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tinkle-community 7e96c5d0f2 Ai grid (#1344 )

* feat: add AI grid trading and market regime classification

- Add GridTrader interface with PlaceLimitOrder, CancelOrder, GetOrderBook
- Implement GridTrader for all exchanges (Binance, Bybit, OKX, Bitget, Hyperliquid, Aster, Lighter)
- Add grid engine with ATR-based boundary calculation and fund distribution
- Add market regime classification documents (Chinese/English)
- Add GridConfigEditor component for frontend configuration

* fix: implement GetOpenOrders for Lighter exchange

* debug: add logging for Lighter GetActiveOrders API call

* fix: correct Lighter API response parsing for GetOpenOrders

- Changed response field from 'data' to 'orders' to match Lighter API
- Updated OrderResponse struct to match Lighter's actual field names
- Fixed field types: price/quantity as strings, is_ask for side

* feat: implement GetOpenOrders for Aster, OKX, Bitget exchanges

- Aster: uses /fapi/v3/openOrders endpoint
- OKX: uses /api/v5/trade/orders-pending and orders-algo-pending
- Bitget: uses /api/v2/mix/order/orders-pending and orders-plan-pending

* fix: address code review issues for GetOpenOrders

- Add error logging for OKX/Bitget API failures (was silently swallowed)
- Fix Lighter position side logic to handle reduce-only orders
- Change verbose debug logs from Infof to Debugf level

* fix: provide FromAccountIndex and ApiKeyIndex for Lighter nonce auto-fetch

Root cause: SDK requires these fields to fetch nonce from API, otherwise nonce gets cached/stuck

* fix: use auth query parameter instead of Authorization header for Lighter API

* test: add Lighter API authentication tests and diagnostic tools

* fix(grid): add leverage setting before order placement

CRITICAL BUG FIX:
- Call SetLeverage() in GridTraderAdapter.PlaceLimitOrder()
- Set leverage during grid initialization
- Log leverage setting results

* fix(grid): prevent CancelOrder from canceling all orders

CRITICAL BUG FIX:
- CancelOrder no longer calls CancelAllOrders
- Try exchange-specific CancelOrder if available
- Return error if individual cancellation not supported

* fix(grid): add total position value limit check

CRITICAL: Prevent excessive position accumulation
- New checkTotalPositionLimit() function
- Checks current + pending + new order value
- Rejects orders that would exceed TotalInvestment x Leverage
- Logs clear error messages when limit exceeded

* feat(grid): implement stop loss execution

CRITICAL: Add code-level stop loss protection
- New checkAndExecuteStopLoss() function
- Checks each filled level against StopLossPct
- Automatically closes positions exceeding stop loss
- Called during every grid state sync

* feat(grid): add breakout detection and auto-pause

CRITICAL: Detect price breakout from grid range
- New checkBreakout() function to detect upper/lower breakouts
- Auto-pause grid on significant breakout (>2%)
- Cancel all orders when breakout detected
- Prevent continued losses in trending market
- Minor breakouts (1-2%) logged for AI consideration

* feat(grid): enforce max drawdown limit with emergency exit

CRITICAL: Add drawdown protection
- New checkMaxDrawdown() function tracks peak equity
- emergencyExit() closes all positions and cancels orders
- Auto-pause grid when MaxDrawdownPct exceeded
- Protect capital from excessive losses

* feat(grid): enforce daily loss limit

- Add checkDailyLossLimit() function to check if daily loss exceeds limit
- Track daily PnL with auto-reset at midnight
- Pause grid when DailyLossLimitPct exceeded
- Add updateDailyPnL() helper for realized PnL tracking
- Prevent excessive single-day losses

* fix(grid): update daily PnL when stop loss is executed

The updateDailyPnL() function was added but never called, leaving
DailyPnL always at 0 and preventing daily loss limit checks from
triggering.

This fix updates DailyPnL and TotalProfit directly in checkAndExecuteStopLoss()
when a stop loss is executed. We update directly rather than calling
updateDailyPnL() because the mutex is already held in that function.

* feat(grid): add automatic grid adjustment

- New checkGridSkew() detects imbalanced grid
- autoAdjustGrid() reinitializes around current price
- Prevents grid from becoming ineffective after drift
- Triggers when one side is 3x more filled than other

* fix(grid): recalculate bounds in autoAdjustGrid before reinitializing levels

Critical fix for grid auto-adjustment:
- Recalculate grid bounds (UpperPrice, LowerPrice, GridSpacing) centered
  on current price before reinitializing grid levels
- Preserve filled positions during adjustment by saving and restoring
  them to the closest new level after reinitialization
- Hold mutex lock for the entire adjustment operation to ensure atomicity
- Add locked variants of calculateDefaultBounds, calculateATRBounds, and
  initializeGridLevels to use during adjustment

Without this fix, autoAdjustGrid was using old boundaries when creating
new grid levels, defeating the purpose of auto-adjustment when price
moved significantly.

* fix(grid): improve order state sync logic

- Don't assume missing orders are filled
- Compare position size to determine fill vs cancel
- Properly reset cancelled orders to empty state
- More accurate grid state tracking

* fix(grid): use actual PositionSize sum instead of count in syncGridState heuristic

The position-based heuristic was using `float64(previousFilledCount) * level.OrderQuantity`
which incorrectly assumed uniform order quantities. Since the grid uses weighted distribution
(gaussian, pyramid, uniform) where orders have different quantities, this could lead to
incorrect fill detection.

Now sums the actual PositionSize from filled levels for accurate comparison.
Also adds warning log when GetPositions() fails.

* docs: add grid market regime detection design

Design for enhanced market state recognition with:
- Multi-dimensional indicators (ATR, Bollinger, EMA, MACD, RSI)
- Multi-period box indicators (72/240/500 1h candles)
- 4-level ranging classification
- Breakout detection and handling
- Frontend risk control panel

* docs: add grid market regime implementation plan

20 tasks covering:
- Donchian channel calculation
- Box data types and API
- Regime classification (4 levels)
- Breakout detection and handling
- False breakout recovery
- Frontend risk panel
- AI prompt updates

* feat(market): add Donchian channel calculation

Add calculateDonchian function to compute highest high and lowest low
over a specified period. This is the foundation for box (range) detection
in the multi-period box indicator system for grid trading.

* fix(market): handle invalid period in calculateDonchian

* feat(market): add BoxData and RegimeLevel types

* feat(market): add GetBoxData for multi-period box calculation

Adds calculateBoxData internal function and GetBoxData public API that
fetches 1h klines and computes three Donchian box levels (short/mid/long).
This will be used by the grid trading system to detect market regime.

* feat(store): add box and regime fields to grid models

* feat(trader): add regime classification and breakout detection

Implements Tasks 6-9 for grid market regime awareness:
- Task 6: classifyRegimeLevel with Bollinger/ATR thresholds
- Task 7: detectBoxBreakout for multi-period box breakouts
- Task 8: confirmBreakout with 3-candle confirmation logic
- Task 9: getBreakoutAction mapping breakout levels to actions

* feat(trader): integrate box breakout detection into grid cycle

- Task 10: Add checkBoxBreakout with 3-candle confirmation
- Task 11: Add checkFalseBreakoutRecovery for 50% position recovery
- Task 12: Add box/breakout/regime fields to GridState

* feat: add grid risk panel with API endpoint

- Task 13: Add GridRiskInfo type to frontend
- Task 14: Add /traders/:id/grid-risk API endpoint
- Task 15: Add GetGridRiskInfo method to AutoTrader
- Task 16: Create GridRiskPanel component with i18n

* feat(kernel): add box indicators to AI prompt

- Add BoxData field to GridContext
- Add box indicator table to both zh/en prompts
- Show breakout/warning alerts based on price position

* feat(web): integrate GridRiskPanel into TraderDashboardPage

* feat(lighter): improve API key validation and market caching

- Add API key validation status tracking
- Add market list caching to reduce API calls
- Improve logging (debug vs info levels)
- Add comprehensive integration tests
- Update trader manager and store for lighter support

* fix: remove hardcoded test wallet address

* fix(grid): improve GridRiskPanel layout and fix liquidation data

- Make panel collapsible with summary badges when collapsed
- Use compact 2-column grid layout for detailed info
- Fix auth token key (token -> auth_token)
- Only calculate liquidation distance when position exists

* fix(grid): add isRunning checks to prevent trades after Stop() is called

2026-01-19 12:07:14 +08:00

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Market Regime Classification Framework

A comprehensive market state identification system for quantitative trading strategy matching

1. Classification Dimensions Overview

Market state identification requires analysis across multiple dimensions:

Dimension	Sub-dimensions	Description
Trend	Direction, Strength	Determine market movement direction and momentum
Volatility	Amplitude, Frequency	Measure price fluctuation characteristics
Structure	Pattern, Phase	Identify market structure and cycle position

2. Primary Classification (5 Categories)

2.1 Classification Overview

Code	Name	Key Characteristics	Suitable Strategies
`TREND_UP`	Uptrend	Higher highs & higher lows	Trend following, Breakout
`TREND_DOWN`	Downtrend	Lower highs & lower lows	Trend following, Short selling
`RANGE`	Range-bound	Price oscillates within bounds	Grid trading, Mean reversion
`TRANSITION`	Transition	Uncertain directional period	Wait & watch, Small positions
`BREAKOUT`	Breakout	Price breaks key levels	Breakout trading

2.2 Identification Indicators

ADX (Average Directional Index): Measures trend strength
- ADX > 25: Clear trend exists
- ADX < 20: Range-bound market
EMA Alignment: Determines trend direction
- EMA20 > EMA50 > EMA200: Bullish alignment
- EMA20 < EMA50 < EMA200: Bearish alignment

3. Secondary Classification (18 Sub-categories)

3.1 Uptrend Sub-categories (5 Types)

Code	Name	Technical Features	Quantitative Indicators
`TU_STRONG_LOW_VOL`	Strong Uptrend · Low Vol	Steady rise, shallow pullbacks	ADX>40, ATR%<2%, Pullback<38.2%
`TU_STRONG_HIGH_VOL`	Strong Uptrend · High Vol	Rapid surge, high volatility	ADX>40, ATR%>4%, MACD histogram expanding
`TU_WEAK_CHOPPY`	Weak Uptrend · Choppy	Two steps forward, one back	ADX 20-30, RSI oscillating 50-70
`TU_PARABOLIC`	Parabolic Acceleration	Exponential price increase	Price far from MA, RSI>80, Volume surge
`TU_EXHAUSTION`	Uptrend Exhaustion	New highs but weakening momentum	Price new high + MACD/RSI divergence

Strategy Matching:

Strong Low Vol: Heavy trend following, pyramid adding
Strong High Vol: Medium position, trailing stops
Weak Choppy: Light swing trading
Parabolic: Cautious, prepare to exit
Exhaustion: Reduce positions, prepare for reversal

3.2 Downtrend Sub-categories (5 Types)

Code	Name	Technical Features	Quantitative Indicators
`TD_STRONG_LOW_VOL`	Strong Downtrend · Low Vol	Steady decline, weak bounces	ADX>40, ATR%<2%, Bounce<38.2%
`TD_STRONG_HIGH_VOL`	Strong Downtrend · High Vol	Panic selling, wild swings	ADX>40, ATR%>5%, VIX spike
`TD_WEAK_CHOPPY`	Weak Downtrend · Choppy	Grinding lower with bounces	ADX 20-30, RSI oscillating 30-50
`TD_CAPITULATION`	Capitulation	High volume crash, extreme fear	RSI<20, Volume>3x average
`TD_EXHAUSTION`	Downtrend Exhaustion	New lows but selling pressure fading	Price new low + MACD/RSI divergence

Strategy Matching:

Strong Low Vol: Short trend following
Strong High Vol: Stay flat or light hedge
Weak Choppy: Wait for stabilization
Capitulation: Light bottom fishing possible
Exhaustion: Gradually build long positions

3.3 Range Sub-categories (4 Types)

Code	Name	Technical Features	Quantitative Indicators
`RG_TIGHT_LOW_VOL`	Tight Range · Low Vol	Extreme contraction, coiling	BB Width<2%, ATR at new lows
`RG_TIGHT_HIGH_VOL`	Tight Range · High Vol	Violent swings within range	BB Width<3%, ATR%>3%
`RG_WIDE_LOW_VOL`	Wide Range · Low Vol	Large range, slow movement	BB Width>5%, ATR%<2%
`RG_WIDE_HIGH_VOL`	Wide Range · High Vol	Large range, fast movement	BB Width>5%, ATR%>3%

Strategy Matching:

Tight Low Vol: Dense grid, wait for breakout
Tight High Vol: Fast grid, small frequent profits
Wide Low Vol: Sparse grid, patient holding
Wide High Vol: Swing trading, high profit targets

3.4 Transition (2 Types)

Code	Name	Technical Features	Quantitative Indicators
`TR_BOTTOM_FORMING`	Bottom Forming	Decline slowing, testing support	Price stabilizing + Volume drying up + RSI divergence
`TR_TOP_FORMING`	Top Forming	Rally slowing, testing resistance	Price stalling + Volume drying up + RSI divergence

3.5 Breakout (2 Types)

Code	Name	Technical Features	Quantitative Indicators
`BK_UPWARD`	Upward Breakout	Breaking resistance with volume	Price>Previous high, Volume>2x, BB breakout
`BK_DOWNWARD`	Downward Breakout	Breaking support with volume	Price<Previous low, Volume>2x, BB breakdown

4. Tertiary Classification (36 Ultra-fine Categories)

4.1 Trend Phase Classification

Uptrend lifecycle consists of 5 phases:

Phase Code	Name	Description	Quantitative Criteria
`TU_S1_INITIATION`	Uptrend Initiation	First break above MA or previous high	MACD bullish cross, Price>EMA20
`TU_S2_ACCELERATION`	Uptrend Acceleration	Momentum increasing, slope steepening	MACD histogram expanding, ADX rising
`TU_S3_MAIN_WAVE`	Main Wave	Sustained rise, shallow pullbacks	RSI 60-80, Pullbacks hold EMA20
`TU_S4_EXHAUSTION`	Uptrend Exhaustion	Slowing momentum, divergences appearing	RSI divergence, MACD divergence
`TU_S5_REVERSAL`	Trend Reversal	Breakdown, trend ending	Break below EMA50, MACD bearish cross

Downtrend phases follow same pattern: TD_S1 through TD_S5

4.2 Range Position Classification

Position Code	Name	Description	Strategy Suggestion
`RG_UPPER`	Upper Range	Price near resistance	Bias toward short
`RG_MIDDLE`	Mid Range	Price near middle band	Neutral grid trading
`RG_LOWER`	Lower Range	Price near support	Bias toward long
`RG_SQUEEZE`	Squeeze Pattern	Highs and lows converging	Wait for direction
`RG_EXPAND`	Expanding Pattern	Highs and lows diverging	Boundary reversal

4.3 Volatility Grades

Code	Name	ATR%	BB Width	Strategy Suggestion
`VOL_EXTREME_LOW`	Extreme Low Vol	<1%	<1.5%	Option selling
`VOL_LOW`	Low Volatility	1-2%	1.5-2.5%	Grid / Mean reversion
`VOL_NORMAL`	Normal Volatility	2-3%	2.5-4%	Trend following
`VOL_HIGH`	High Volatility	3-5%	4-6%	Momentum / Breakout
`VOL_EXTREME_HIGH`	Extreme High Vol	>5%	>6%	Reduce exposure / Hedge

5. Complete State Encoding Rules

5.1 Encoding Format

{Primary}_{Volatility}_{Phase}_{Position}

5.2 Encoding Examples

Full Code	Interpretation
`TU_LV_S3_M`	Uptrend_LowVol_MainWave_Middle
`TD_HV_S2_L`	Downtrend_HighVol_Acceleration_Lower
`RG_NV_SQ_U`	Range_NormalVol_Squeeze_Upper
`BK_HV_UP_M`	Breakout_HighVol_Upward_Middle

6. Core Identification Indicators

6.1 Trend Indicators

Indicator	Calculation	Criteria
ADX	14-period Average Directional Index	>40 Strong, 25-40 Medium, <25 Weak/Range
Trend Score	Composite EMA/MACD/Price structure	-100 to +100, Positive=Bullish, Negative=Bearish
EMA Alignment	Relative position of EMA20/50/200	Bullish/Bearish/Mixed alignment

6.2 Volatility Indicators

Indicator	Calculation	Purpose
ATR Percent	ATR(14) / Current Price × 100%	Measure relative volatility
BB Width	(Upper - Lower) / Middle × 100%	Measure price range
Volatility Rank	Current vol percentile in history	Determine vol level

6.3 Momentum Indicators

Indicator	Calculation	Criteria
RSI	14-period Relative Strength Index	>70 Overbought, <30 Oversold, 50 Neutral
MACD Histogram	MACD - Signal	Positive=Bullish momentum, Negative=Bearish
Momentum Score	Composite RSI/MACD/Volume	Measure current momentum

6.4 Structure Indicators

Indicator	Description	Purpose
Swing Structure	HH/HL/LH/LL sequence	Determine trend structure
Support/Resistance	Key price levels	Define trading range
Volume Profile	Volume-price relationship	Validate price action

7. Strategy Matching Matrix

7.1 Regime-Strategy Mapping

Regime Type	Recommended Strategy	Position Size	Stop Loss
Strong Uptrend · Low Vol	Trend following + Pyramid	60-80%	ATR×2
Strong Uptrend · High Vol	Momentum + Quick profit	40-60%	ATR×1.5
Uptrend Exhaustion	Reduce + Reversal short	20-30%	Previous high
Panic Decline	Wait or light bottom fish	10-20%	Wide stop
Low Vol Range	Grid trading	50-70%	Range boundary
High Vol Range	Swing trading	30-50%	ATR×2
Squeeze Pattern	Wait for breakout	10-20%	-
Upward Breakout	Chase + Add on pullback	50-70%	Breakout level
Bottom Formation	Scale in gradually	20-40%	New low

7.2 Grid Strategy Parameter Matching

Range Type	Grid Levels	Grid Spacing	Other Parameters
Tight Low Vol	30-50 levels	Small spacing	Enable Maker Only
Tight High Vol	15-25 levels	Small spacing	Fast execution mode
Wide Low Vol	10-20 levels	Large spacing	Patient execution
Wide High Vol	15-25 levels	Large spacing	High profit targets
Squeeze Pattern	Pause grid	-	Wait for breakout signal
Upper Range	Short bias	Medium	Increase sell weight
Lower Range	Long bias	Medium	Increase buy weight

8. Real-time Monitoring Guidelines

8.1 State Transition Triggers

Current State	Trigger Condition	Transitions To
Range	Price breakout + Volume + ADX rising	Breakout
Uptrend	RSI divergence + Volume decline	Exhaustion
Downtrend	RSI divergence + Volume decline	Exhaustion
Breakout	Failed breakout, price returns	Range
Exhaustion	Confirmed reversal breakout	Opposite trend

8.2 Risk Control Rules

Regime State	Max Position	Risk Per Trade	Special Rules
Strong Trend	80%	2%	Adding allowed
Weak Trend	50%	1.5%	No adding
Range	60%	1%	Diversified holding
Transition	30%	1%	Reduce activity
High Volatility	40%	0.5%	Wide stops

9. Appendix

9.1 Abbreviation Reference

Abbrev	Full Form	Description
TU	Trend Up	Upward trend
TD	Trend Down	Downward trend
RG	Range	Range-bound market
TR	Transition	Trend transition
BK	Breakout	Breakout pattern
LV	Low Volatility	Low volatility regime
HV	High Volatility	High volatility regime
NV	Normal Volatility	Normal volatility regime
XLV	Extreme Low Vol	Extremely low volatility
XHV	Extreme High Vol	Extremely high volatility

9.2 Document Information

Version: v1.0
Created: January 2026
Applicable: Cryptocurrency, Forex, Stocks, and other financial markets

This document is designed for market state identification and strategy matching in quantitative trading systems

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Market Regime Classification Framework

1. Classification Dimensions Overview

2. Primary Classification (5 Categories)

2.1 Classification Overview

2.2 Identification Indicators

3. Secondary Classification (18 Sub-categories)

3.1 Uptrend Sub-categories (5 Types)

3.2 Downtrend Sub-categories (5 Types)

3.3 Range Sub-categories (4 Types)

3.4 Transition (2 Types)

3.5 Breakout (2 Types)

4. Tertiary Classification (36 Ultra-fine Categories)

4.1 Trend Phase Classification

4.2 Range Position Classification

4.3 Volatility Grades

5. Complete State Encoding Rules

5.1 Encoding Format

5.2 Encoding Examples

6. Core Identification Indicators

6.1 Trend Indicators

6.2 Volatility Indicators

6.3 Momentum Indicators

6.4 Structure Indicators

7. Strategy Matching Matrix

7.1 Regime-Strategy Mapping

7.2 Grid Strategy Parameter Matching

8. Real-time Monitoring Guidelines

8.1 State Transition Triggers

8.2 Risk Control Rules

9. Appendix

9.1 Abbreviation Reference

9.2 Document Information

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