Frequently Asked Questions

Getting Started

How many strategies can I import?

There is no hard limit on the number of strategies you can import. Import as many as you need.

What file formats are supported?

AlgoChef accepts CSV, TXT (with various delimiters), and TradeStation/Multicharts RINA XML files. See the Import Guide for details.

What's the minimum data needed?

At minimum, you need entry dates, exit dates, and P&L (in dollars or points) for each trade. More fields unlock more metrics.

How many trades do I need for reliable analysis?

The more trades, the more reliable the analysis. AlgoChef requires a minimum number of trades for scoring — below this threshold, circuit breakers cap the score. For the most robust statistical results, aim for as many trades as possible. The platform will guide you if your trade count is too low for specific features. See Why Strategies Fail — Insufficient Sample Size for more context on why this matters.

Does AlgoChef work with NinjaTrader or MetaTrader?

AlgoChef accepts CSV exports from any platform, including NinjaTrader and MetaTrader. Export your trade history as CSV from your platform and use the import wizard to map your columns. See the CSV Format Reference for details.

How do I report a bug or request a feature?

If you're logged in, use the Bug Report and Feature Request options available inside the app. For general questions, use the contact form on our website.

What is the difference between backtesting and paper trading?

Backtesting replays historical data through your strategy rules to measure how it would have performed. Paper trading runs the strategy forward in real-time on live market data without risking capital. Both are useful, but neither alone proves a strategy is robust. AlgoChef goes further by applying statistical validation — scoring your backtest across profitability, risk, confidence, and health dimensions — so you can quantify how trustworthy those backtest results really are before you paper trade or go live. See Why Strategies Fail in Live Trading for the most common failure modes.

Scoring

What makes AlgoChef's scoring system different?

Most platforms show you a handful of standalone metrics — Sharpe Ratio, net profit, max drawdown — and leave you to interpret them yourself. AlgoChef's five proprietary scores evaluate 20+ metrics across four independent dimensions (Profitability, Risk, Confidence, and Health) and combine them into a single composite (CSI). You get an institutional-grade snapshot of your strategy's quality in seconds, covering profitability, capital protection, statistical reliability, and real-time degradation — all at once.

Why is my CSI score 0 or very low?

Check for circuit breakers. The CSI will be capped or zeroed when fundamental problems are detected, such as:

• Too few trades — Import more trade history
• Excessive drawdown — Strategy has too much capital risk
• No profitability — Strategy is not generating positive returns
• Unusual win rate — Extremely low or high win rates may indicate a data issue

See Why Strategies Fail for a full explanation of the most common validation problems.

Why is my Confidence Score 0?

The Confidence Score requires a minimum number of trades. Below this threshold, it's automatically set to 0. This is the most common reason for a low CSI score.

Can I improve my scores by adjusting settings?

Scores are based on your actual trade data. The only way to improve them is to improve the strategy itself (better entries, exits, risk management) or to provide more trade data for better statistical reliability.

What's the difference between CSI and Health Score?

CSI evaluates absolute quality — is this a good strategy? Health Score evaluates recent performance — is this strategy getting worse? A strategy can have a high CSI (historically good) but a low Health Score (recently degrading).

What is a good Sharpe Ratio for a trading strategy?

A Sharpe Ratio above 1.0 is generally considered acceptable, above 1.5 is good, and above 2.0 is excellent — but context matters. A high Sharpe alone doesn't guarantee robustness. AlgoChef incorporates the Sharpe Ratio into both the Risk Score and Confidence Score, alongside dozens of other metrics, so you're never relying on a single number.

What is a good Profit Factor?

Profit Factor (gross profit ÷ gross loss) above 1.0 means the strategy is profitable. Above 1.5 is solid, and above 2.0 is strong. However, a high Profit Factor on a small sample can be misleading. AlgoChef's Confidence Score accounts for sample size and statistical significance so you can tell whether your Profit Factor is trustworthy or just noise.

How many trades do I need to backtest a strategy reliably?

More is always better. With fewer than 30 trades, most statistical measures are unreliable. AlgoChef's Confidence Score directly penalizes small sample sizes — if your trade count is too low, circuit breakers will cap your scores to prevent overconfidence in statistically thin results.

How do I know if my strategy is curve-fitted?

Curve-fitting (overfitting) means your strategy is tuned to past data rather than capturing a genuine edge. Warning signs include exceptional backtest results that don't hold up out-of-sample. AlgoChef's Monte Carlo simulation stress-tests your strategy under randomized conditions, and the IS/OOS validation compares in-sample performance against out-of-sample results — a large gap is a red flag for overfitting.

Strategy Validation

What is In-Sample vs Out-of-Sample testing?

In-Sample (IS) data is the portion of your trade history used to develop or optimize a strategy. Out-of-Sample (OOS) data is a held-back portion the strategy has never "seen." Comparing IS and OOS performance reveals whether your strategy captures a real edge or is just memorizing past data. AlgoChef automatically splits your trades and measures the divergence as part of the Health Score and Monte Carlo IS/OOS validation.

What is walk-forward testing?

Walk-forward testing repeatedly optimizes a strategy on a rolling in-sample window, then validates it on the next out-of-sample window. This process simulates how a strategy would perform if re-optimized periodically in real trading. It's one of the strongest defenses against curve-fitting because every validation segment is truly unseen data.

What is Monte Carlo simulation and why does it matter?

Monte Carlo simulation generates thousands of randomized variations of your trade sequence to see how results change under different conditions. It answers questions like "What's the worst drawdown I should realistically expect?" and "How likely am I to hit my profit target?" AlgoChef's Monte Carlo engine offers five simulation methods and recalculates all scoring dimensions for each run — giving you confidence intervals across 20+ metrics, not just a simple equity fan chart.

What is the difference between optimization and curve-fitting?

Optimization is the legitimate process of tuning strategy parameters to improve performance. Curve-fitting is optimization taken too far — the parameters become tailored to historical noise rather than a repeatable edge. The line between them is statistical: if performance collapses on unseen data, you've curve-fitted. AlgoChef helps you detect this through the Confidence Score (which penalizes fragile statistics) and Monte Carlo IS/OOS validation (which compares in-sample and out-of-sample results).

Features

How does Monte Carlo simulation work?

Monte Carlo runs thousands of randomized variations of your trade history to test robustness. Unlike most tools that only simulate net profit and max drawdown, AlgoChef recalculates all four scoring dimensions (Profitability, Risk, Confidence, and CSI) for each simulation run — so you see confidence intervals across 20+ metrics, not just a single equity fan chart. See Monte Carlo Simulation for the five methods.

Can I combine strategies in a portfolio?

Yes! Portfolio Studio lets you allocate capital across multiple strategies, analyze correlations, and backtest rebalancing approaches.

How often should I check the Health Monitor?

For actively traded strategies, check weekly (or every 10 trades). The Health Monitor compares recent performance against historical baselines — regular checks help catch degradation early.

How do I share a strategy comparison?

From the Comparison page, click "Share" to generate a public link. Recipients can view the comparison without an AlgoChef account.

Can I run Monte Carlo on a portfolio?

Not directly — Monte Carlo runs on individual strategies. However, you can build your portfolio in Portfolio Studio first, then run Monte Carlo on each constituent strategy individually to validate robustness before combining them.

How does AlgoChef compare to Strategy Quant or Market System Analyzer?

AlgoChef is a validation platform, not a strategy builder. Strategy Quant X generates and optimizes strategies automatically — AlgoChef validates whether those strategies are worth trading. Many traders use both together. Market System Analyzer focuses primarily on position sizing and Monte Carlo — AlgoChef covers the full validation workflow including scoring, portfolio construction, and health monitoring. See the full comparison page for details.

Data & Privacy

Is my trade data secure?

Your data is stored securely with row-level security — only you can access your strategies.

Can I delete my data?

You can delete individual strategies from the Strategy Hub. You can delete your account and all associated data.

Does AlgoChef execute trades?

No. AlgoChef is a pure analysis platform. It does not connect to brokers, execute trades, or manage money. All trading decisions are yours.

Pricing & Trial

Is there a free trial?

Yes — AlgoChef offers a free trial with no credit card required. You can import and analyze strategies immediately. See the pricing page for trial limits and plan details.

What happens when my trial ends?

Your data is preserved. You can upgrade to a paid plan at any time to regain full access to your imported strategies and results.

Troubleshooting

My import failed — what do I check?

• Verify the file format (CSV, TXT, or TradeStation/Multicharts RINA XML)
• Make sure date columns are in a recognizable format
• Ensure there's at least one P&L column (dollars or points)
• Check for special characters or encoding issues in the file

Metrics show N/A — why?

Some metrics require specific data:

• MAE/MFE require MAE, MFE value in dollars
• ATR metrics require ATR data in the import
• Profit Consistency requires 12+ months of data
• Stability metrics require a minimum number of trades

The scores don't match what I expected

AlgoChef's scores are designed to be conservative. A "real" Sharpe Ratio of 1.5 is genuinely good — most strategies score lower than traders expect because AlgoChef accounts for all trades including outliers and uses robust statistical methods.