Understanding GridBot Statistics: A Complete Guide to Performance Tracking

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Automated trading bots have transformed the way traders interact with financial markets, offering precision, speed, and continuous operation. Among the most effective strategies is grid trading, where bots place buy and sell orders at predetermined price levels. To fully leverage this strategy, understanding GridBot statistics is essential. These metrics provide deep insights into performance, profitability, and market behavior across different timeframes.

This guide breaks down the key components of GridBot statistics into three main categories: grid row statistics, bot-level data, and overall summary reports. Whether you're evaluating a single trade line or analyzing long-term portfolio growth, this comprehensive overview ensures you can make informed decisions with confidence.


Grid Row Statistics: Monitoring Individual Trade Lines

Within the "Grid Statistic" tab of your selected bot, you’ll find detailed performance metrics for each individual grid row. These rows represent specific price levels where buy and sell orders are placed. Analyzing them helps identify high-performing zones and optimize future setups.

Key Metrics Per Grid Line

Each grid line displays the following information:

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Trade Activity Over Time

Two critical counters track transaction frequency:

These figures help assess market volatility and demand intensity at specific price points. High-frequency trading on certain lines may suggest strong support or resistance zones.

Profitability Across Currencies

Profits are tracked in multiple formats to give a holistic view:

Annualized percentages (% p.a.) are calculated based on actual gains since the start date and projected over a year, giving an estimated rate of return under current conditions.


Bot-Level Statistics: Deep Dive into Trading Activity

Beyond individual grid lines, each bot provides broader operational insights through several dedicated tabs.

Order History

This log records every order created by the bot, including:

Understanding these fields helps diagnose failed executions or optimize order placement logic.

Current Orders

Displays all open orders still active on the exchange. The structure mirrors the order history tab but focuses only on pending actions. Monitoring this section ensures transparency and control over live positions.

Trade History

The "Trades" tab logs every executed transaction with rich detail:

This granular data enables backtesting, tax reporting, and performance audits.

Daily Statistics

Summarizes daily trading outcomes:

This summary simplifies trend analysis over time—ideal for spotting profitable days or adjusting parameters during low-volatility periods.


Overall Summary Statistics: Portfolio-Wide Insights

Located in the main "Statistics" section, this high-level report aggregates data from all bots, including deleted ones, offering a complete historical record.

Data is grouped by:

Each entry includes:

These consolidated views are crucial for long-term strategy evaluation and portfolio health checks. They reflect true system-wide performance regardless of individual bot lifecycle status.


Frequently Asked Questions (FAQ)

Q: How is annualized return (% p.a.) calculated in GridBot statistics?
A: It's derived from actual profits recorded since the bot started, then extrapolated to a yearly rate using the current growth trend. No assumptions—only real trade data.

Q: Can I compare profitability across different trading pairs?
A: Yes. By converting all profits to BTC or USDT at execution time, GridBot enables apples-to-apples comparisons across any market.

Q: Why are deleted bots included in overall statistics?
A: To maintain data integrity and ensure accurate historical performance tracking—even after configuration changes.

Q: What does “Need analyze” mean in the trade log?
A: It flags trades that haven’t been processed by the profit calculation engine yet. Once analyzed, associated profits will be updated.

Q: How often are sliding windows (like 24h) updated?
A: Continuously. The counters use rolling periods, so they always reflect the most recent full cycle (e.g., last 24 hours up to now).

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By mastering these statistical layers—from granular grid rows to portfolio-wide summaries—you gain full visibility into your automated trading operations. With precise data at your fingertips, optimizing strategies becomes not just possible, but predictable.