Learn to trade systematically — without the hype
Day Trading Lab is a structured, three-level curriculum that takes complete beginners from reading their first candlestick all the way to building, backtesting, and forward-testing their own algorithmic strategy — entirely in paper-trading environments, with zero live-money risk and zero profit promises.

"I will never let your excitement outrun your evidence — that's the one rule this whole school runs on."
— Moe.SH

What you'll learn
What you'll be able to do
- Read and annotate live candlestick charts in TradingView with confidence, identifying key price-action patterns and market-structure levels
- Explain how markets, order types, spreads, commissions, and slippage work — and calculate their true cost on a simulated position
- Apply a disciplined risk-management framework: position sizing, stop placement, and risk-reward ratios, entirely in a paper-trading environment
- Build and back-test a rules-based strategy using TradingView's Pine Script, then validate the same logic in Python with QuantConnect
- Automate and forward-test a strategy in MetaTrader 5 using MQL5, interpreting equity-curve statistics and drawdown metrics critically
- Complete a structured paper-trading lab — logging trades, reviewing psychology biases, and producing a written performance report grounded in evidence, not outcome luck
How it works
A school that adapts to you
This isn't a set of static videos. Every lesson is generated live and tuned to where you actually are.
We learn your level
A quick placement check tailors your starting point so you're never bored or lost.
Lessons adapt as you go
Each lesson is written for your pace and your goal, adjusting as your skills grow.
Your AI coach keeps you moving
Checkpoints, feedback, and gentle nudges turn progress into a real result.
The curriculum
What's inside your school
9 modules · 44 lessons

Chart Literacy & TradingView Foundations
Students learn to navigate TradingView, read candlestick charts, and identify core price-action patterns and market-structure levels.
- 1.1TradingView OrientationIncluded
- 1.2How Candlesticks WorkIncluded
- 1.3Essential Candlestick PatternsIncluded
- 1.4Chart Types & TimeframesIncluded
- 1.5Annotating Support, Resistance & TrendsIncluded
Market Mechanics & True Cost of Trading
Students discover how exchanges and brokers operate, what drives price, and how to calculate the real financial cost of every simulated trade.
- 2.1How Markets & Exchanges WorkIncluded
- 2.2Order Types DemystifiedIncluded
- 2.3Spreads, Commissions & SlippageIncluded
- 2.4Asset Classes on the Day-Trader's MenuIncluded
- 2.5Reading Level 2 & the Order BookIncluded
Price Action, Indicators & Chart Analysis
Students layer technical indicators onto price-action foundations and learn to use — and question — every popular tool critically.
- 3.1Market Structure & Price ActionIncluded
- 3.2Moving Averages & Trend FiltersIncluded
- 3.3Momentum & OscillatorsIncluded
- 3.4Volume Analysis & VWAPIncluded
- 3.5Building a Multi-Confirmation SetupIncluded
Risk Management & Paper Trading Practice
Students build a personal risk framework — position sizing, stop placement, risk-reward — and apply it exclusively in a simulated paper-trading environment.
- 4.1The Risk-First MindsetIncluded
- 4.2Position Sizing & the 1% RuleIncluded
- 4.3Stop Placement & Risk-Reward RatiosIncluded
- 4.4Setting Up & Using TradingView Paper TradingIncluded
- 4.5Reviewing a Paper-Trade SessionIncluded
ICT, Liquidity, Order Flow & Forecasting
Students learn how liquidity, market structure, ICT concepts, order-flow terminology, and intraday forecasting can be used as hypotheses—not guarantees. The module distinguishes chart and OHLCV proxies from true event-level order-flow data, emphasizes uncertainty and data limits, and keeps every exercise paper-only with unseen-data testing.
- 5.1Liquidity: Where the Orders Are HidingIncluded
- 5.2ICT Market Structure & the Concept of Price DeliveryIncluded
- 5.3Order Flow Tools & Reading Institutional FootprintsIncluded
- 5.4Intraday Forecasting: Building a Structured Daily BiasIncluded
Strategy Building & Pine Script Backtesting
Students translate their chart rules into a coded, backtestable strategy using TradingView's Pine Script, then critique the results honestly.
- 6.1What Makes a Rules-Based StrategyIncluded
- 6.2Pine Script FundamentalsIncluded
- 6.3Coding Entry, Exit & Stop RulesIncluded
- 6.4Reading the Strategy Tester ReportIncluded
- 6.5Overfitting, Curve-Fitting & Walk-Forward TestingIncluded
Python, QuantConnect & Algorithmic Validation
Students re-implement their Pine Script strategy in Python on QuantConnect, gaining a second, independent validation of the same logic.
- 7.1Python Crash Course for TradersIncluded
- 7.2QuantConnect Environment & LEAN EngineIncluded
- 7.3Translating Pine Script Logic to PythonIncluded
- 7.4Backtesting & Comparing Results Across PlatformsIncluded
- 7.5Monte Carlo Simulation & Realistic ExpectationsIncluded
Automation & Forward-Testing in MetaTrader 5 / MQL5
Students automate their strategy as an Expert Advisor in MetaTrader 5 using MQL5, then forward-test it on a demo account and interpret the equity curve.
- 8.1MetaTrader 5 Platform TourIncluded
- 8.2MQL5 FundamentalsIncluded
- 8.3Building an Expert AdvisorIncluded
- 8.4MT5 Strategy Tester & OptimizationIncluded
- 8.5Demo Forward-Test & Equity-Curve InterpretationIncluded
Trading Psychology & the Structured Paper-Trading Lab
Students confront cognitive biases, build a personal psychology checklist, and complete a comprehensive paper-trading lab culminating in a written performance report.
- 9.1Cognitive Biases in Trading DecisionsIncluded
- 9.2Building a Pre-Trade & Post-Trade RoutineIncluded
- 9.3Forecasting, Uncertainty & Probabilistic ThinkingIncluded
- 9.4The Four-Week Paper-Trading LabIncluded
- 9.5Writing Your Performance ReportIncluded
Who it's for
Is this you?
The Complete Beginner
She's heard about day trading but hasn't opened a chart yet — this curriculum gives her a genuine, jargon-free starting point with no live money on the line.
The Self-Taught Retail Trader
He's been trading sporadically for a year with patchy results and needs the structured foundation he never got — especially around risk management and strategy validation.
The Software Developer
He's comfortable with code but knows nothing about markets, making the Pine Script, Python, and MQL5 modules a natural entry point into algorithmic thinking applied to trading.
The Evidence-Driven Professional
She's skeptical of trading hype by nature and wants a curriculum that quantifies risk, names uncertainty plainly, and backs every claim with data rather than anecdote.
The Career Changer
He's exploring whether systematic trading could become a serious pursuit, and needs a rigorous, honest assessment of what the skill actually requires — not a sales pitch.
The Returning Learner
She tried trading years ago, lost money she shouldn't have risked, and is ready to rebuild from scratch — this time in paper-only environments with a proper process.
Questions
Frequently asked
Moe.SH
A note from your teacher
Moe.SH
If you've ever opened a trading chart and felt simultaneously fascinated and completely lost — or if you've been self-teaching for a while and still can't explain exactly why you take a trade — I built this school for you.
I know what the self-taught path usually looks like. You watch videos that promise a "simple system," you paper-trade for a week, you feel ready, and then reality delivers a sharp lesson. Or you go the opposite direction: you download every indicator, read about every pattern, and end up more confused than when you started. Neither path is your fault. The material most traders are handed is either too shallow or too scattered. What's almost always missing is structure — a sequenced curriculum that builds each concept on the last and names uncertainty honestly at every step.
That's the gap Day Trading Lab is designed to close. We start where you actually are: reading a candlestick for the first time, understanding what a spread really costs you, learning why most retail traders dramatically underestimate slippage. We build from there — price action, market structure, indicators used as confirmation tools rather than crystal balls — until you have genuine chart literacy, not just pattern recognition by rote. Then we go further: you'll write your first strategy rules in Pine Script, stress-test them in TradingView's Strategy Tester, port the logic to Python on QuantConnect, run a Monte Carlo simulation, and forward-test an Expert Advisor in MetaTrader 5. By the end, you won't just have a strategy — you'll have a validated, cross-checked framework and the skills to build another one.
I want to be direct about one thing: this school does not promise profits, and it does not provide signals. The reason is straightforward — no honest educator can promise you an edge in markets, and anyone who does is selling you something else. What I can promise is a rigorous, evidence-based process: the same kind of disciplined, probabilistic thinking that separates traders who survive from those who don't. The four-week paper-trading lab at the end of the curriculum — with trade journaling, cognitive-bias review, and a written performance report — exists precisely because process accountability is what builds durable skill.
If you're willing to do the methodical work, I'm glad you're here. Let's build something you can actually trust.
— Moe.SH
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- 9 modules, 44 lessons
- AI-adaptive lessons tuned to your level
- Quizzes & checkpoints to lock in progress
- Your own AI learning coach
- Learn on any device, at your pace
- Full access for as long as you're subscribed
