• [FREE] Python Quant Strategy Starter Pack: SOL, MCL & MES Systematic Trading Bots - HFTCODE.COM
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[FREE] Python Quant Strategy Starter Pack: SOL, MCL & MES Systematic Trading Bots

[FREE] Python Quant Strategy Starter Pack: SOL, MCL & MES Systematic Trading Bots

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Institutional-Grade Python Futures Strategies

Instant access to 3 broker-agnostic, production-grade Python algorithmic bots targeting Crypto, Energy, and Equity index futures (SOL, MCL, and MES). Complete commented source code included.

Broker-Agnostic
Standard Python 3.10+
Architecture
Asyncio Event-Driven
Included Bots
3 Complete Strategies
Cost
Free / Open Architecture

Overview

Most retail traders spend months—and thousands of dollars—building systematic strategies from scratch, only to discover their edge collapses when exposed to real-world latency and execution friction. This free bundle gives you the actual source code to three engineered algorithmic strategies, structured and commented the way professional quant desks build systems.

All proprietary data pipes and exchange-specific execution plumbing have been decoupled into clean placeholder hooks. You can feed bars from any source (Interactive Brokers, Tradovate, NinjaTrader, CCXT, or CSV backtests) and execute via paper or live broker APIs.

Included Trading Strategies

1. SOL Futures Momentum Engine

Script: bar_sol_long_20260916_212659

A long-only systematic signal model designed for high-volatility cryptocurrency futures using RSI thresholding, moving-average trend confirmation, and volatility-adaptive trailing stops.

Target Asset: SOL Futures (Front-Month) Direction: Long Only
Core Indicators: RSI, EMA/SMA Crossovers, ATR Risk Management: Dynamic Trailing Stop

2. Micro Crude Oil Geopolitical Momentum (MCL)

Script: bot_mcl_geopolitical_momentum

A systematic trend-following algorithm targeting Micro Crude Oil (MCLN6). Features multi-tier profit taking, Donchian channel breakouts, and realized-volatility regime filters.

Target Asset: Micro WTI Crude Oil (MCLN6 / NYMEX) Max Position: Up to 4 Contracts
Core Indicators: Donchian Breakout, MACD, Realized Volatility Controls: Daily Loss Limits & Circuit Breakers

3. Micro E-Mini S&P 500 Fed Hawkish Momentum (MES)

Script: bot_mes_fed_momentum

A bidirectional (Long/Short) macroeconomic momentum engine tuned for S&P 500 micro contracts with inverse-volatility scaling, VIX regime integration, and multi-R scaled profit targets.

Target Asset: Micro E-Mini S&P 500 (MESM6 / CME) Direction: Long & Short Capable
Sizing Module: ATR & VIX-Adaptive Sizing Backtested Sharpe: 2.28 (Grade A+)

What You Receive (Instant Zip Download)

  • bar_sol_long_20260916_212659_portable.py — Complete portable Python code for the SOL momentum bot.
  • bot_mcl_geopolitical_momentum_portable.py — Complete portable Python code for the Crude Oil momentum bot.
  • bot_mes_fed_momentum_portable.py — Complete portable Python code for the E-Mini S&P 500 momentum bot.
  • Fully Decoupled Execution Layer — Easily connect to Interactive Brokers, CCXT, Alpaca, or custom WebSocket feeds.
  • Heavily Documented Source Code — In-line notes detailing indicator logic, risk gates, position sizing, and event loops.

Technical Requirements

  • Python Version: Python 3.10 or higher.
  • Dependencies: Zero proprietary lock-in. Built entirely with standard Python libraries (asyncio, logging, typing, dataclasses).
  • Data Requirement: Any standard OHLCV feed (60-second to 4-hour bars).

Frequently Asked Questions

Q: Are these black-box compiled binaries?

A: No. You receive 100% open, human-readable Python source code. You can inspect every line, modify variables, and backtest on your own data.

Q: Do I need a Rithmic or Redis account?

A: No. All proprietary infrastructure has been replaced with standard asynchronous placeholder functions so you can route data and orders wherever you choose.

Q: Can I run this in paper-trading simulation?

A: Yes. All three bots include built-in simulation hooks so you can track performance on live bar feeds without risking capital.

Educational & Research Disclaimer: This source code is provided for educational and research purposes only and does not constitute investment or financial advice. Futures and crypto trading involve substantial risk of loss. Past backtested performance is hypothetical and does not guarantee future results.

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