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Algorithmic Trading · Level not specified
Algorithmic trading
Learn how to define strategy rules, apply risk controls, backtest assumptions, review performance, and plan an automation workflow.
Sign in to saveIs this course for you?
For learners who want to convert trading ideas into rule-based, testable systems and understand the path toward monitored automation.
Before you begin
Any software, data, or prior-knowledge requirements will be confirmed before enrollment.
What you’ll study
Algorithmic Trading Course includes 6 modules in this published curriculum overview.
- 01
Algorithmic-trading foundations: systematic trading, rule-based frameworks, market data, and execution
- 02
Strategy building: entry, exit, indicator and price-action rules, market filters, and trade management
- 03
Risk and money management: position sizing, stop-loss, take-profit, risk-reward, and drawdown rules
- 04
Backtesting: historical data, test parameters, entries, exits, transaction costs, and slippage
- 05
Strategy performance: win rate, profit factor, expectancy, drawdown, risk-adjusted measures, and equity curves
- 06
Optimization and automation: overfitting, robustness, forward testing, workflow design, monitoring, and execution
Class dates will appear in the member workspace when scheduled.
Download course overview (PDF)The learning objective
Design, test, measure, and improve a rule-based trading framework with documented assumptions and risk controls.
An educational objective, not a promise of trading performance. Progress depends on prior knowledge and practice.
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No instructor identity is published for this course yet. A profile will appear only after the name, photograph, teaching role, experience, and claimed credentials have been checked and approved for publication.