Grid Trading
A-share grid trading: managing range, inventory and trend risk
Grid strategies split a stated price range into layered buy and sell levels to seek repeated range-bound price moves. The critical design choices are the range, spacing, per-level size, maximum inventory and what happens after a trend breaks the range.
Typical holding period
Depends on range behaviour; set a maximum inventory holding period and failure condition.
Rebalance and trigger
Check at grid touches; do not continually chase price by redefining the range.
Research universe
One or a small number of liquid instruments with modelled price-limit rules.
Research hypothesis
Write the hypothesis before reading the backtest
When price oscillates inside a tradeable range and costs are sufficiently low, layered trading may capture part of short-cycle variation. In trends, gaps or poor liquidity, inventory risk can accumulate quickly.
This guide is for research education and backtest design. It is not investment advice or a return promise; results depend on sample, cost, regime and execution.
Strategy rules
Turn the idea into zero-discretion rules
Price range
Define upper and lower bounds from volatility, support/resistance or fixed percentages.
States the range where the hypothesis applies.
Grid spacing
Use fixed price, percent or volatility-based levels.
Sets trade frequency and per-trade spread.
Inventory limit
Cap cumulative position, capital use and daily trade value.
Limits trend exposure and concentration.
Implementation
From signal to portfolio
- 1Fix range, grid count, per-level size, maximum inventory and reset condition before testing.
- 2Maintain separately sellable inventory and same-day purchases under T+1.
- 3Specify pause or exit rules for range breaks, repeated limits and no-trade periods.
- 4Simulate commissions, stamp duty, lot size, slippage and partial fills trade by trade.
A-share constraints
Execution belongs in the test
- T+1 means shares bought today cannot fund a same-day sell grid.
- Price limits can stop orders at the grid level and magnify inventory risk.
- Capacity must be constrained by trading value and impact, not only price history.
Validation checklist
Try to break the strategy first
Prefer stable regions that survive costs, regime changes and parameter perturbation to a single maximum return.
Risk map
How the strategy can fail
Research prompt
A first backtest specification
“For one liquid A-share instrument, test a range grid using 60-day volatility to set range and spacing, fixed per-grid size and maximum inventory. Model T+1, 100-share lots, price limits, partial fills, commission, stamp duty and slippage. Report inventory path, net performance, maximum capital use, regime results and parameter sensitivity.”
FAQ
Common questions
Do denser grids earn more?
Not necessarily. More trades reduce per-grid spread and can make costs, slippage and execution error dominate.
How should a grid handle a range break?
Define pause, reset or exit rules in advance and test their worst drawdown. Moving the range after the fact is not validation.
Next research step
Fix research conventions before the backtest
Use the related factors, data boundaries and out-of-sample review to turn a strategy idea into an auditable research record.