A rule-based order setup that places buy and sell instructions at predefined price levels. It automates order placement; it does not guarantee a profit, avoid directional exposure, or make a range persist.
Supports: Explains active prediction-based trading, transaction costs, missed-opportunity risk, and the need to consider whether a strategy fits the investor rather than presenting a trading method as universally suitable.
Supports: Explains that performance information can depend on calculation assumptions and that past performance does not necessarily predict future results.
Supports: Explains that market-order execution price is not guaranteed and limit orders can be unfilled, relevant to automated order execution constraints.
Grid trading automates predefined orders; it does not guarantee profit or eliminate directional and inventory exposure
Spacing, range, size, order behavior, and re-entry rules are implementation choices that must be stated
More fills can increase fees, spread, slippage, inventory exposure, and taxable events instead of profit
Evaluate exact venue rules with realistic execution conditions and avoid treating backtests or annualized figures as forecasts
A user configures a BTC/USD grid with a stated range and order size. Before activating it, they include fees, expected spread, partial fills, custody and API permissions, maximum inventory, and a pause rule. If price leaves the range, they record the result and reassess under their stated rules instead of calling the setup market-neutral or assuming past fills guarantee a return.
The difference between a quoted or expected trade result and the result that can execute under the protocol's state and limits.
The process of setting an intended exposure for a position. It requires explicit assumptions about price, instrument, leverage, liquidity, costs, correlations, and loss tolerance; no universal percentage or formula is suitable for every account or product.
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