The first complete Metavulus learning path, focused on forex foundations, macro context, structure, and execution discipline.
Open pathLearning structure
Build a clear forex workflow: understand the market, read price structure, size risk, and prepare each session before execution.
01
Start with forex basics, pair language, candlesticks, trend, support resistance, and market context.
02
Use checkpoints, progress, XP, and completion states to keep the next step obvious.
03
Turn every lesson into a repeatable routine for prep, execution, journaling, and review.
Live curriculum
Every module turns one risk concept into lessons, fieldwork, and a quiz checkpoint.
Module 1
FreeStart with the core language of forex: how pairs are read, why prices move, and how a beginner builds market context before opening a chart.
Module 2
FreeBuild the ability to read a chart calmly: candlesticks as decision footprints, trend as the dominant direction, and levels as reaction zones.
Module 3
FreeRead economic data as inputs to central bank expectations: inflation, labor market, growth, PMI, and how surprises shift market pricing.
Module 4
FreeTurn the economic calendar and market bias into a concrete session plan: when to focus, when to wait, and when not to trade.
Module 5
FreeRead risk-on/risk-off conditions while building personal discipline through journaling, review, and rules that reduce impulsive decisions.
Module 6
MembersRead conditions where government and central bank are pushing in different directions, and understand the impact on yields, currencies, and volatility.
Module 7
FreeStart with definitions: what algorithmic trading is, why institutions and serious traders use it, and how an automated system works end to end.
Module 8
FreeBefore writing a strategy, understand the playing field: how orders meet in the order book, the role of brokers and APIs, and what each order type implies.
Module 9
FreePython is the de facto language for quantitative research. Build practical foundations with environments, NumPy, Pandas, and price data.
Module 10
FreeA strategy is only as good as its data. Learn price-data structure, timeframe resampling, and the quiet data traps that break backtests.
Module 11
FreeConnect the pieces from hypothesis to rules, signals, and positions through a simple moving-average crossover strategy.
Module 12
FreeA bad backtest is more dangerous than no backtest. Learn honest testing practices and the biases that must be avoided.
Module 13
FreeReturns alone are misleading. Build the metric vocabulary needed to balance reward and risk and compare strategies fairly.
Module 14
FreeIndicators transform price data into features. Learn the main indicator families, how to program them, and common implementation mistakes.
Module 15
FreeCosts quietly kill strategies. Model transaction costs realistically and understand capacity, turnover, and market impact.
Module 16
FreeMachine learning is a tool, not magic. Frame market prediction as supervised learning and build the right conceptual pipeline.
Module 17
FreeApply statistical foundations to practical quant strategies including mean reversion, pairs trading, cross-sectional momentum, and factor investing.
Module 18
MembersSurvey modern AI techniques in trading, where they can help, and where they are often over-promoted.
Module 19
FreeA strong strategy can fail through weak operations. Learn how to run strategies live with staged rollout, monitoring, and fail-safes.
Module 20
FreeA comprehensive assessment drawing from foundations, backtesting, metrics, risk, statistics, machine learning, strategy, and production.
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