How our products are built, what ships in each release, and the decisions we make under the hood. Straight from the EasyTrading team.
A trading journal template that separates the plan, execution and rule adherence from profit. Three examples and a review process for manual and algo trading.
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CopyTrader’s new pricing: budget for active connections, pooled places and separate project costs. New accounts receive $20 in service credit with no expiry.
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Trading bot or copy trading? Compare signals, rule-based execution and sharing trades with an audience. Choose a task and know what to check before connecting.
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A completed educational crypto bot specification: closed candles, entry and exit rules, position sizing, data errors, and three acceptance scenarios before backtesting.
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What to delegate to AI when working on a strategy, when a trader’s confirmation is needed, and how to retain manual control over code, parameters and the start of live trading.
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Final P&L can show that an outcome changed, but rarely explains why. Trace data, decisions, orders, fills and positions to the earliest mismatch.
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A profitable backtest, a successfully copied order and a live return are three different kinds of evidence. A trading workflow should never present them as interchangeable.
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A smooth equity curve may come from a sound idea, parameter fitting, or fills that were never attainable. We take one backtest from hypothesis to a decision: reject it, revise it, or move it to forward validation.
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Local stdio describes how an MCP client talks to the host, but it does not guarantee a fully local AI process. This guide maps the complete data path and practical security boundaries.
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An AI agent may improve a strategy only on paper if the data, fees or execution model changed with the code. Here is what to preserve so another run can reproduce the result.
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We compared two ways to copy a position. On one day of data they behaved identically; differences appeared after rounding and changed order-state rules.
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