Add signal quality version comparison to analytics dashboard

- Created /api/analytics/version-comparison endpoint
- Shows performance metrics for v1, v2, v3 scoring logic
- Compares: trade count, win rate, P&L, quality scores, MFE/MAE
- Special focus on extreme positions (< 15% or > 85% range)
- Tracks weak ADX count (< 18) for each version
- Visual indicators for current version (v3)
- Data collection progress notice for v3 (need 20+ trades)
- Legend explaining MFE, MAE, extreme positions, weak ADX

Enables data-driven optimization by comparing algorithm performance
with clean, version-tagged datasets.
This commit is contained in:
mindesbunister
2025-11-07 13:05:48 +01:00
parent 625dc44c59
commit 711ff9aaf4
3 changed files with 465 additions and 1 deletions

View File

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/**
* Trading Bot v4 - Signal Quality Version Comparison API
*
* Returns performance metrics comparing different signal quality scoring versions
*/
import { NextResponse } from 'next/server'
import { getPrismaClient } from '@/lib/database/trades'
export const dynamic = 'force-dynamic'
interface VersionStats {
version: string
tradeCount: number
winRate: number
totalPnL: number
avgPnL: number
avgQualityScore: number | null
avgMFE: number | null
avgMAE: number | null
extremePositions: {
count: number
avgADX: number | null
weakADXCount: number
winRate: number
avgPnL: number
}
}
export async function GET() {
try {
const prisma = getPrismaClient()
// Get overall stats by version
const versionStats = await prisma.$queryRaw<Array<{
version: string | null
trades: bigint
wins: bigint
total_pnl: number
avg_pnl: number
avg_quality_score: number | null
avg_mfe: number | null
avg_mae: number | null
}>>`
SELECT
COALESCE("signalQualityVersion", 'v1') as version,
COUNT(*) as trades,
SUM(CASE WHEN "realizedPnL" > 0 THEN 1 ELSE 0 END) as wins,
ROUND(SUM("realizedPnL")::numeric, 2) as total_pnl,
ROUND(AVG("realizedPnL")::numeric, 2) as avg_pnl,
ROUND(AVG("signalQualityScore")::numeric, 1) as avg_quality_score,
ROUND(AVG("maxFavorableExcursion")::numeric, 2) as avg_mfe,
ROUND(AVG("maxAdverseExcursion")::numeric, 2) as avg_mae
FROM "Trade"
WHERE "exitReason" IS NOT NULL
AND "exitReason" NOT LIKE '%CLEANUP%'
AND "isTestTrade" = false
GROUP BY "signalQualityVersion"
ORDER BY version DESC
`
// Get extreme position stats by version (< 15% or > 85%)
const extremePositionStats = await prisma.$queryRaw<Array<{
version: string | null
count: bigint
avg_adx: number | null
weak_adx_count: bigint
wins: bigint
avg_pnl: number
}>>`
SELECT
COALESCE("signalQualityVersion", 'v1') as version,
COUNT(*) as count,
ROUND(AVG("adxAtEntry")::numeric, 1) as avg_adx,
COUNT(*) FILTER (WHERE "adxAtEntry" < 18) as weak_adx_count,
SUM(CASE WHEN "realizedPnL" > 0 THEN 1 ELSE 0 END) as wins,
ROUND(AVG("realizedPnL")::numeric, 2) as avg_pnl
FROM "Trade"
WHERE "exitReason" IS NOT NULL
AND "exitReason" NOT LIKE '%CLEANUP%'
AND "isTestTrade" = false
AND "pricePositionAtEntry" IS NOT NULL
AND ("pricePositionAtEntry" < 15 OR "pricePositionAtEntry" > 85)
GROUP BY "signalQualityVersion"
ORDER BY version DESC
`
// Build combined results
const results: VersionStats[] = versionStats.map(stat => {
const extremeStats = extremePositionStats.find(e =>
(e.version || 'v1') === (stat.version || 'v1')
)
const trades = Number(stat.trades)
const wins = Number(stat.wins)
const extremeCount = extremeStats ? Number(extremeStats.count) : 0
const extremeWins = extremeStats ? Number(extremeStats.wins) : 0
return {
version: stat.version || 'v1',
tradeCount: trades,
winRate: trades > 0 ? Math.round((wins / trades) * 100 * 10) / 10 : 0,
totalPnL: stat.total_pnl,
avgPnL: stat.avg_pnl,
avgQualityScore: stat.avg_quality_score,
avgMFE: stat.avg_mfe,
avgMAE: stat.avg_mae,
extremePositions: {
count: extremeCount,
avgADX: extremeStats?.avg_adx || null,
weakADXCount: extremeStats ? Number(extremeStats.weak_adx_count) : 0,
winRate: extremeCount > 0 ? Math.round((extremeWins / extremeCount) * 100 * 10) / 10 : 0,
avgPnL: extremeStats?.avg_pnl || 0,
}
}
})
// Get version descriptions
const versionDescriptions: Record<string, string> = {
'v1': 'Original logic (price < 5% threshold)',
'v2': 'Added volume compensation for low ADX',
'v3': 'Stricter: ADX > 18 required for positions < 15%'
}
return NextResponse.json({
success: true,
versions: results,
descriptions: versionDescriptions,
timestamp: new Date().toISOString()
})
} catch (error) {
console.error('❌ Failed to fetch version comparison:', error)
return NextResponse.json(
{ success: false, error: 'Failed to fetch version comparison data' },
{ status: 500 }
)
}
}