- Add version dropdown selector (v9, v8, v6, v5, all) to frontend - Update backend API to accept ?version= query parameter - Add version filter to all 5 broken SQL queries using Prisma parameterized queries - Update Data Collection Status to use selected version instead of hardcoded v8 - Add version context to all recommendations - Add URL encoding for version parameter (security best practice) - Validate version parameter against whitelist (SQL injection protection) Co-authored-by: mindesbunister <32161838+mindesbunister@users.noreply.github.com>
550 lines
24 KiB
TypeScript
550 lines
24 KiB
TypeScript
import { NextRequest, NextResponse } from 'next/server'
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import { getPrismaClient } from '../../../../lib/database/trades'
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import { Prisma } from '@prisma/client'
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export const dynamic = 'force-dynamic'
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// Valid indicator versions for filtering
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const VALID_VERSIONS = ['v5', 'v6', 'v8', 'v9', 'all']
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export async function GET(request: NextRequest) {
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const searchParams = request.nextUrl.searchParams
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const version = searchParams.get('version') || 'v9' // Default to current production
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// Validate version parameter to prevent SQL injection
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if (!VALID_VERSIONS.includes(version)) {
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return NextResponse.json({
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success: false,
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error: `Invalid version parameter. Must be one of: ${VALID_VERSIONS.join(', ')}`
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}, { status: 400 })
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}
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const prisma = getPrismaClient()
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const analyses = []
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// Version label for recommendations
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const versionLabel = version === 'all' ? 'All versions combined' : `${version.toUpperCase()} only`
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try {
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// ============================================================================
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// 1. QUALITY SCORE DISTRIBUTION
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// ============================================================================
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try {
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// Build query with optional version filter
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const qualityDistribution = version === 'all'
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? await prisma.$queryRaw<any[]>`
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SELECT
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CASE
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WHEN "signalQualityScore" >= 95 THEN '95-100 (Excellent)'
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WHEN "signalQualityScore" >= 90 THEN '90-94 (Very Good)'
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WHEN "signalQualityScore" >= 85 THEN '85-89 (Good)'
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WHEN "signalQualityScore" >= 80 THEN '80-84 (Fair)'
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WHEN "signalQualityScore" >= 70 THEN '70-79 (Marginal)'
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WHEN "signalQualityScore" >= 60 THEN '60-69 (Weak)'
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ELSE '<60 (Very Weak)'
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END as tier,
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COUNT(*) as trades,
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ROUND(AVG("signalQualityScore")::numeric, 1) as avg_score,
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SUM(CASE WHEN "realizedPnL" > 0 THEN 1 ELSE 0 END) as wins,
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SUM(CASE WHEN "realizedPnL" <= 0 THEN 1 ELSE 0 END) as losses,
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ROUND(100.0 * SUM(CASE WHEN "realizedPnL" > 0 THEN 1 ELSE 0 END) / COUNT(*)::numeric, 1) as win_rate,
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ROUND(SUM("realizedPnL")::numeric, 2) as total_pnl,
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ROUND(AVG("realizedPnL")::numeric, 2) as avg_pnl
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FROM "Trade"
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WHERE "exitReason" IS NOT NULL
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AND "signalQualityScore" IS NOT NULL
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GROUP BY tier
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ORDER BY MIN("signalQualityScore") DESC
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`
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: await prisma.$queryRaw<any[]>`
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SELECT
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CASE
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WHEN "signalQualityScore" >= 95 THEN '95-100 (Excellent)'
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WHEN "signalQualityScore" >= 90 THEN '90-94 (Very Good)'
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WHEN "signalQualityScore" >= 85 THEN '85-89 (Good)'
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WHEN "signalQualityScore" >= 80 THEN '80-84 (Fair)'
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WHEN "signalQualityScore" >= 70 THEN '70-79 (Marginal)'
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WHEN "signalQualityScore" >= 60 THEN '60-69 (Weak)'
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ELSE '<60 (Very Weak)'
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END as tier,
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COUNT(*) as trades,
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ROUND(AVG("signalQualityScore")::numeric, 1) as avg_score,
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SUM(CASE WHEN "realizedPnL" > 0 THEN 1 ELSE 0 END) as wins,
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SUM(CASE WHEN "realizedPnL" <= 0 THEN 1 ELSE 0 END) as losses,
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ROUND(100.0 * SUM(CASE WHEN "realizedPnL" > 0 THEN 1 ELSE 0 END) / COUNT(*)::numeric, 1) as win_rate,
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ROUND(SUM("realizedPnL")::numeric, 2) as total_pnl,
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ROUND(AVG("realizedPnL")::numeric, 2) as avg_pnl
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FROM "Trade"
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WHERE "exitReason" IS NOT NULL
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AND "signalQualityScore" IS NOT NULL
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AND "indicatorVersion" = ${version}
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GROUP BY tier
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ORDER BY MIN("signalQualityScore") DESC
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`
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const formattedData = qualityDistribution.map(row => ({
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tier: row.tier,
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trades: Number(row.trades),
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avg_score: Number(row.avg_score),
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win_rate: Number(row.win_rate),
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total_pnl: Number(row.total_pnl),
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avg_pnl: Number(row.avg_pnl)
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}))
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// Find best performing tier
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const bestTier = formattedData.reduce((best, current) =>
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current.win_rate > best.win_rate ? current : best
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)
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analyses.push({
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name: 'Quality Score Distribution',
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description: `Win rate and P&L across quality score tiers (${versionLabel})`,
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status: 'success',
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data: formattedData,
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recommendation: bestTier.win_rate >= 70
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? `${versionLabel}: Quality ${bestTier.tier.split(' ')[0]} shows ${bestTier.win_rate}% WR. Consider raising threshold to this tier.`
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: `${versionLabel}: Continue collecting data for reliable quality threshold optimization.`
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})
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} catch (error) {
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analyses.push({
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name: 'Quality Score Distribution',
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description: 'Win rate and P&L across quality score tiers',
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status: 'error',
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data: { error: (error as Error).message }
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})
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}
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// ============================================================================
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// 2. DIRECTION PERFORMANCE (Long vs Short)
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// ============================================================================
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try {
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const directionPerformance = version === 'all'
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? await prisma.$queryRaw<any[]>`
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SELECT
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direction,
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COUNT(*) as trades,
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SUM(CASE WHEN "realizedPnL" > 0 THEN 1 ELSE 0 END) as wins,
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ROUND(100.0 * SUM(CASE WHEN "realizedPnL" > 0 THEN 1 ELSE 0 END) / COUNT(*)::numeric, 1) as win_rate,
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ROUND(SUM("realizedPnL")::numeric, 2) as total_pnl,
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ROUND(AVG("realizedPnL")::numeric, 2) as avg_pnl,
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ROUND(AVG("signalQualityScore")::numeric, 1) as avg_quality
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FROM "Trade"
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WHERE "exitReason" IS NOT NULL
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AND direction IS NOT NULL
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GROUP BY direction
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ORDER BY win_rate DESC
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`
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: await prisma.$queryRaw<any[]>`
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SELECT
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direction,
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COUNT(*) as trades,
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SUM(CASE WHEN "realizedPnL" > 0 THEN 1 ELSE 0 END) as wins,
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ROUND(100.0 * SUM(CASE WHEN "realizedPnL" > 0 THEN 1 ELSE 0 END) / COUNT(*)::numeric, 1) as win_rate,
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ROUND(SUM("realizedPnL")::numeric, 2) as total_pnl,
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ROUND(AVG("realizedPnL")::numeric, 2) as avg_pnl,
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ROUND(AVG("signalQualityScore")::numeric, 1) as avg_quality
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FROM "Trade"
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WHERE "exitReason" IS NOT NULL
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AND direction IS NOT NULL
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AND "indicatorVersion" = ${version}
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GROUP BY direction
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ORDER BY win_rate DESC
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`
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const formattedData = directionPerformance.map(row => ({
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direction: String(row.direction).toUpperCase(),
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trades: Number(row.trades),
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wins: Number(row.wins),
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win_rate: Number(row.win_rate),
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total_pnl: Number(row.total_pnl),
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avg_pnl: Number(row.avg_pnl),
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avg_quality: Number(row.avg_quality)
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}))
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const longData = formattedData.find(d => d.direction === 'LONG')
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const shortData = formattedData.find(d => d.direction === 'SHORT')
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let recommendation = ''
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if (longData && shortData) {
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const wrDiff = Math.abs(longData.win_rate - shortData.win_rate)
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if (wrDiff > 15) {
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const better = longData.win_rate > shortData.win_rate ? 'LONG' : 'SHORT'
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const worse = better === 'LONG' ? 'SHORT' : 'LONG'
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recommendation = `${versionLabel}: ${better} signals perform ${wrDiff.toFixed(1)}% better. Consider raising ${worse} quality threshold or reducing ${worse} position size.`
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} else {
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recommendation = `${versionLabel}: Direction performance is balanced. No threshold adjustment needed.`
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}
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}
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analyses.push({
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name: 'Direction Performance',
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description: `Compare LONG vs SHORT trade outcomes (${versionLabel})`,
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status: 'success',
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data: formattedData,
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recommendation
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})
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} catch (error) {
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analyses.push({
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name: 'Direction Performance',
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description: 'Compare LONG vs SHORT trade outcomes',
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status: 'error',
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data: { error: (error as Error).message }
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})
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}
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// ============================================================================
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// 3. BLOCKED SIGNALS ANALYSIS
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// ============================================================================
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try {
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const blockedSignals = version === 'all'
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? await prisma.$queryRaw<any[]>`
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SELECT
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"blockReason",
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COUNT(*) as count,
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ROUND(AVG("signalQualityScore")::numeric, 1) as avg_score,
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ROUND(AVG(adx)::numeric, 1) as avg_adx,
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ROUND(AVG(atr)::numeric, 3) as avg_atr
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FROM "BlockedSignal"
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WHERE "blockReason" IS NOT NULL
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GROUP BY "blockReason"
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ORDER BY count DESC
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`
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: await prisma.$queryRaw<any[]>`
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SELECT
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"blockReason",
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COUNT(*) as count,
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ROUND(AVG("signalQualityScore")::numeric, 1) as avg_score,
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ROUND(AVG(adx)::numeric, 1) as avg_adx,
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ROUND(AVG(atr)::numeric, 3) as avg_atr
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FROM "BlockedSignal"
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WHERE "blockReason" IS NOT NULL
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AND "indicatorVersion" = ${version}
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GROUP BY "blockReason"
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ORDER BY count DESC
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`
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const formattedData = blockedSignals.map(row => ({
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reason: String(row.blockReason),
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count: Number(row.count),
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avg_score: Number(row.avg_score),
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avg_adx: Number(row.avg_adx),
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avg_atr: Number(row.avg_atr)
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}))
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const qualityBlocked = formattedData.find(d => d.reason === 'QUALITY_SCORE_TOO_LOW')
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let recommendation = ''
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if (qualityBlocked && qualityBlocked.count >= 20) {
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recommendation = `${versionLabel}: ${qualityBlocked.count} signals blocked by quality threshold. Ready for Phase 2 analysis - check if these would have been profitable.`
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} else {
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const needed = qualityBlocked ? 20 - qualityBlocked.count : 20
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recommendation = `${versionLabel}: Need ${needed} more blocked signals for reliable analysis. Keep collecting data.`
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}
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analyses.push({
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name: 'Blocked Signals Analysis',
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description: `Signals rejected by quality filters (${versionLabel})`,
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status: 'success',
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data: formattedData,
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recommendation,
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action: qualityBlocked && qualityBlocked.count >= 20
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? 'Run price tracking analysis to determine if blocked signals would have been profitable'
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: undefined
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})
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} catch (error) {
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analyses.push({
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name: 'Blocked Signals Analysis',
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description: 'Signals rejected by quality filters',
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status: 'error',
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data: { error: (error as Error).message }
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})
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}
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// ============================================================================
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// 4. RUNNER PERFORMANCE ANALYSIS
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// ============================================================================
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try {
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const runnerPerformance = version === 'all'
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? await prisma.$queryRaw<any[]>`
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SELECT
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COUNT(*) as total_trades,
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SUM(CASE WHEN "tp1Filled" = true THEN 1 ELSE 0 END) as tp1_hits,
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SUM(CASE WHEN "tp2Filled" = true THEN 1 ELSE 0 END) as tp2_hits,
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ROUND(100.0 * SUM(CASE WHEN "tp1Filled" = true THEN 1 ELSE 0 END) / NULLIF(COUNT(*), 0)::numeric, 1) as tp1_rate,
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ROUND(100.0 * SUM(CASE WHEN "tp2Filled" = true THEN 1 ELSE 0 END) / NULLIF(COUNT(*), 0)::numeric, 1) as tp2_rate,
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ROUND(AVG("maxFavorableExcursion")::numeric, 2) as avg_mfe,
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ROUND(AVG("maxAdverseExcursion")::numeric, 2) as avg_mae
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FROM "Trade"
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WHERE "exitReason" IS NOT NULL
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AND "createdAt" >= NOW() - INTERVAL '30 days'
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`
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: await prisma.$queryRaw<any[]>`
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SELECT
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COUNT(*) as total_trades,
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SUM(CASE WHEN "tp1Filled" = true THEN 1 ELSE 0 END) as tp1_hits,
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SUM(CASE WHEN "tp2Filled" = true THEN 1 ELSE 0 END) as tp2_hits,
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ROUND(100.0 * SUM(CASE WHEN "tp1Filled" = true THEN 1 ELSE 0 END) / NULLIF(COUNT(*), 0)::numeric, 1) as tp1_rate,
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ROUND(100.0 * SUM(CASE WHEN "tp2Filled" = true THEN 1 ELSE 0 END) / NULLIF(COUNT(*), 0)::numeric, 1) as tp2_rate,
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ROUND(AVG("maxFavorableExcursion")::numeric, 2) as avg_mfe,
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ROUND(AVG("maxAdverseExcursion")::numeric, 2) as avg_mae
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FROM "Trade"
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WHERE "exitReason" IS NOT NULL
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AND "createdAt" >= NOW() - INTERVAL '30 days'
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AND "indicatorVersion" = ${version}
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`
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const data = runnerPerformance[0]
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const formattedData = {
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total_trades: Number(data.total_trades) || 0,
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tp1_hits: Number(data.tp1_hits) || 0,
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tp2_hits: Number(data.tp2_hits) || 0,
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tp1_rate: Number(data.tp1_rate) || 0,
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tp2_rate: Number(data.tp2_rate) || 0,
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avg_mfe: Number(data.avg_mfe) || 0,
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avg_mae: Number(data.avg_mae) || 0
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}
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let recommendation = ''
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if (formattedData.total_trades === 0) {
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recommendation = `${versionLabel}: No trades found in last 30 days. Need data to analyze runner performance.`
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} else if (formattedData.avg_mfe > formattedData.tp1_rate * 1.5) {
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recommendation = `${versionLabel}: Avg MFE (${formattedData.avg_mfe.toFixed(2)}%) significantly exceeds TP1 rate. Consider widening TP1 or increasing runner size.`
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} else if (formattedData.tp2_rate > 50) {
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recommendation = `${versionLabel}: TP2 hit rate is ${formattedData.tp2_rate}%. Trailing stop working well - keep current settings.`
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} else {
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recommendation = `${versionLabel}: Runner performance is within expected range. Continue monitoring.`
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}
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analyses.push({
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name: 'Runner Performance',
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description: `TP1/TP2 hit rates and max excursion analysis (${versionLabel})`,
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status: 'success',
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data: formattedData,
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recommendation
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})
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} catch (error) {
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analyses.push({
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name: 'Runner Performance',
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description: 'TP1/TP2 hit rates and max excursion analysis',
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status: 'error',
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data: { error: (error as Error).message }
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})
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}
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// ============================================================================
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// 5. ATR CORRELATION WITH MFE
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// ============================================================================
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try {
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const atrCorrelation = version === 'all'
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? await prisma.$queryRaw<any[]>`
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SELECT
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CASE
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WHEN "atrAtEntry" < 0.3 THEN '<0.3 (Low Vol)'
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WHEN "atrAtEntry" < 0.5 THEN '0.3-0.5 (Med Vol)'
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WHEN "atrAtEntry" < 0.7 THEN '0.5-0.7 (High Vol)'
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ELSE '0.7+ (Very High Vol)'
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END as atr_range,
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COUNT(*) as trades,
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ROUND(AVG("maxFavorableExcursion")::numeric, 2) as avg_mfe,
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ROUND(AVG("realizedPnL")::numeric, 2) as avg_pnl,
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ROUND(100.0 * SUM(CASE WHEN "realizedPnL" > 0 THEN 1 ELSE 0 END) / COUNT(*)::numeric, 1) as win_rate
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FROM "Trade"
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WHERE "exitReason" IS NOT NULL
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AND "atrAtEntry" IS NOT NULL
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GROUP BY atr_range
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ORDER BY MIN("atrAtEntry")
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`
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: await prisma.$queryRaw<any[]>`
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SELECT
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CASE
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WHEN "atrAtEntry" < 0.3 THEN '<0.3 (Low Vol)'
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WHEN "atrAtEntry" < 0.5 THEN '0.3-0.5 (Med Vol)'
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WHEN "atrAtEntry" < 0.7 THEN '0.5-0.7 (High Vol)'
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ELSE '0.7+ (Very High Vol)'
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END as atr_range,
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COUNT(*) as trades,
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ROUND(AVG("maxFavorableExcursion")::numeric, 2) as avg_mfe,
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ROUND(AVG("realizedPnL")::numeric, 2) as avg_pnl,
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ROUND(100.0 * SUM(CASE WHEN "realizedPnL" > 0 THEN 1 ELSE 0 END) / COUNT(*)::numeric, 1) as win_rate
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FROM "Trade"
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WHERE "exitReason" IS NOT NULL
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AND "atrAtEntry" IS NOT NULL
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AND "indicatorVersion" = ${version}
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GROUP BY atr_range
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ORDER BY MIN("atrAtEntry")
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`
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const formattedData = atrCorrelation.map(row => ({
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atr_range: String(row.atr_range),
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trades: Number(row.trades),
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avg_mfe: Number(row.avg_mfe),
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avg_pnl: Number(row.avg_pnl),
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win_rate: Number(row.win_rate)
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}))
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let recommendation = `${versionLabel}: ATR-based targets already implemented. Monitor correlation over time.`
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if (formattedData.length >= 3) {
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const highestMFE = formattedData.reduce((best, current) =>
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current.avg_mfe > best.avg_mfe ? current : best
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)
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recommendation = `${versionLabel}: ${highestMFE.atr_range} shows highest avg MFE (${highestMFE.avg_mfe}%). ATR-based targets adapting correctly.`
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} else if (formattedData.length === 0) {
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recommendation = `${versionLabel}: No ATR data available. Need trades with ATR tracking enabled.`
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}
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analyses.push({
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name: 'ATR vs MFE Correlation',
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description: `How volatility affects profit potential (${versionLabel})`,
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status: 'success',
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data: formattedData,
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recommendation
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})
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} catch (error) {
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analyses.push({
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name: 'ATR vs MFE Correlation',
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description: 'How volatility affects profit potential',
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status: 'error',
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data: { error: (error as Error).message }
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})
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}
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// ============================================================================
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// 6. INDICATOR VERSION COMPARISON
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// ============================================================================
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try {
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const indicatorComparison = await prisma.$queryRaw<any[]>`
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SELECT
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"indicatorVersion",
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COUNT(*) as trades,
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SUM(CASE WHEN "realizedPnL" > 0 THEN 1 ELSE 0 END) as wins,
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ROUND(100.0 * SUM(CASE WHEN "realizedPnL" > 0 THEN 1 ELSE 0 END) / COUNT(*)::numeric, 1) as win_rate,
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ROUND(SUM("realizedPnL")::numeric, 2) as total_pnl,
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ROUND(AVG("realizedPnL")::numeric, 2) as avg_pnl,
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ROUND(AVG("signalQualityScore")::numeric, 1) as avg_quality
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FROM "Trade"
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WHERE "exitReason" IS NOT NULL
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AND "indicatorVersion" IS NOT NULL
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GROUP BY "indicatorVersion"
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ORDER BY "indicatorVersion" DESC
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`
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const formattedData = indicatorComparison.map(row => ({
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version: String(row.indicatorVersion),
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trades: Number(row.trades),
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wins: Number(row.wins),
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win_rate: Number(row.win_rate),
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total_pnl: Number(row.total_pnl),
|
|
avg_pnl: Number(row.avg_pnl),
|
|
avg_quality: Number(row.avg_quality)
|
|
}))
|
|
|
|
const v8Data = formattedData.find(d => d.version === 'v8')
|
|
let recommendation = ''
|
|
if (v8Data && v8Data.trades >= 20) {
|
|
recommendation = `v8 has ${v8Data.trades} trades with ${v8Data.win_rate}% WR. Sufficient data for statistical confidence.`
|
|
} else if (v8Data) {
|
|
recommendation = `v8 has ${v8Data.trades} trades. Need ${20 - v8Data.trades} more for statistical validation.`
|
|
} else {
|
|
recommendation = 'No v8 indicator data yet. Ensure TradingView alerts include IND:v8 field.'
|
|
}
|
|
|
|
analyses.push({
|
|
name: 'Indicator Version Comparison',
|
|
description: 'Performance across TradingView strategy versions',
|
|
status: 'success',
|
|
data: formattedData,
|
|
recommendation
|
|
})
|
|
} catch (error) {
|
|
analyses.push({
|
|
name: 'Indicator Version Comparison',
|
|
description: 'Performance across TradingView strategy versions',
|
|
status: 'error',
|
|
data: { error: (error as Error).message }
|
|
})
|
|
}
|
|
|
|
// ============================================================================
|
|
// 7. DATA COLLECTION STATUS
|
|
// ============================================================================
|
|
try {
|
|
// For 'all' version, show overall data collection status
|
|
// For specific version, show that version's data status
|
|
const dataStatus = version === 'all'
|
|
? await prisma.$queryRaw<any[]>`
|
|
SELECT
|
|
COUNT(*) FILTER (WHERE "exitReason" IS NOT NULL) as completed_trades,
|
|
COUNT(*) FILTER (WHERE "signalQualityScore" IS NOT NULL) as with_quality,
|
|
COUNT(*) FILTER (WHERE "atrAtEntry" IS NOT NULL) as with_atr,
|
|
COUNT(*) FILTER (WHERE "maxFavorableExcursion" IS NOT NULL) as with_mfe,
|
|
COUNT(*) FILTER (WHERE "indicatorVersion" = 'v9') as version_trades,
|
|
(SELECT COUNT(*) FROM "BlockedSignal" WHERE "blockReason" = 'QUALITY_SCORE_TOO_LOW') as blocked_quality
|
|
FROM "Trade"
|
|
`
|
|
: await prisma.$queryRaw<any[]>`
|
|
SELECT
|
|
COUNT(*) FILTER (WHERE "exitReason" IS NOT NULL AND "indicatorVersion" = ${version}) as completed_trades,
|
|
COUNT(*) FILTER (WHERE "signalQualityScore" IS NOT NULL AND "indicatorVersion" = ${version}) as with_quality,
|
|
COUNT(*) FILTER (WHERE "atrAtEntry" IS NOT NULL AND "indicatorVersion" = ${version}) as with_atr,
|
|
COUNT(*) FILTER (WHERE "maxFavorableExcursion" IS NOT NULL AND "indicatorVersion" = ${version}) as with_mfe,
|
|
COUNT(*) FILTER (WHERE "indicatorVersion" = ${version}) as version_trades,
|
|
(SELECT COUNT(*) FROM "BlockedSignal" WHERE "blockReason" = 'QUALITY_SCORE_TOO_LOW' AND "indicatorVersion" = ${version}) as blocked_quality
|
|
FROM "Trade"
|
|
`
|
|
|
|
const data = dataStatus[0]
|
|
const formattedData = {
|
|
completed_trades: Number(data.completed_trades) || 0,
|
|
with_quality: Number(data.with_quality) || 0,
|
|
with_atr: Number(data.with_atr) || 0,
|
|
with_mfe: Number(data.with_mfe) || 0,
|
|
version_trades: Number(data.version_trades) || 0,
|
|
blocked_quality: Number(data.blocked_quality) || 0
|
|
}
|
|
|
|
const blockedNeeded = Math.max(0, 20 - formattedData.blocked_quality)
|
|
const versionNeeded = Math.max(0, 50 - formattedData.version_trades)
|
|
const targetVersion = version === 'all' ? 'v9' : version
|
|
|
|
let action = ''
|
|
if (blockedNeeded > 0) {
|
|
action = `${versionLabel}: Need ${blockedNeeded} more blocked signals for Phase 2 quality threshold analysis.`
|
|
}
|
|
if (versionNeeded > 0) {
|
|
if (action) action += ' '
|
|
action += `Need ${versionNeeded} more ${targetVersion} indicator trades for statistical validation.`
|
|
}
|
|
|
|
analyses.push({
|
|
name: 'Data Collection Status',
|
|
description: `Progress toward analysis milestones (${versionLabel})`,
|
|
status: 'success',
|
|
data: formattedData,
|
|
recommendation: action || `${versionLabel}: Data collection milestones reached! Ready for optimization decisions.`,
|
|
action: action || undefined
|
|
})
|
|
} catch (error) {
|
|
analyses.push({
|
|
name: 'Data Collection Status',
|
|
description: 'Progress toward analysis milestones',
|
|
status: 'error',
|
|
data: { error: (error as Error).message }
|
|
})
|
|
}
|
|
|
|
return NextResponse.json({
|
|
success: true,
|
|
analyses,
|
|
selectedVersion: version,
|
|
timestamp: new Date().toISOString()
|
|
})
|
|
|
|
} catch (error) {
|
|
console.error('❌ Optimization analysis failed:', error)
|
|
return NextResponse.json({
|
|
success: false,
|
|
error: 'Failed to run optimization analyses',
|
|
message: (error as Error).message
|
|
}, { status: 500 })
|
|
}
|
|
}
|