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ParthP28/README.md

Parth Patel

M.S. Applied Data Intelligence, SJSU (2027) · San Jose, CA

Building data pipelines and quant systems that run fast and explain themselves.

Stack

Python C++ Apache Kafka Apache Spark AWS PostgreSQL Docker dbt

Projects

Project Description Stack
options-pricing-engine Vectorized Black-Scholes + Monte Carlo · 8.56M prices/s · CRR binomial for American options Python · NumPy · Cython
streaming-lakehouse Medallion architecture · Kafka → Spark → Delta Lake · 10.9K rows/s · 73 tests Kafka · Spark · MinIO · dbt
market-data-pipeline Zero-copy ITCH parser · lock-free SPSC ring buffer · per-symbol order book C++20 · FIX 4.2
limit-order-book Price-time priority matching · 715k orders/sec · p99 5μs · Cython hot path · 42 tests Python · Cython
backtesting-engine Market microstructure simulation · slippage modeling · supports limit/market orders Python

📫 work.parth01@gmail.com · LinkedIn

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  1. limit-order-book limit-order-book Public

    Price-time priority limit order book engine in Python. 715k orders/sec · p99 5µs · FIX 4.2 · Cython hot path · 42 tests

    Python

  2. backtesting-engine backtesting-engine Public

    Event-driven backtesting framework with realistic market microstructure simulation, supports limit/market orders, slippage modeling, and transaction cost analysis

    Python

  3. streaming-lakehouse streaming-lakehouse Public

    Streaming lakehouse with medallion architecture: Kafka, Spark, Delta Lake on MinIO, dbt, Dagster. 18s p50 streaming freshness, 10.9K rows/s sustained, 73 tests

    Python

  4. market-data-pipeline market-data-pipeline Public

    Low-latency market data feed handler in C++20. Zero-copy ITCH-style parser, lock-free SPSC ring buffer, sequence gap recovery, and per-symbol book building with HDR latency instrumentation.

    C++

  5. options-pricing-engine options-pricing-engine Public

    Options pricing engine in pure Python. Vectorized Black-Scholes at 8.56M prices/s, batch implied vol solver at 100k quotes in 0.12s, CRR binomial for American exercise, Monte Carlo with 2.67x varia…

    Python