Course Overview

Lesson 1: Core Principles

Discover five timeless principles that anchor long-term trading success. This lesson explores the probabilistic nature of markets, the importance of risk control, the value of realistic expectations, and the power of evidence-based strategy development.

Lesson 2: Hardware Configuration

Unlock StrategyQuant’s full potential with the right hardware setup. This lesson walks you through optimal CPU, RAM, and storage configurations, and offers practical tweaks to maximize speed and stability.

Lesson 3: Downloading & Configuring Data

Master the setup of high-quality historical data to match your broker's specifications. This lesson walks you through configuring time zones, spreads, swaps, and commissions—illustrated with forex, metals, and crypto. Learn how to verify your configuration so backtests reflect real-world trading conditions.

Lesson 4: Market Selection

Learn how to evaluate a market’s tendency to trend or mean-revert using a systematic approach. This lesson guides you through manually programming strategies in AlgoWizard and running comparative backtests—so you can focus your development on markets most aligned with your strategy style and trading objectives.

Lesson 5: Genetic Builder

Learn the process behind automated strategy generation, and how to configure the builder like a pro.

Builder Concept and Configuration
Learn how the genetic builder mimics natural selection to evolve trading strategies. This lesson explains genetic evolution—selection, crossover, mutation—and provides detailed guidance on configuring the builder, including how to segment data, choose building blocks, set money management rules, and apply performance filters to automatically generate robust strategies.
Custom Templates
Want to preserve your trading idea while leveraging the efficiency of genetic algorithms? This lesson shows you how to program custom strategy templates in AlgoWizard for trend following and mean reversion setups, and how to use random groups to prioritize your preferred entry conditions.
Multiple Timeframe/Market Strategies
Trying to boost your win rate by finding confluence across timeframes or markets? This lesson demonstrates the simplest way to build a multiple timeframe strategy, and how to use custom blocks to program your own entry conditions.
Fuzzy Logic Strategies
With fuzzy logic, only a portion of your entry conditions must be met for a trade to trigger. Learn how to configure the builder to create fuzzy logic strategies, increasing both trading frequency and portfolio diversity.

Lesson 6: What-if Simulations

Test your strategy under different trading conditions—without rerunning a full backtest. This lesson covers a wide range of simulations, including the removal of outlier trades and addition of entry time filters, and demonstrates how to modify your strategy after simulating a day-of-week filter.

Lesson 7: Monte Carlo Simulations (Randomized Trade Sequence)

Monte Carlo simulations reveal the hidden uncertainties in your backtest. This lesson explains the role of confidence levels, then shows how to configure the simulations and interpret the results for a more realistic view of your strategy’s robustness.

Lesson 8: Tick Backtesting

A backtest is your strategy’s scorecard and serves as a performance benchmark after going live. Learn to configure high-precision tick backtests and understand why accurate intra-bar price modeling is essential for certain strategies.

Lesson 9: Additional Timeframe/Market Backtesting

Apply your strategy to additional timeframes and markets for effective out-of-sample testing. Learn to select relevant charts and fine-tune your configuration and passing criteria to quickly shortlist robust strategies.

Lesson 10: Monte Carlo Simulations (OOS Testing)

Shake up your strategy with randomized price and parameter simulations to reveal sneaky overfitting. This lesson explains the concept behind each test with intuitive flowcharts and walks you through detailed configuration and filtering.

Lesson 11: Sequential Optimization

Avoid curve fitting by optimizing one parameter at a time and focusing on high fitness plateaus. This lesson walks through the configuration process, explains how to evaluate fitness stability, and compares results against conventional brute force optimization.

Lesson 12: Optimization Profile/System Parameter Permutation

Perfect for evaluating parameter stability, the 3D optimization profile lets you visualize performance across the parameter space and identify robust regions. SPP uses histograms and median-based metrics to detect overfitting, providing a more reliable assessment than a single backtest result.

Lesson 13: Walk-forward Optimization (WFO)

Periodically reoptimize your strategy to verify its robustness and improve its adaptability. This lesson covers anchored vs. unanchored WFO, key settings like the number of optimization runs and out-of-sample percentages, and essential performance filters. You’ll also learn to use the Walk Forward Matrix to select optimal WFO settings while adding another layer of robustness testing.

Lesson 14: Portfolio Composition

A diversified portfolio could be the closest thing to a holy grail in trading. This lesson covers:

Why a diversified portfolio improves your risk-adjusted returns, and tips to improve diversification
How to use Portfolio Master’s genetic algorithm to optimize strategy selection and minimize correlations
How to use Portfolio Composer to fine-tune individual strategy weights
How to apply variable position sizing and adjust it to match your risk appetite
How to estimate margin and capital requirements before going live

Lesson 15: Custom Projects

Custom projects let you automate the entire strategy development process—covering the build, robustness testing, and portfolio composition. I’ll illustrate by developing a diversified 10-strategy portfolio consisting of the GBPJPY, Gold, and Bitcoin.

Lesson 16: Live Trading

Address these key considerations before risking real capital:

Whether you need a VPS, and how to select the best VPS
How to maximize your Metatrader performance
How to track live performance and compare it against your backtest
When to quit trading a strategy, and how to implement a portfolio-level stop loss

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