Two things are hidden on purpose: which instrument you are trading, and the second half of its price history. Both would let hindsight do the thinking instead of your rules. Build your strategy on the visible slice, then watch how it behaves on the part you never saw — a risk-free way to catch overfitting before real money is involved.
Disclaimer: Trading financial instruments involves risk. Simulated and historical results do not guarantee future performance, and this page is for education only — not financial advice.
To keep results accurate, confirm the basic parameters below before building rules — changing them resets the whole workspace.
Each template is a complete plan — capital, position sizing and rules (entry + exit) all filled in. The symbol is picked at random for you, so a template never tells you what you are trading.
Nothing is locked: every number stays editable. Each card also tells you where the idea breaks down — which matters more than how it looks on history.
A carefully stacked 3-condition entry that looks brilliant on history. Import it, then take it to the Training Ground and watch it fall apart.
Where it breaks: Out-of-sample data. Every extra condition was tuned to one specific stretch of the past — that is overfitting, and the blind test is designed to expose it.
Bets that a move, once started, tends to continue — buy when the fast average crosses above the slow one, exit when it crosses back.
Change any value, then load the template into the editor below.
Where it breaks: Sideways, choppy markets. The averages cross back and forth and you get whipsawed into a string of small losses.
Bets that a new high signals fresh demand — buy when price breaks the highest level of the last 20 bars, exit when it breaks the lowest.
Change any value, then load the template into the editor below.
Where it breaks: Range-bound markets full of false breakouts. Price pokes above the high, fails, and reverses — you bought the top of the range.
Bets that a sharp sell-off overshoots and snaps back — buy when RSI drops below 30, exit when it recovers above 70. Sized by risk, not by cash.
Change any value, then load the template into the editor below.
Where it breaks: A sustained downtrend. RSI can stay 'oversold' for months while price keeps falling — this is how beginners catch falling knives.
Bets that price drifts back toward its 60-bar average — buy the dip below it, exit when price closes back above.
Change any value, then load the template into the editor below.
Where it breaks: Strong one-way trends. Price leaves the average behind and never comes back, so you sit in cash (or early) while it runs away.
A trend entry wrapped in a fixed stop (-5%) and target (+15%), sized so each stop costs ~1% of the account — the textbook shape of a trade plan.
Change any value, then load the template into the editor below.
Where it breaks: Nothing here is broken when it loses — that is the point. A stop means you take small losses on purpose; a plan that never loses is a plan with no stop.
Starts small, adds once the trade is up 5%, then trails a tiered stop so profit is protected on the way up.
Change any value, then load the template into the editor below.
Where it breaks: A sharp reversal right after you add. You cannot add size without also adding risk — pyramiding amplifies both directions.
Choose the symbol you want to study, your starting capital, and how much to risk on each trade. Fees and slippage are real numbers — what you see is what the market would have charged.
Two sentences are enough to start: when to get in, and when to get out. Stack conditions like building blocks — no code, and every rule reads back to you in plain language.
Run the plan over real price history and see what actually happened — the equity curve, the drawdown, and every entry and exit marked on the chart. Judge it by the numbers, not by how convincing the idea sounds.
The crypto training ground applies the same train-then-validate idea to cryptocurrency pairs. Build a strategy on one slice of history, then check whether it holds up on unseen data — a practical lesson in how easily crypto volatility can fake a good idea.
Randomized window
The data used changes between runs, reducing the chance of memorizing one pattern.
Blind validation
The out-of-sample portion is hidden until you commit to the strategy.
Build on the first slice
You design a crypto rule on the in-sample window — say a volatility breakout with a fixed stop.
Lock the strategy
The out-of-sample window stays hidden until you commit, preventing you from tuning to data you have not earned the right to see.
Reveal and compare
The strategy runs on the unseen slice, and you compare the two returns side by side.
Read the volatility honestly
Crypto's swings make the gap between the two windows especially telling — a rule that only worked on one lucky slice is quickly exposed.
Pick a market
Choose the stock, ETF or crypto pair you want to study.
Build the rules
Combine entry, exit and position rules as visual blocks — no code required.
Run the test
The engine replays the rules bar by bar over real price history.
Read the result
Review the return, drawdown and equity curve, plus a plain-language assessment of strengths and weaknesses.
In-sample vs out-of-sample
The gap between the two is a simple overfitting signal.
Drawdown
Cryptocurrency swings make drawdown a core part of the judgment.
✗ Tuning the rule to the specific crypto slice you were shown
✓Random windows are designed so you cannot memorize one episode. If you keep iterating until that slice passes, you are defeating the exercise.
✗ Trusting a pass from a single random window
✓One window is one exam. The idea earns trust across several different, unseen slices — not just one.
✗ Assuming a good practice run equals a good live strategy
✓Validation checks one idea on one kind of data. Live crypto adds liquidity, slippage, and regime changes the simulation excludes.
Use it when
Skip it when
Keep the rules simple
Crypto's noise rewards simple rules that generalize. Complexity that fits one slice is exactly what fails the next.
Watch the drawdown, not just the return
A crypto validation that passes with a 60% drawdown may still be untradeable. Read both numbers.
Run multiple windows before concluding
Surviving several different random slices is far more convincing than acing a single favorable one.
Random windows prevent you from tuning to one specific market episode in the homework before the exam.
No. It means the idea survived one validation pass; many more conditions — costs, liquidity, regime change — are not modeled here.
The structure is the same, but the data is different: crypto trades around the clock with wider swings, so the validation pass is often harsher. A strategy has to survive much wilder price behavior to stay consistent out-of-sample.
Take it as information, not failure. Go back and ask whether the rules were too specific to the first window, simplify, and run again. The whole exercise is to catch that problem before real capital is involved.
Passing validation is one evidence point, not permission to go live. Live markets add execution costs, liquidity limits, and regime shifts that no historical simulation captures, so treat a passing run as a starting point for further testing.
Start free, scale as you grow. No hidden fees, no surprises.
The full platform with usage limits — no card, no countdown.
Best for
Testing whether an idea survives contact with real data.
No monthly allowance — signup credits only
Deeper history, and your first intraday intervals.
Best for
Swing and intraday strategies on 15- and 30-minute bars, over a decade of context.
Includes 360 credits/month · about 72 runs with review
Every interval we support, and the longest intraday windows.
Best for
High-frequency rules that only make sense on 1- to 5-minute bars.
Includes 1000 credits/month · about 200 runs with review
Crypto practice results are simulated from randomized historical data and are educational only. They do not constitute investment advice.
Disclaimer: The tools and content on this site are provided for educational purposes only and do not constitute investment advice. Trading and investing involve a substantial risk of loss, and past performance does not guarantee future results.