ALGORITHMIC TRADING SYSTEM v4.0

Know-Defeat

A collaboration between Jordan Pack and Clayton Christian. Probability-driven execution for precision trading. Empower your portfolio with 100+ algorithmic bots, dynamic fund allocation, and real-time market analysis.

100+Trading Bots

6Strategy Types

TickData Processing

2msExecution Delay

Core Capabilities

Multi-Algorithm Engine

6 sophisticated algorithm types: Momentum, Mean Reversion, Breakout, Support/Resistance, Price Pattern, Volatility Breakout.

Bot Ranking System

Dynamic performance ranking with weighted scoring based on win rate, PnL, Sharpe ratio, and profit factor.

Fund Allocation

Automated capital allocation from $200 to $5,000 per bot based on tiered performance rankings.

Backtesting Framework

Comprehensive historical simulation with tick-level data replay and performance metrics.

Risk Management

Advanced drawdown protection, position sizing, and automated risk controls.

AI Agent Integration

AgentStack-powered agents: Market Analyzer, Strategy Executor, Risk Manager, Performance Tracker.

System Architecture

A closed-loop autonomous trading system designed for continuous improvement.

Data Ingestion

Real-time tick data from Interactive Brokers/Alpaca

Signal Generation

Multi-algorithm analysis identifies opportunities

Risk Assessment

Risk Manager validates against position limits

Order Execution

Strategy Executor places trades via broker APIs

Performance Tracking

Metrics calculated and rankings updated

Fund Reallocation

Capital redistributed based on updated rankings

Built for Scale

Enterprise-grade infrastructure designed for high-frequency data processing and low-latency execution.

Python / FastAPI

Backend

PostgreSQL

Database

TimescaleDB

Time-Series

Docker

Infrastructure

Interactive Brokers

Brokerage

AgentStack

AI Framework

Data Ownership

We Own Our Data

Unlike retail platforms that rely on third-party feeds, we collect, store, and manage every tick ourselves. Complete data sovereignty with institutional-grade infrastructure.

Multi-Tier Database Architecture

Our data infrastructure handles millions of ticks daily across multiple asset classes. Built on PostgreSQL with TimescaleDB extension for time-series optimization, the system maintains sub-millisecond query performance even with terabytes of historical data.

350GB+

Tick Data Storage (30 days)

<1ms

Query Response Time

Multiple

Asset Classes

24/7

Data Collection

Complete Data Sovereignty

Raw Tick Collection
We capture every price movement, bid/ask change, and volume update directly from exchanges—no intermediaries, no delays.
Custom Candle Generation
Build candles of any timeframe: 1-second, 37-minute, or 4-hour. Our system aggregates raw ticks into any periodicity you need.
Historical Replay
Backtest strategies against actual market conditions with tick-perfect precision. Every execution, every spread, every liquidity event preserved.
No Data Vendor Lock-in
Your strategies rely on YOUR data. No monthly fees to Bloomberg or Reuters. No API rate limits. Complete independence.

Database Architecture Overview

Tick Data Layer

tick_data - Raw price feeds

ohlcv_1m - 1-minute candles

order_book - L2 market depth

trades - Executed transactions

Strategy Layer

bot_metrics - Performance tracking

bot_rankings - Dynamic rankings

sim_bot_trades - Simulated trades

variable_weights - Scoring weights

Operations Layer

fund_allocations - Capital distribution

allocation_history - Audit trail

strategy_params - Configurations

execution_logs - Order history

100+ tables across 12 schema domains managing millions of records daily

Win Rate

Profitable trades %

Sharpe Ratio

Risk-adjusted return

Max Drawdown

Peak-to-trough decline

Profit Factor

Gross profit / Gross loss

Performance Metrics

We track every tick, trade, and outcome. Our system continuously optimizes based on four key performance indicators to ensure consistent growth while minimizing risk.

Real-time equity curve monitoring
Automated strategy disabling upon drawdown limits
Volatility-adjusted position sizing
Cross-strategy correlation analysis

Why Know-Defeat?

Professional-grade infrastructure vs. retail solutions

Feature

Know-Defeat

Standard Retail Bots

Strategy Complexity

Multi-algorithm + Dynamic Ranking

Single static strategy

Data Handling

Tick-level Time-Series DB

Standard MT4/MT5 feeds

Bot Management

100+ bots with coordinated allocation

Single bot instance

Customization

Full algorithm customization

Limited presets

Scalability

Enterprise-grade Docker/K8s

Desktop application

Transparency

Open Architecture

Proprietary Black Box

Ready to Automate Your Trading?

Get in touch to learn more about Know-Defeat and how it can transform your trading strategy with institutional-grade technology.