01 Front Office Quant (Chapters 1–8) | Commodities (Gas & Power)
Full Programme: https://durgaanalytics.com/etrm_quant
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Chapters
00:00 01 What a Front-Office Quant Actually Does
11:20 02 The Trading Desk Ecosystem
22:20 03 A Day in the Life of a Gas & Power Desk
32:44 04 Prices, Returns, and the Language of Markets
43:39 05 Setting Up Your Python Lab
53:14 06 Python Building Blocks for Quants
1:04:55 07 Your First Market Calculation in Python
1:14:53 08 How This Course Builds Four Real Apps
Designed around the software, mathematics, and market structure used by energy trading desks. Rather than treating derivatives pricing as isolated theory, every chapter contributes to a reusable pricing library and ultimately to a production-style trading analytics platform.
The curriculum progresses from commodity market microstructure and forward curve construction through Black-76, Monte Carlo simulation, stochastic processes, swing contracts, spread options, storage valuation, Greeks, VaR, stress testing, model validation, and production Python engineering. Along the way, learners build a reusable Forward Curve engine, a Gas Swing Pricing Engine, a Spark Spread Risk platform with Greeks, a Gas Storage Valuation model, and a live Trader Risk Dashboard.
The engineering focus extends beyond quantitative models into software architecture: vectorised NumPy implementations, SciPy optimisation, numerical methods, reproducible research, automated testing, pricing library design, market data pipelines, object-oriented pricing frameworks, caching, profiling, and production-ready Python modules.
This is not a notebook-only course. It is a build-first programme where every lab feeds one integrated codebase, enabling participants to develop portfolio-quality applications that resemble the analytical tooling used by commodity trading desks.
If you're interested in Commodity Quantitative Finance, Energy Trading, ETRM, Risk Analytics, or Front-Office Pricing Systems, the attached brochure provides the complete curriculum.
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