Paras.
BACK_TO_ARCHIVE
PROJ_DERIV-004

Derivatives Analytics AI

SaaS predictive analytics dashboard for Indian Derivatives (NSE) markets.

HARDWARE_STACK

FastAPI
Django
React
PostgreSQL

VIBE_CHECK

SYSTEM_STABILITY: OPTIMAL
USER_ENGAGEMENT: HIGH
LATENCY_METRIC: <50MS
DESIGN_STYLE: BRUTALIST

PROBLEM

Calculating Black-Scholes options Greeks (Delta, Gamma, Vega, Theta) on high-frequency NSE market ticks creates extreme CPU latency.

GOAL

Maintain sub-50ms data streaming latency during peak market volumes while calculating complex mathematical Greeks.

ARCHITECTURE

FastAPI server running LSTM models for market regime classification, pulling data from Redis cached tick buffers and sending metrics to a Django dashboard.

PERFORMANCE

Utilized python multiprocessing queues and fast math models to avoid GIL blocks and keep calculations asynchronous.

REVISIONv1.0.4-STABLE
ENGINE_TYPENEXT_JS_APP
UPTIME_PROB99.99%
LOAD_TIME342MS