The answers below are written assuming you've read at least the welcome page. If a term is unfamiliar, the glossary defines it. For platform errors and bug reports, see troubleshooting; for direct help, see support.
Platform & getting started
Do I need to know how to code?
No. The Visual Strategy Builder is the strategy. There is no script underneath that you'd ever need to edit. Every strategy is a node graph you build by dragging and connecting nodes.
The platform is opinionated about this: there's no "advanced mode" that drops you into Python. The reasoning is that a typed visual builder catches structural errors at design time, which is faster than discovering them in a backtest log at 2 AM. The handful of things that are awkward to express in nodes are mostly things experienced quants don't want to express anyway.
What kind of trader is this for?
Three groups, roughly:
- Discretionary traders who already have a sense of their edge and want to systematize it. AlgoLift gives them a way to encode their judgment into rules and stress-test whether it's real.
- Code-first quants tired of plumbing — fill modeling, data infrastructure, broker connectors. AlgoLift handles that layer so they can focus on strategy logic.
- Complete beginners who want to learn algorithmic trading from scratch. The Algotrading-101 Academy is a structured curriculum that teaches the underlying math and market mechanics, with labs in AlgoLift at every step.
If you're none of those — you're looking for a platform that hands you a pre-built winning strategy — AlgoLift is not the right place. There aren't any.
How long does it take to build my first strategy?
About 20 minutes from a blank canvas to a complete, backtested EMA-crossover strategy. The your first strategy walkthrough is the hands-on tutorial.
What markets and instruments are supported?
Futures: ES, MES, NQ, MNQ, GC, MGC, CL, MCL, RTY, M2K, YM, MYM, and the corresponding micro contracts. Several softs and metals. Equities: major US stocks and ETFs. Crypto: BTC-PERP, ETH-PERP, and most major pairs on Binance, Coinbase, and Bybit. The exact list per broker depends on the broker connector you use during export.
Can I trade options?
Limited support today. The platform's primary focus is futures, equities, and crypto. Options strategies that depend on greeks or volatility surfaces are not currently first-class.
What brokers can I connect to?
For live trading, the supported brokers today are Interactive Brokers, Tradovate, NinjaTrader, TopstepX (for prop accounts), and the major crypto exchanges (Binance, Coinbase, Bybit). See exporting & going live for the details on how broker connections work.
Backtesting
Why does my backtest look so much better than my forward test?
Three common causes, in roughly the order they should be investigated:
- Look-ahead bias. Your strategy is using information that wouldn't have been available at the moment of the trade — most commonly, reading the closed-bar value of the current bar before the bar has closed. Check the forward test divergence report — if live trades don't match backtest trades on the same days, this is almost always why.
- Optimistic fill settings. If you backtested with no slippage, no commission, or fills at the trigger price exactly, the live execution is going to be worse — sometimes much worse. Re-run with the Realistic slippage model and your broker's actual commission rate.
- Overfitting. Your strategy memorized the past instead of finding an edge. Run a parameter sweep — if the strategy only works at one specific parameter value, it's not a strategy, it's a coincidence. The overfitting in trading page covers detection in depth.
How many years of data should I backtest on?
For most futures and equities, 5–10 years is the right range. You want enough data to cover multiple regimes (the 2018 Q4 selloff, 2020 COVID, 2022 rate hikes, the 2023 yen-carry unwind) so the strategy has been stress-tested on real market state changes — not just the latest bull run.
For very new instruments (newer crypto pairs, recently-listed contracts), you may have less data available. Less than 2 years of data is rarely enough to call a strategy validated.
What does "tick-accurate" actually mean?
It means the backtest engine processes every individual price print in the historical tape, not just the open/high/low/close of each bar. This matters because inside a 1-minute bar, the order in which the high and low formed determines whether your stop or your target was hit first. Bar-only engines guess; AlgoLift's backtest engine knows. See tick vs. bar data for the full mechanics.
How fast does a backtest run?
A 5-year MES 5m backtest runs in 30–90 seconds. A 10-year multi-instrument test runs in 2–4 minutes. The speed comes from parallel cloud execution — the engine splits the date range into monthly chunks that run on separate workers simultaneously.
Why is my strategy losing money in backtest even though my logic seems right?
Usually one of three things:
- The signal is real but the exits are wrong. Most "logic seems right" strategies have entries that work and exits that don't — the strategy enters profitably but exits at the wrong time. Look at the MAE/MFE distribution in Analytics.
- The signal is real but the position sizing is wrong. A strategy with 0.05R per-trade risk can have a real edge and still lose to commissions and slippage. The risk management page covers sizing math.
- The signal isn't actually an edge. EMA crossovers without filters lose money on most major instruments because the markets are mostly choppy. Strategies typically need at least one filter (regime, volatility, session) on top of a base signal to be profitable.
Strategy design
Should I start with mean reversion or momentum?
Most beginners are better served starting with momentum strategies. Momentum signals are visually intuitive (you can see them on a chart), tend to have larger per-trade edges, and degrade more slowly than mean reversion. Mean reversion has its place — see mean reversion strategies — but it's harder to backtest honestly because it often requires more nuanced execution.
How many indicators should my strategy use?
Fewer than you think. Every parameter is a knob the optimizer can use to chase noise. A 2-indicator, 4-parameter strategy is much harder to overfit than a 5-indicator, 12-parameter one. The strategies that survive live deployment almost always have 2–4 main components, not 8.
The overfitting in trading page covers the math behind this.
Can I import strategies from TradingView, NinjaTrader, or Pine Script?
No automated importer today. You'd rebuild the strategy as a node graph. In practice this is usually faster than expected — even complex TradingView scripts often translate to 10–20 nodes on the canvas.
How do I combine multiple strategies into a portfolio?
Use the Portfolio Builder. You stack 2–8 validated strategies, set allocation weights, and see the combined equity curve, correlation matrix, and risk-adjusted metrics. The whole point is that uncorrelated strategies smooth each other's drawdowns — which is the only structural reason to run a portfolio at all.
Optimization
When should I optimize parameters?
After you've confirmed the strategy has a plausible shape at default parameters, not before. If a strategy doesn't make money with reasonable defaults, optimization rarely fixes it — it just finds the parameter set that overfits the past most. See parameter optimization.
What's the difference between optimization and walk-forward?
A one-shot optimization finds the parameter set that performed best on a specific historical window. The same parameter set may or may not perform well on future data — usually not.
Walk-forward optimization addresses this by repeatedly fitting on a training window and evaluating on a held-out window, rolling forward in time. You see whether "best parameters from each window" continue to work on the next window. If yes, the strategy probably has a real edge. If no, the optimization was fitting noise.
My strategy works at exactly RSI period 14 but fails at 13 or 15. Is that bad?
Yes. A strategy that lives on a single parameter value is fit to a coincidence the optimizer happened to find. Real edges produce a plateau of parameter values that all work reasonably well — small changes shouldn't crater performance. This is the most important diagnostic from a parameter sweep.
Forward testing & deployment
How long should I forward-test before going live?
Depends on trade frequency. The number of trades matters more than calendar time:
- Intraday scalping (20–100 trades/week): 2 weeks minimum, ~40–200 trades.
- Day trading (3–10 trades/week): 4 weeks, ~30 trades.
- Swing trading (0.5–2 trades/week): 8–12 weeks, ~10 trades.
- Position / macro (less than 1 trade/week): 6+ months.
See forward testing for the full criteria.
Where should I run my live executable?
For most users, a $10/month VPS near your broker's data center is the right answer. Chicago for CME futures, New York for equities, Tokyo or Frankfurt for crypto. The latency drop alone usually pays for the VPS in the first month, and you don't have to worry about your laptop going to sleep or losing Wi-Fi.
See exporting & going live for the trade-offs between laptop, home machine, and VPS.
Can AlgoLift see my live trades?
No. The exported executable runs entirely on your hardware. It reads ticks directly from your broker's market data feed and sends orders directly back. Your broker API keys are entered into the local executable and never touch AlgoLift's servers. We can't see live trades because we're not in the loop.
What happens if AlgoLift's web app is down?
Your live executable keeps running. The cloud platform is for research — backtests, optimization, portfolio analysis. Live execution is local and decoupled. A maintenance window on the web app has zero effect on running strategies.
Can I run the same strategy on multiple accounts?
You can run multiple copies of the same executable, each connected to a different broker account. The executables are independent — they don't know about each other and don't coordinate. Don't run two copies on the same broker account; they'll both try to manage positions and the resulting double-trading is one of the most expensive bugs in systematic trading.
Pricing & account
Is there a free tier?
The welcome page covers what's free. In short: research is free — you can build strategies, run backtests, optimize, and forward-test without paying. Live deployment requires a paid plan.
How much capital do I need to start trading live?
Depends entirely on the strategy. The platform doesn't impose a minimum. The risk management page covers the math of what's mathematically survivable at different account sizes — short version, $5,000 is the rough floor for trading MES with reasonable sizing, less than that and ordinary losing streaks will eat your account.
Do you offer prop firm support?
Yes. The prop firm traders use case covers the platform's built-in modeling for FTMO, TopStep, Apex, and others — including the daily-loss and trailing-drawdown rules as automatic kill-switches in your exported executable.
Common platform questions
Where do I find my old strategies?
Dashboard → Strategies. Every strategy you've ever built lives there, sorted by last modified. Click any one to open it in the Visual Builder.
Can I share strategies with someone else?
Strategies are private by default. You can export a strategy as a .algolift file and share that file directly. The recipient can import it on their own account. The exported executable also contains your full compiled strategy logic — so be careful who you share executables with, since they could run your strategy on their own broker account.
Can I edit a strategy that's currently in forward testing?
Editing the strategy in the Visual Builder won't affect the running forward test — the forward test runs a snapshot of the strategy at the moment it was deployed. To deploy your edits, stop the existing forward test and deploy a new one.
How do I get help?
Three options, in roughly the order of speed:
- Search this guide. The search bar (Shift+S anywhere on the docs) usually surfaces the answer.
- The glossary and troubleshooting pages.
- The support page — for direct help from the team.