PROJECT REGISTRY — 3 ENTRIES

TECHNICAL
PROJECTS

Each system below is an active build or architectural design. Live System entries are connected to real APIs and can be interacted with directly. Architecture Only entries are proprietary or conceptual — source is restricted, but the full execution stack is documented here.

LIVE SYSTEM1 active
PRIVATE CORE2 restricted
[P-01]LQC-CORE
PRIVATE CORE

LeoLogic Quantitative Core

ARCHITECTURE ONLY

Automated trading system powered by a custom Python execution engine with strict order logic.

LQC is a systematic trading infrastructure built entirely in pure Python. It interfaces directly with the Interactive Brokers TWS API via socket-level communication to manage live and paper positions. The engine enforces strict entry/exit rules, real-time signal evaluation, and hard drawdown caps — with no discretionary overrides permitted at runtime. Source code and strategy logic are closed to protect execution edge.

TECH STACK

Python 3.12IBKR TWS APIFastAPIpandasTA-LibasyncioSQLiteNext.js 16

SYSTEM SPECS

ENGINEPure Python
BROKERIBKR TWS API
EXECUTIONLive + Paper
PARADIGMEvent-driven
RISK MODULEDrawdown cap · Kelly
LATENCYSub-100 ms target

SYSTEM ARCHITECTURE

LQC — EXECUTION STACK
01
MARKET DATA FEED— Real-time price + volume stream via IBKR socket
02
SIGNAL PROCESSOR— EMA · RSI · VWAP · ATR band evaluation
03
STRATEGY ENGINE— Rule validation · entry / exit condition gating
04
RISK MODULE— Drawdown cap · position sizing · Kelly fraction
05
ORDER ROUTER— IBKR TWS API — live order placement + fills
06
AUDIT LEDGER— SQLite trade log · execution timestamps · P&L
READ ARCHITECTUREVIEW WHITEPAPER
#ALGORITHMIC_TRADING#PYTHON_AUTOMATION#IBKR_API#SIGNAL_PROCESSING#EVENT_DRIVEN#RISK_MANAGEMENT#QUANT_FINANCE
[P-02]CATALYST-SYS
PRIVATE CORE

Project Catalyst

ARCHITECTURE ONLY

Multi-asset portfolio optimization engine applying modern portfolio theory and factor-based allocation models.

Catalyst is a research-grade portfolio construction system designed to run scenario analysis across equity and derivative instruments. It integrates mean-variance optimization, Black-Litterman blending, and Fama-French factor exposure reporting. The allocation engine operates on a configurable rebalance schedule and is interfaced via a private REST API layer. Full source code is restricted — architecture overview reflects the actual component design.

TECH STACK

Python 3.12cvxpyscipy.optimizepandasFastAPIPostgreSQLRedisNext.js 16

SYSTEM SPECS

OPTIMIZERMV · Black-Litterman
FACTORSFama-French 3/5F
INSTRUMENTSEquity · Options
REBALANCEConfigurable schedule
CONSTRAINTSWeight · sector · VaR
OUTPUTEfficient frontier + weights

SYSTEM ARCHITECTURE

CATALYST — ALLOCATION STACK
01
DATA INGESTION— Market data + fundamentals · REST + WebSocket
02
FACTOR ENGINE— Fama-French exposure · alpha signal generation
03
OPTIMIZER CORE— cvxpy MV · Black-Litterman view blending
04
CONSTRAINT LAYER— Weight bounds · sector limits · VaR ceiling
05
REBALANCE SCHEDULER— Drift trigger · calendar-based execution gating
06
REPORTING API— FastAPI · frontier chart · attribution breakdown
READ ARCHITECTUREVIEW WHITEPAPER
#PORTFOLIO_OPTIMIZATION#FACTOR_INVESTING#BLACK_LITTERMAN#MEAN_VARIANCE#QUANT_FINANCE#PYTHON_SCIENCE#RISK_MANAGEMENT
[P-03]HALF-LIFE-BIO
LIVE SYSTEM

Half-Life Bio-Metrics

Metabolic decay simulator applying first-order half-life kinetics to track substance plasma concentration.

Half-Life Bio-Metrics models the pharmacokinetic decay of supplemental compounds — including Creatine, Vitamin D3, and Magnesium — using the first-order decay equation A(t) = A₀ × e^(−0.693t / t½). The system accounts for scheduled dosing intervals, accumulation effects across multi-day cycles, and generates a continuous concentration curve to inform optimal supplementation timing.

TECH STACK

Python 3.12NumPy / SciPyFastAPINext.js 16TypeScriptTailwind CSSRecharts

SYSTEM SPECS

SUBSTANCESCreatine · Vit-D3 · Mg
ALGORITHMFirst-order decay
FORMULAA(t) = A₀ × e^(−λt)
HALF-LIFEConfigurable per compound
DOSINGAccumulation-aware
OUTPUTPlasma conc. curve

SYSTEM ARCHITECTURE

HALF-LIFE — DECAY ENGINE
01
SUBSTANCE CONFIG— t½ per compound · dosage · unit-of-measure
02
HALF-LIFE KINETICS— A(t) = A₀ × e^(−0.693t / t½) — first-order ODE
03
DOSE SCHEDULER— Multi-dose accumulation · replenishment timing
04
SIMULATION ENGINE— Discrete time-step integration across cycle window
05
API LAYER— FastAPI — /simulate endpoint · JSON payload
06
VISUALIZER— Plasma concentration curve · peak / trough markers

DECAY SIMULATOR — INTERACTIVE

LAUNCH DASHBOARDVIEW LIVE METRICS
#PHARMACOKINETICS#HALF_LIFE_MODELING#PYTHON_SCIENCE#NUMPY_SCIPY#FASTAPI#NEXT_JS#BIO_INFORMATICS

leologic@sys ~/projects

3 REGISTERED · 1 LIVE · 2 PRIVATE