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Glossary

Dry-run (paper trading) mode

A dry-run is the dress rehearsal: the bot watches real prices, makes real decisions, places simulated trades. Everything is live except the money.

What it is

Dry-run (paper trading) mode, explained.

Dry-run mode — also called paper trading — runs a trading bot against live market prices with simulated money. The bot receives real-time data, evaluates its strategy, and 'places' trades that are tracked in a virtual wallet. Every part of the pipeline is real except the capital at risk.

Dry-run answers a different question than backtesting. A backtest asks 'would this strategy have worked on past data?'; a dry-run asks 'does this bot behave correctly on today's market, right now?'. It catches what historical simulation cannot: how the strategy handles current conditions and how the whole system behaves end-to-end in real time.

The honest limitation: simulated fills are optimistic. A dry-run fills orders at observed market prices, without your order actually competing in the book — so live results will include slippage the simulation did not. That makes dry-run a necessary gate rather than a sufficient one: pass the backtest, pass the dry-run, then start live with small size.

How it works

From idea to a running bot.

The standard validation ladder puts dry-run between simulation and real money.

  1. Backtest first

    Establish on historical data that the strategy has a plausible edge — metrics, drawdown, trade count. No point rehearsing a play that does not work on paper.

  2. Dry-run on live prices

    Deploy the identical strategy in dry-run mode. Watch it trade current markets for long enough to see varied conditions — days to weeks, depending on trade frequency.

  3. Compare and graduate

    Do the live-market decisions match what the backtest led you to expect — frequency, direction, holding times? If yes, go live with conservative size. If no, investigate before real money finds the discrepancy for you.

Who it's for

Built for the way you trade.

Dry-run mode serves everyone from first-timers to veterans.

First-time bot users

Watching a bot trade simulated money on real markets is the fastest safe way to understand what automated trading actually feels like — including its boring stretches.

Strategy graduates

A promising backtest earns a dry-run, not a live deployment. The rehearsal catches regime mismatches and configuration surprises while they are still free.

VolatiCloud users

Every VolatiCloud bot can run in dry-run mode with the exact same strategy, settings, and dashboard as live trading — flip to live only when the rehearsal has earned it.

  • Live prices, real decisions, simulated money
  • Validates behaviour a backtest cannot show
  • Simulated fills are optimistic — no real slippage
  • The standard gate between backtest and live capital
  • Every VolatiCloud bot supports dry-run mode
FAQ

Frequently asked questions.

What is the difference between dry-run and backtesting?

Backtesting replays historical data to evaluate a strategy's past hypothetical performance. Dry-run executes the strategy on live current prices with simulated money. Backtesting explores history; dry-run rehearses the present. A sound workflow uses both, in that order.

How long should I dry-run a strategy?

Long enough to see the strategy make a meaningful number of trades across varied conditions — typically days to a few weeks for active strategies, longer for slow ones. A dry-run that has not yet traded has not yet validated anything.

Will dry-run results match live trading?

Closely but not exactly. Dry-run fills are simulated at observed prices, so live trading adds slippage and fill uncertainty the rehearsal did not have. Treat dry-run success as necessary, not sufficient — and start live with small size.

Does VolatiCloud support paper trading?

Yes. Dry-run is a first-class mode on every bot: same strategy, same configuration, same monitoring dashboard as live trading, with a simulated wallet. Strategies can be flipped to live once they have proven themselves in rehearsal.

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