Market Recovery Dynamics During the 2020 Crash

Timeframe: Apr 2025 – May 2025
Stack: Hadoop · HDFS · MapReduce · Hive · Trino · Python

Overview

Integrated large-scale stock, COVID, mobility, and macroeconomic datasets into an HDFS data lake using MapReduce jobs and Hive/Trino schemas. Implemented time-aligned joins and windowed aggregations to quantify crash depth and recovery speed across sectors, geographies, and factor portfolios. Exposed cleaned tables for interactive SQL and dashboards, enabling exploration of sector rotation patterns and policy effects during the 2020 drawdown and rebound.