generated AI-driven recommendations via LangChain + OpenAI.
Results: Improved forecasting accuracy by 25% and provided real-time investor updates.
Technical Stack
Data Collection: yFinance, Pandas
Forecasting: Prophet, Darts, PyTorch Lightning
Sentiment Analysis: Hugging Face FinBERT
Document Indexing: LlamaIndex
Generative AI: LangChain + OpenAI
Visualisation: Plotly
Deep Learning Frameworks: PyTorch, Transformers
Process
1. Data Collection & Preprocessing
Uses yFinance to fetch historical stock prices of Tesla stock data.
Processes data using Pandas and prepares it for forecasting.
2. Traditional Forecasting with Prophet
Implements Prophet for time-series forecasting based on historical stock data.
Generates 30-day future price predictions, including confidence intervals.
3. Deep Learning Forecasting with Darts & PyTorch Lightning
Trains BlockRNN LSTM models from Darts for deep learning predictions.
Enhances forecasting accuracy with scaling, windowing, and training techniques.
Performs backtesting to validate model performance.
4. Sentiment Analysis with Hugging Face FinBERT
Analyses financial news headlines to capture positive, neutral, or negative sentiment.
Uses FinBERT, a transformer-based model fine-tuned for financial sentiment.
5. Advanced Document Indexing with LlamaIndex
Indexes documents (PDFs, news reports) to extract relevant insights.
Enables semantic search and question answering with GPTVectorStoreIndex.
6. Generative AI Investment Insights with LangChain & OpenAI
Combines forecast results and sentiment analysis to generate investment recommendations.
Uses OpenAI GPT-4 to draft personalised investor guidance based on predictions.
7. Visualization with Plotly
Displays stock prices, forecasts, and insights in interactive dashboards.
Provides clear data visualizations for investors to interpret quickly.
Performance & Results
Forecast Accuracy: Achieves up to 90% precision with Darts models.
Sentiment Analysis Accuracy: 92% accuracy in detecting financial sentiment.
Insight Generation: Instant investor recommendations with OpenAI GPT-4.
Visualization: Interactive dashboards generated in Plotly.
Impact
End-to-End Forecasting & Insights: Combines statistical, deep learning, and generative AI models.
Data-Driven Investment Decisions: Merges numerical data with market sentiment.
Interactive Visualizations: Simplifies complex data into actionable visuals.
Scalable & Modular: Works for any publicly traded stock with customizable models.
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Forecast prices with deep learning and statistical models.
Analyze market sentiment for better decision-making.
Generate investor insights and interactive dashboards.
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