Harnessing the power of unstructured data has become a defining edge in modern investing. This course dives into the fusion of sentiment analysis and alternative data to uncover market signals often invisible to traditional analysis. Delegates will explore how AI, natural language processing (NLP), and geospatial intelligence can be used to anticipate market behavior, build predictive signal models, and validate investment decisions across diverse asset classes.
- NLP-driven sentiment scoring for earnings calls and MD&A sections
- Social media sentiment and its impact on equity and FX markets
- Web-scraping and structured alternative datasets: credit card, payment flows
- Satellite and geospatial data for commodity, foot traffic, and supply chain signals
- ESG sentiment and news-event analysis for sustainable investing
- Ensemble models: combining multi-source sentiment signals
- Deep learning for regime detection and crisis early warnings
- Explainable AI (SHAP, LIME) for signal validation
- Algorithmic trading integration: real-time signals into execution frameworks
- Backtesting alternative data strategies with Python and BI tools
- Implement NLP sentiment models for corporate disclosures
- Analyze social media sentiment for alpha generation
- Scrape and process alternative data for investment insights
- Integrate satellite/geospatial data into signal pipelines
- Backtest sentiment-driven trading strategies
- Explain and validate multi-source signal models with XAI
- Build signal-to-trade frameworks incorporating sentiment inputs
- Build dashboards to monitor sentiment signals and performance
- Portfolio managers, quant researchers, and data scientists - Buy-side analysts in equities, FX, commodities, and macro - Quantitative hedge funds & systematic investment teams - Fintech developers building signal-processing platforms - ESG analysts and sustainable investment officers
- Live coding: Python, NLP libraries, satellite APIs, web scraping - Case studies: Twitter, Reddit, satellite-tracking success stories - Labs: sentiment scoring, alternative data pipelines, backtesting - Explainability clinics: apply SHAP/LIME to sentiment models - Dashboarding: integrate signals into Power BI/Streamlit - Group project: build a live signal-to-trade prototype
- Text mining earnings calls, MD&A sections with FinBERT
- Sentiment scoring and polarity extraction
- Lab: Scrape and score sentiment from SEC filings
- Event-study backtest using policy announcements
- Interpretability: breaking down NLP sentiment features
- Twitter, Reddit sentiment analytics for momentum/trend signals
- Bot-detection and data quality filtering
- Lab: Build real-time tweet sentiment stream with Tweepy & VADER
- Case: GameStop & short-squeeze anomalies
- Dashboard: monitor social sentiment with Streamlit
- Constructing data pipelines: credit card flows, job postings, reviews
- Ethical scraping: data privacy and compliance
- Lab: Build scraper + structured data ingestion
- Analyze alternative indicators vs market performance
- Integration: merge datasets for ensemble signal models
- Satellite data in commodities: crop yields, traffic flows
- Tools: Google Earth Engine, Planet API
- Lab: Fetch and process satellite data for commodity signals
- Combine geospatial and sentiment signals
- Trading integration: signal-to-trade pipelines
- XAI: SHAP and LIME for sentiment model interpretability
- Backtesting frameworks: Zipline, Backtrader
- Lab: Backtest multi-source sentiment strategy
- Deploy a dashboard-linked prototype
- Final group presentations: signal strategies + performance metrics
Group & Corporate Discounts: Available for companies enrolling multiple participants to help maximize ROI. Individual Discounts: Offered to self-sponsored participants who pay in full and upfront. Registration Process: Corporate nominations must go through the client’s HR or Training department. Self-nominations must be prepaid via the “payment by self” option. Confirmation: All registrations are subject to DIXONTECH’s approval and seat availability. Refunds: Provided in case of course cancellation or no seat availability. Tax Responsibility: Clients are responsible for any local taxes in their country.