Fair Value Analysis
AI-powered weather-adjusted fair value predictions for IEX India
Fair Value Methodology
How we calculate weather-adjusted fair value predictions
Weather Factors Considered
Temperature
High temperatures (>35°C) increase cooling demand, pushing prices up. Cold weather reduces AC load.
Solar Radiation
High solar radiation (>500 W/m²) increases renewable supply during 10:00-15:00, lowering prices.
Wind Speed & Cloud Cover
Wind affects wind generation capacity. Cloud cover reduces solar output, increasing thermal dependency.
Prediction Model
AI-Powered Analysis
Our model uses GPT-4o-mini to analyze weather conditions and historical IEX market patterns. It correlates temperature, solar radiation, and demand periods with historical clearing prices.
Algorithmic Fallback
When AI is unavailable, a rule-based algorithm uses temperature deviation, time-of-day adjustments, and solar/cloud correlations based on Indian power market patterns.
Data Sources
Real-time weather from Open-Meteo API. Market prices scraped from IEX India (Day-Ahead & Real-Time Markets). 5 major Indian grid zones monitored.
Important Disclaimer
Fair value predictions are estimates based on weather data and historical market patterns. They do not constitute financial advice. Actual market prices are influenced by numerous factors including transmission constraints, generator outages, demand variations, regulatory changes, and market manipulation that are not fully captured by weather-based models. Confidence scores indicate model certainty, not prediction accuracy. Past performance does not guarantee future results. Always conduct independent analysis before making trading decisions.
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The AI fair value engine needs weather and market data to generate predictions.