Portfolios, not lucky symbols.

AurexionLabs is built for portfolios: many coins, chosen by a rule each day, and several portfolios on one account, tested together the way they would trade.

One symbol proves little.

A strategy tuned on one coin can look good by luck. Across many coins, and a rule that picks them the same way every day, the result has to hold up before you trust it.

Which coins, every day.

Pro and up

A good trading strategy on the wrong coins still loses. Choosing the coins is a strategy of its own, so AurexionLabs lets you build it, test it and run it like one.

Universes: the coins you are willing to trade

  • A fixed list you choose, or a list built from a rule you write, for example every coin above a daily traded value over a past window.
  • A coin sweep can write one for you: the coins where your strategy passed a significance test.

Selectors: which of them to trade today

  • Rules you set in the form, or a short expression, such as momentum minus BTC's momentum, top 3, among the liquid coins.
  • Your own machine-learning model, trained in Python.
  • Each selector is checked and previewed day by day: every coin's score and rank on that day, and which ones were picked.
  • Selectors are scored on each past day with only the data known that day, so a backtest can follow one over years.

There is no profit split per coin, on purpose: it would invite you to keep the coins that happened to win.

The app's selector editor: a four-line expression that picks the 3 coins with the strongest 10-day momentum over BTC among liquid coins, checked green, and its one-day preview: 17 eligible coins with their rank and score, the top 3 highlighted
The app's selector editor with its own example: momentum minus BTC's momentum, top 3, among liquid coins. Checked, then previewed for one day (2026-07-01, the newest day in the daily data here): every eligible coin's score and rank, and the 3 it picks. A preview shows what a rule picks, not whether the picks will make money.

Several portfolios on one account.

Pro and up

A combined backtest runs up to 8 portfolios on one account, the way they would trade as sub-accounts. Each portfolio is its own sub-account, so you can trade the same coins with different strategies, or the same strategy on different timeframes, at the same time.

  • Each portfolio has its own strategy, build, settings, timeframe, selector or coin list, coins per day and positions at once.
  • Give each one a share of the account, and a risk per trade as a percent of its share, dollars per trade, or lots.
  • Every morning the account is split again by those shares, and the day's profit and loss goes back to the one account, so it compounds the way a real account does.
  • The result shows the whole account's curve and each portfolio's curve, together or side by side, how much each portfolio added, how closely their daily returns move together, and the peak exposure.

On paper and live, several portfolios run at once, one per account. On Bybit, each portfolio can trade on its own sub-account under your main account, with a daily rebalancer that makes the real transfers between them.

The app's combined result for two portfolios on one account over 2025: the whole account's curve and each portfolio's curve, a table per portfolio with allocation, net P&L, return on its share, max drawdown, Sharpe and trades, and how closely their daily returns move together: 0.38
The app's result for one real combined backtest: two portfolios on one account, both Donchian Breakout, one of the included example strategies, at default settings, one on 4-hour bars and one on 1-hour bars, each trading BTC, ETH and SOL, all of 2025, run once. Shown as it came out. An example, not an edge; a backtest is a simulation, not a promise of future results.

Does it still work bigger?

Capacity check. Reruns strategies at increasing order sizes, models market impact and shows where performance starts to deteriorate.

The same rigour in backtest and paper.

Backtest fills are simulated with fees, slippage and spread, not optimistic fills. See how backtests are simulated.

Paper trading is a quarantine. A candidate strategy runs on real market data without spending a live account, or even an exchange demo account, until it has earned its way to live. See paper and live.