DEXBot2 Tuning Cheat Sheet

This is a practical baseline for grid trading on DEXBot2. It is based on the engine's actual grid math and reset flow, not a universal "best" config.

Core rule

• Start from targetSpreadPercent ≈ 4 x incrementPercent.
• DEXBot2 enforces a minimum spread floor of about 2.1 x incrementPercent and at least two spread slots, so the spread cannot be arbitrarily tight.
• The tighter the grid, the more liquid and stable the market must be.

Structural vs Adaptive

Keep these structural settings static in normal operation:

• incrementPercent
• targetSpreadPercent
• activeOrders

These settings define ladder geometry and order-size distribution, so changing them is a retune, not a tactical response.

Use these adaptive settings for live trading behavior:

• weightDistribution
• minPrice / maxPrice ratio
• debt / collateral actions

That is the practical split:

• increment/spread define the grid
• AMA provides the anchor
• weights adapt to trend
• range ratio adapts slowly to former price action
• debt/collateral actions manage CR

Quick ladder

The main tradeoff is always the same:

• lower increment = tighter ladder, but more churn and smaller per-order sizes
• higher increment = wider ladder, less churn, but slower response and less quote quality

What each setting means

incrementPercent

This is the spacing between grid levels.

• lower values tighten the ladder
• higher values reduce churn and give the market more room to move
• if the pair is noisy or thin, do not force a tight increment

targetSpreadPercent

This is the empty gap between the best buy and best sell rails.

• keep it as small as the market can tolerate
• 4x increment is a healthy starting heuristic
• 3x is a conservative default, not a universal optimum

weightDistribution

This controls how size is distributed across the ladder.

• 0.5 is the neutral baseline
• values above 0.5 concentrate more size near the market-adjacent orders
• values below 0.5 flatten the ladder

Use weights to express inventory preference:

• mature, stable markets usually work best with flatter or near-neutral weights
• trending markets can justify stronger weighting if you want more size near the spread
• volatile markets usually prefer flatter weights so the bot does not over-commit near the edge
• lower volatility lets you increase weights and concentrate more funds near market-adjacent orders
• higher volatility argues for lower weights so more funds stay on the outer levels

In DEXBot2, buy-side allocation is reversed internally so the near-market buy orders also receive the larger share when weights are higher.

Negative weights are a special case:

• use slightly negative weights only when you intentionally want more size toward the outer ladder
• this makes sense in very volatile or mean-reverting markets where distant fills are realistic
• for most markets, lowering toward 0 is safer than going negative
• negative weights are not a default optimization; they are a deliberate fade/outer-liquidity choice

botFunds

This is how much of each side's available balance gets committed.

• 100% / 100% is aggressive
• leaving reserve gives you flexibility for fees, manual intervention, and regime changes
• if orders get too small, reduce commitment or reduce order count

activeOrders

This is the number of live orders kept near the market on each side.

• more orders = smoother ladder, but smaller orders
• fewer orders = larger orders, but less depth
• 20 / 20 is a solid conservative baseline
• as increment tightens, you may need fewer orders unless capital is large enough to keep order sizes meaningful

minPrice / maxPrice

These define the outer range of the grid.

• make the range only as wide as needed for the expected move until the next reset
• 3x is a conservative default, not a target
• mature and frequently reset markets often do not need that much width
• wider ranges make sense only if the bot must survive larger drift between resets
• practical range bands:
  • below 2x = very competitive
  • around 2x = competitive
  • around 3x = conservative
  • above 3x = very conservative
• treat range ratio as a slow-moving setting driven by former price action, not a fast tactical knob
• use dexbot tv <bot> to see the grid range and AMA recentering against real candles before fixing the bounds

gridPrice

This controls the reference price used when the grid is rebuilt.

• null uses the start price
• ama or ama1..ama4 recenters on the adaptive moving average
• use AMA when the market drifts enough that a static center becomes stale

Fund allocation logic

Use allocation settings to match market structure, not emotion.

• mature and liquid markets can support more aggressive deployment
• volatile or thin markets usually need more reserve and flatter allocation
• if you want stronger quoting near the spread, increase the weight
• if you want the ladder to feel smoother and less front-loaded, reduce the weight

The clean mental model is:

• incrementPercent controls spacing
• targetSpreadPercent controls the empty buffer
• weightDistribution controls size concentration
• botFunds controls risk budget
• activeOrders controls depth

When to adjust

Adjust when the market changes enough that the current settings no longer make sense.

Examples:

• spreads are too tight and the bot churns
• spreads are too wide and the bot misses fills
• order sizes become dust-like
• too much capital sits idle
• the price center keeps drifting away from the grid
• the pair becomes more or less liquid than before

Do not tune on a fixed schedule. Tune when the bot's behavior stops matching the market.

Resetting a grid

Use a normal reset when you want the bot to rebuild around the current market:

dexbot reset <bot>

That writes the recalculation trigger file. If the bot is running, it resets immediately; if it is stopped, it resets on the next start.

Use a hard cleanup only when you want a full wipe of persisted order state.

AMA in practice

AMA is the recentering mechanism.

• it is calculated from 1h candle closes
• it watches how far the adaptive center moves
• once the move crosses the configured threshold, DEXBot2 triggers a grid recalculation
• AMA recentering requires whitelisting the bot for the market adapter to work live (otherwise it only logs).
• gridPrice: "ama" tells the rebuilt grid to center itself on that AMA reference
• gridPrice: "pool" or gridPrice: "book" centers the rebuilt grid on the live pair price instead
• gridPrice: null falls back to the current startPrice reference

poolRef

When using startPrice: "pool", the bot discovers a pool matching your trading pair. If no such pool exists (e.g. a pair using a wrapped token without its own AMM pool), set poolRef to pin a proxy pool:

"poolRef": "1.19.48"

The pool is fetched directly by ID (get_objects) — no discovery, no caching. Enter just the number ("48") and the 1.19. prefix is added automatically. Leave unset for normal discovery behavior.

Practical interpretation:

• if the market trends, AMA helps the bot stay centered
• if the market is choppy, a higher delta threshold reduces unnecessary resets
• if the market is moving and the bot lags, lower the threshold and recenter sooner

Suggested operating defaults

For a conservative starting point:

• incrementPercent: 0.5
• targetSpreadPercent: 2.0
• activeOrders: 20 / 20
• weightDistribution: 0.5 / 0.5
• minPrice and maxPrice: as narrow as the expected drift allows, not blindly 3x

For a more competitive market:

• incrementPercent: 0.4
• targetSpreadPercent: 1.6
• keep order sizes meaningful before increasing order count
• use weights only if you have a reason to prefer front-loaded inventory

For a very competitive market:

• incrementPercent: 0.3
• targetSpreadPercent: 1.2
• ensure liquidity is strong enough to justify the tighter ladder
• watch churn, fills, and dust closely

For an aggressive market:

• incrementPercent: 0.2
• targetSpreadPercent: 0.8
• only use this when the pair is liquid enough to support it
• reset discipline and fee control matter more at this level

Bottom line

• tune for the market you actually have, not the market you wish you had
• tighter grids belong to more mature markets
• wider bounds are a safety margin, not a default optimum
• weights shape inventory behavior
• resets are for when the market regime has changed