Turn your ideas into a set of clear rules, then replay them against historical price data with realistic costs. See how your rules would have performed — including the losing streaks every rulebook has — before risking real capital.
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 — symbol, capital, position sizing and rules (entry + exit) all filled in. Load one and you can run it immediately.
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.
Waits for price to push above the recent high, then rides the session's first real move.
Change any value, then load the template into the editor below.
Where it breaks: Choppy, range-bound sessions. Almost every breakout fades straight back, and at intraday frequency the round-trip costs turn a small loss into a steady bleed.
Buys short-term exhaustion — oversold on a fast RSI — and exits as soon as price normalizes.
Change any value, then load the template into the editor below.
Where it breaks: Trending sessions. Oversold keeps getting more oversold, and mean-reversion takes its worst losses on exactly the days that look most obvious.
A fast/slow average cross compressed onto intraday bars — follows the direction of the last few minutes, flat the moment it turns.
Change any value, then load the template into the editor below.
Where it breaks: Flat, low-volume stretches. The averages cross back and forth with no follow-through, and every whipsaw pays a full round trip in fees.
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.
Tokenized-stock backtesting covers a market that is still young: shares and funds issued as tokens on a blockchain, trading continuously against a stablecoin. Because these instruments only began listing in 2026, the usable history is measured in minutes rather than years — so this page replays your rules over 1-, 5- and 15-minute bars instead of daily ones.
Continuous trading
These tokens trade every day of the week with no opening bell, so overnight gaps and weekend moves appear in the data in ways the underlying shares never show.
Short history
Listings on this market began in 2026. Minute bars are what exists, so results rest on weeks of data rather than years — an early read, not a settled conclusion.
Pick a token and a rule
Choose a tokenized name and test a momentum rule: buy when price closes above its 20-bar average, sell when it closes below.
Use minute bars, not daily
Because listings are recent there is no meaningful daily history. 15-minute bars give the longest window (up to 90 days); 1-minute bars cover 60 days.
Apply realistic costs
These tokens trade continuously against a stablecoin, so spreads and depth differ from name to name. The backtest charges per-trade costs rather than assuming frictionless fills.
Validate before trusting
A promising minute-level result is a starting point. Move to the training ground to check the same rule on minutes you have not seen.
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.
Total return
Overall profit/loss across the simulated window.
Max drawdown
Largest peak-to-trough decline — the first number to check when the window covers only a few months.
Profit factor
Gross profit divided by gross loss — above 1 means profitable, but read it together with the number of trades, because short windows produce few.
✗ Treating a few weeks of minute data as a track record
✓A 90-day window is a small sample. A rule that looks excellent across it may simply have fitted the single regime that window contains.
✗ Assuming tokenized stocks behave exactly like the underlying shares
✓Trading is continuous and settlement is on-chain, so intraday behaviour differs from the same name on a stock exchange. Do not carry expectations across without testing them.
✗ Ignoring liquidity differences between names
✓This market spans widely traded listings, thinner ones, and leveraged or sector funds. A result from a liquid name does not transfer to a thinly traded one.
Use it when
Skip it when
Respect the sample size
With only weeks of data, one unusually quiet or violent stretch can dominate the result. Rerun across different windows before drawing conclusions.
Stress the costs
Continuous trading against a stablecoin means costs vary more than the headline fee suggests. If an edge disappears at pessimistic spreads, it was not robust.
Watch the drawdown, not just the return
Short windows hide long losing runs. Check that the historical worst case is something you could realistically sit through.
They are tokens issued on a blockchain that are intended to track the value of an underlying share or fund. They trade continuously against a stablecoin instead of through a stock exchange, which changes session hours, settlement and how the instrument is accessed.
The instruments listed in 2026, so there is not yet a year of daily history — and a backtest over a few months of daily bars would contain almost no observations to work with. Minute bars provide a usable number of data points instead.
Up to 60 days of 1-minute bars and up to 90 days of 5- and 15-minute bars, depending on when the particular listing began. Newer listings carry less.
No. The price is intended to track the same underlying, but trading hours, settlement, custody and liquidity are all different. Those differences are precisely why an intraday strategy can behave differently here than the same rule applied to a stock exchange.
No. SoloTrade provides market data and analytical tools. We do not recommend, rate or rank any instrument, and a backtest is a historical simulation rather than a forecast.
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
Tokenized-stock backtest results are simulated from historical market data and are provided for educational purposes only. They do not constitute investment advice or a recommendation of any instrument.
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.