ENERGY, COMMODITIES & CLIMATE

Models for energy, markets and transition risk.

Quantitative systems for forecasting, market volatility and climate-transition decisions.

Selected examples of quantitative workflows designed for energy markets, commodities and climate-risk analysis.

Electricity Pricing

Models electricity price dynamics, seasonality, volatility and supply-demand behaviour to support forecasting, trading and energy-market decision-making.

SARIMA Forecasting

Applies seasonal time-series modelling, stochastic forecasting and probabilistic analysis to identify trends, forecast demand and generate dynamic scenarios.

Commodities GARCH

Models time-varying volatility across energy, metals and agricultural commodities to support VaR, stress testing, hedging and position sizing.

Climate & Energy Transition Risk

Compares net-zero, delayed-transition and baseline scenarios across emissions, carbon prices, energy demand, macroeconomic stress and sector-level financial impacts.

Kalman Filtering

Uses Bayesian state-space models to extract latent signals, filter noisy observations and dynamically estimate evolving market or energy-system states.