ETRM Modeling | Market Data, Curves & Time-Series Modeling | 12-module full course скачать в хорошем качестве

ETRM Modeling | Market Data, Curves & Time-Series Modeling | 12-module full course

Learn how professional trading and risk systems handle market data, curve building, and time-series modeling — from ingestion to real-time analytics. Format: Self-paced + Cohort · Duration: 4–8 weeks · Level: Advanced (201/301) https://durgaanalytics.com/etrm_marke... Cohort - Hands-on Lab 3 — Build a Forward Curve (Bootstrapping) Objective: Construct a simple yield and forward curve from sample market instruments, compare interpolation techniques, and visualize differences. Tools: Python / Databricks SQL / Jupyter Notebook Steps: 1. Load rate data (Deposits, Futures, Swaps) from provided CSV. 2. Implement bootstrapping to derive discount factors. 3. Build a forward curve using interpolated forward rates. 4. Compare linear, spline, and log-linear interpolation. 5. Visualize the curves and identify smoothness differences. 6. Incorporate holiday adjustments and day count conventions. Deliverables: Python notebook implementing bootstrapping and interpolation Curve visualization chart (rates vs maturity) Validation report comparing interpolation errors (RMSE) ---- This continuous 12-module course takes you step-by-step through the architecture, math, and engineering patterns behind modern market-data platforms used in banks, ETRM systems, and fintech firms. Build real expertise in: 📊 Data ingestion pipelines (real-time + batch) 🧠 Curve construction & interpolation methods 📈 Volatility surfaces & time-series forecasting 🧪 Backtesting, validation & stress testing 🏗️ Production governance, lineage & reproducibility ⚡ Streaming, OLAP, hybrid, and caching architectures Each lesson includes clear explanations, architecture diagrams, and real-world examples using tools like Kafka, Databricks, Snowflake, Redis, and FastAPI. By the end, you’ll be able to design your own market-data and curve-management platform with full reproducibility and low-latency analytics. Chapters 00:00 - Course Introduction 08:57 - Module 1 — Market Data Ingestion & Pipelines 16:42 - Module 2 — Time-Series Storage Patterns 24:50 - Module 3 — Curve Construction (Rates & Commodity Forwards) 32:04 - Module 4 — Interpolation & Smoothing Techniques 42:14 - Module 5 — Volatility Surfaces & Smile Modeling 49:59 - Module 6 — Time-Series Analysis & Forecasting 58:23 - Module 7 — Backtesting & Validation 1:07:00 - Module 8 — Production Considerations & Governance 1:15:55 - Module 9 — Streaming-First Pipeline Design 1:26:05 - Module 10 — Batch + OLAP Pipeline 1:36:15 - Module 11 — Hybrid (Real-Time + Historical) Pipeline 1:42:37 - Module 12 — Curve Service & Caching 📘 About the Course This is part of the Yukti Advanced Market Data Engineering Series — designed for professionals in data engineering, quant development, and risk technology. Follow along to gain hands-on skills that connect data modeling, analytics, and production governance in real trading environments. #MarketData #TimeSeries #CurveModeling #FinancialEngineering #ETRM #QuantAnalytics #Snowflake #Kafka #Databricks #RiskTechnology #DataGovernance #VolatilitySurface market data modeling, curve construction, volatility surface, time-series forecasting, financial data engineering, databricks, snowflake, kafka streaming, dbt pipelines, ETRM, quantitative analytics, risk modeling, backtesting, data governance, hybrid pipelines, real-time data, financial systems architecture