Deep technical notes used across multiple scenes.

A) Derivatives pricing fundamentals

  1. Payoffs and contract specs (vanilla vs structured; path dependence)
  2. No-arbitrage basics (put–call parity, bounds, monotonicity)
  3. Discounting and forwards (curve building concepts; compounding conventions)
  4. Measure / numeraire intuition (why discounting works; risk-neutral pricing idea)
  5. Black–Scholes / Black-76 (when used; limitations)
  6. Greeks (analytic vs finite-difference; stability and bump sizing)
  7. Volatility modelling (implied vol surface, smiles; interpolation sanity)

B) Commodities / power flavour (minimum)

  1. Term structure and seasonality (shape risk)
  2. Mean reversion intuition (why many commodity models use it)
  3. Convenience yield / storage logic (conceptual; power is special)
  4. Optionality in commodities (spark spread type intuition; structured products exist)
  5. Risk measures used in trading (VaR, stress, scenario; PnL explain)

C) Numerical methods used in pricers

  1. Analytic pricing vs numerical (trade-offs)
  2. Monte Carlo (variance reduction basics; reproducibility; seeds)
  3. PDE / finite differences (when relevant; stability intuition)
  4. Trees / lattice methods (quick approximation; calibration)
  5. Calibration (objective functions; stability; overfitting; sanity constraints)

D) Risk analytics

  1. Scenario analysis (shocks, revaluation; aggregation)
  2. Sensitivities (buckets, cross-greeks; risk factor mapping)
  3. Stress testing (historical vs hypothetical; coherent stories)
  4. Model risk and controls (assumptions, limitations, drift monitoring)

E) Portfolio / aggregation thinking

  1. Netting and aggregation (PV and risk across trades/books)
  2. PnL decomposition / explain (risk factor moves → PnL components)
  3. Hedging intuition (delta/vega hedging basics; what breaks it)

F) Optimisation (nice to have, but valuable)

  1. Constrained optimisation (risk limits as constraints)
  2. Stochastic optimisation (scenarios, CVaR, chance constraints)
  3. Dynamic programming intuition (especially relevant to hydro assets)

G) Trading Central Analytics Framework

  1. Pricing Library Design for a Unified Analytics Framework
  2. Power & Commodities Context for a Central Analytics Framework
  3. Engineering Workflow for a Quant Analytics Framework
  4. Correctness and Validation for a Pricing Library
  5. Data Versioning, Replay, and Audit Trail