gorazd 0.7.0

Institutional quantitative execution and physical reality matrix.

GORAZD: Institutional UHFT Execution Matrix

Gorazd is an ultra-high-frequency, zero-allocation quantitative execution engine designed for bare-metal Linux deployments. It physically bypasses the Python Global Interpreter Lock (GIL) and OS-level mutexes to achieve deterministic microsecond execution for Machine Learning models.

Architectural Supremacy

• The 4-Core Hydra: Mechanically hijacks 4 CPU cores (isolcpus) for Ingestion, Execution, Risk (Kill-Switch), and Concept Drift monitoring.
• Page-Aligned Memory: Eradicates OS page faults by mapping monolithic tensors directly to physical RAM via mmap.
• Lock-Free IPC: Inter-Process Communication utilizing C11 atomic pointers and 64-byte L1 cache-line padding.
• Native C-API Inference: Bypasses Python wrappers entirely, mapping RAM directly to libxgboost.dll/so via ctypes.
• Microstructure Physics: Custom XGBoost objective gradients mathematically constrained by Maker/Taker rebates and Continuous Risk Lagrangians.
• Avellaneda-Stoikov Routing: Dynamic Kelly capital exposure scaled by inverse volatility and skewed by real-time inventory risk.

Environmental Configuration (.env)

Gorazd operates across two distinct deployment realms. You must create a .env file in your execution directory.

# Execution Mode: RETAIL (Free APIs) or BLOOMBERG (B-Pipe)
data_source="RETAIL"

# Free API Infrastructure (Used if data_source="RETAIL")
tiingo_api_key="YOUR_TIINGO_KEY"
alpaca_api_key="YOUR_ALPACA_KEY"
alpaca_api_secret="YOUR_ALPACA_SECRET"

# Risk Constraints
max_leverage=1.5
base_capital=250000.0

The Global CLI Matrix

Gorazd installs directly into your operating system's PATH. You do not need to write scripts to operate the core pipeline.

gorazd-fetch   # Polls APIs/Bloomberg, calculates scalars, bakes Parquet.
gorazd-train   # Executes Purged CV and non-linear risk Optimization.
gorazd-ui      # Ignites the ZeroMQ tactical terminal dashboard.
gorazd-ignite  # Launches the 4-Core UHFT memory-mapped daemon.

Top-Level Python API

For quantitative researchers looking to integrate Gorazd into existing frameworks, the gz top-level namespace provides brutal, operational brevity.

import gorazd as gz

# 1. Synthesize Physical Tensors
compiler = gz.TensorCompiler(target="SPY")
compiler.compile(start_date="2016-01-01")

# 2. Optimize Physics-Aware Matrix
optimizer = gz.Optimizer()
optimizer.fit(parquet_file="SPY_institutional_matrix.parquet")

# 3. Ignite the Multicore Daemon
engine = gz.Engine(target="SPY", model_file="core.ubj")
engine.ignite()

Bare-Metal OS Tuning (Equinix NY4)

Do not run this engine on a standard OS if capital is at risk. You must alter the Linux kernel via GRUB to isolate the physical CPU cores from background OS interruptions.

# /etc/default/grub
GRUB_CMDLINE_LINUX_DEFAULT="quiet splash isolcpus=1,2,3,4 nohz_full=1,2,3,4 rcu_nocbs=1,2,3,4"