🦀📊 MarketStat — High-Performance Financial Stats Engine in Rust

MarketStat (a.k.a. quant_marketstat_ws) is a blazing-fast, quantitative financial analytics CLI engine, crafted in Rust by Willy Sajbeni.

Ideal for traders, quants, and data scientists who need low-latency, high-integrity insights extracted from price/volume data.

Quick Install & Run (Requires Rust)

cargo install quant_marketstat_ws
quant_marketstat_ws

Features

• ✔️ Arithmetic Mean
• ✔️ VWAP (Volume Weighted Average Price)
• ✔️ VWAP Group (Bid/Ask average)
• ✔️ Variance (Sample & Population)
• ✔️ Standard Deviation (STD)
• ✔️ VWAP Variance & VWAP STD
• ✔️ Group VWAP Variance & STD
• ✔️ Profit & Loss Calculation (P&L Summary)
• 📈 Global Summary with human-readable interpretations
• 📂 CSV Data Import (Option 11)
• 🦀 Built in pure Rust — fast, safe, and lightweight

CLI Menu Preview

Choose a function:
1 - Mean
2 - VWAP
3 - VWAP Group
4 - Variance
5 - STD
6 - VWAP Variance
7 - VWAP STD
8 - VWAP Group Variance
9 - VWAP Group STD
10 - Profit & Loss Calculation (P&L Summary)
11 - Full Market Stats Report (Global Summary)
12 - Load data from CSV (Bid, Ask, Volume)

CSV Format Example (for Option 11)

Your CSV file must follow this format:

Bid,Ask,Volume
10.5,11.0,1000
10.6,11.1,1500
10.4,10.9,1200

Instructions:

• Save your file as data.csv
• Place it in the same folder where you run cargo run
• When prompted, just type:

  data.csv
  

• You can type x to cancel if you change your mind
• The system loops until a valid file is found

License

MIT License — built and maintained by Willy Sajbeni

Why Rust over Python?

Because speed, safety, and clarity matter.
This crab 🦀 just decapitated the snake 🐍 — with both claws!

Coming Soon

• 📡 Yahoo Finance real-time fetch (optional)
• 📊 Graphs and interactive charts via TUI
• 📦 Binary executables (.exe, .app, ELF) for all platforms

Author

Developed with love and mathematical rigor by Willy Sajbeni
Follow on LinkedIn | GitHub

Quantitative AI & Algorithmic Research | Linux, Rust, Python & Mathematical Modeling for Quant Trading