SubMicro Trading System | 890ns Ultra-Low Latency Execution Engine
Open-source sub-microsecond algorithmic trading system achieving 890ns median latency. Lock-free, deterministic, production-ready.
Agent-based simulator models flash crash events like 2010’s using high-frequency trading data and explores key market conditions behind such volatility.
https://hackernoon.com/the-anatomy-of-a-flash-crash-modeled-to-the-millisecond #highfrequencytrading
The Anatomy of a Flash Crash, Modeled to the Millisecond | HackerNoon
Agent-based simulator models flash crash events like 2010’s using high-frequency trading data and explores key market conditions behind such volatility.
Simulations show how algorithmic trading, inventory limits, and trader speed drive flash crashes—and why real markets may be more fragile than we think.
https://hackernoon.com/how-trading-algorithms-can-trigger-flash-crashes #highfrequencytrading
How Trading Algorithms Can Trigger Flash Crashes | HackerNoon
Simulations show how algorithmic trading, inventory limits, and trader speed drive flash crashes—and why real markets may be more fragile than we think.
Simulated study reveals how market maker limits and trading frequency affect the frequency and severity of mini flash crash events.
https://hackernoon.com/why-tiny-crashes-happen-all-the-time-and-what-they-reveal-about-modern-markets #highfrequencytrading
Why Tiny Crashes Happen All the Time, and What They Reveal About Modern Markets | HackerNoon
Simulated study reveals how market maker limits and trading frequency affect the frequency and severity of mini flash crash events.

The Mechanics of a Mini Flash Crash | HackerNoon
A simulation of the 2010 Flash Crash reveals how algorithmic trading and liquidity withdrawal led to one of the most dramatic market drops in history.
https://hackernoon.com/why-did-the-stock-market-crash-in-2010 #highfrequencytrading
Why Did the Stock Market Crash in 2010? | HackerNoon
A simulation of the 2010 Flash Crash reveals how algorithmic trading and liquidity withdrawal led to one of the most dramatic market drops in history.
Statistical tests show our calibrated model mirrors real financial data. P-values and coverage ratios confirm its accuracy and realism.
https://hackernoon.com/can-a-financial-model-truly-mimic-reality-these-numbers-say-yes #highfrequencytrading
Can a Financial Model Truly Mimic Reality? These Numbers Say Yes | HackerNoon
Statistical tests show our calibrated model mirrors real financial data. P-values and coverage ratios confirm its accuracy and realism.
Surrogate models and grid search combine to calibrate an agent-based financial simulation that mirrors real mid-price market dynamics.
https://hackernoon.com/validation-driven-calibration-of-financial-simulation-models #highfrequencytrading
Validation-Driven Calibration of Financial Simulation Models | HackerNoon
Surrogate models and grid search combine to calibrate an agent-based financial simulation that mirrors real mid-price market dynamics.