mev-beta/orig/examples/profitability_calculator.go

package main

import (
	"fmt"
	"math"
)

// ProfitabilityCalculator performs detailed MEV bot profitability analysis
type ProfitabilityCalculator struct {
	// Market parameters
	dailyArbitrageVolume   float64 // USD
	averageOpportunitySize float64 // USD
	marketSharePercentage  float64 // 0-100
	successRate            float64 // 0-1
	averageProfitMargin    float64 // 0-1

	// Cost parameters
	gasPerTransaction         float64 // USD
	infrastructureCostMonthly float64 // USD
	developmentCostMonthly    float64 // USD
	capitalRequirement        float64 // USD

	// Competition parameters
	competitionLevel float64 // 0-1 (0 = no competition, 1 = intense)
	gasPremiumFactor float64 // Gas multiplier due to competition

	// Risk parameters
	maxDailyLoss   float64 // USD
	slippageImpact float64 // 0-1
	failureRate    float64 // 0-1
}

// ProfitabilityResults contains the results of profitability analysis
type ProfitabilityResults struct {
	// Revenue metrics
	DailyOpportunities int
	DailyGrossRevenue  float64
	DailyNetRevenue    float64
	MonthlyNetProfit   float64
	AnnualNetProfit    float64

	// Cost metrics
	DailyGasCosts         float64
	MonthlyOperatingCosts float64
	AnnualOperatingCosts  float64

	// Performance metrics
	ROIPercentage  float64
	BreakEvenDays  int
	ProfitPerTrade float64

	// Risk metrics
	MaxDrawdownDaily   float64
	WorstCaseScenario  float64
	ProfitabilityScore float64 // 0-100
}

// NewProfitabilityCalculator creates a calculator with Arbitrum L2 defaults
func NewProfitabilityCalculator() *ProfitabilityCalculator {
	return &ProfitabilityCalculator{
		// Realistic Arbitrum market estimates
		dailyArbitrageVolume:   2000000, // $2M daily arbitrage volume
		averageOpportunitySize: 100,     // $100 average opportunity
		marketSharePercentage:  1.0,     // 1% market capture (realistic)
		successRate:            0.75,    // 75% success rate
		averageProfitMargin:    0.015,   // 1.5% average profit margin

		// Arbitrum L2 cost structure (much lower than Ethereum)
		gasPerTransaction:         0.25, // $0.25 average gas per transaction
		infrastructureCostMonthly: 800,  // $800/month infrastructure
		developmentCostMonthly:    3000, // $3000/month development equivalent
		capitalRequirement:        5000, // $5000 working capital

		// Competition assumptions
		competitionLevel: 0.6, // Moderate competition
		gasPremiumFactor: 1.2, // 20% gas premium for priority

		// Risk parameters
		maxDailyLoss:   500,   // $500 max daily loss
		slippageImpact: 0.002, // 0.2% slippage impact
		failureRate:    0.15,  // 15% transaction failure rate
	}
}

// CalculateProfitability performs comprehensive profitability analysis
func (pc *ProfitabilityCalculator) CalculateProfitability() *ProfitabilityResults {
	// Calculate daily opportunities
	marketValue := pc.dailyArbitrageVolume * (pc.marketSharePercentage / 100)
	dailyOpportunities := int(marketValue / pc.averageOpportunitySize)

	// Calculate successful trades
	successfulTrades := float64(dailyOpportunities) * pc.successRate

	// Calculate gross revenue
	grossProfitPerTrade := pc.averageOpportunitySize * pc.averageProfitMargin
	dailyGrossRevenue := successfulTrades * grossProfitPerTrade

	// Apply competition impact
	competitionReduction := pc.competitionLevel * 0.3 // 30% max reduction
	dailyGrossRevenue *= (1 - competitionReduction)

	// Apply slippage impact
	dailyGrossRevenue *= (1 - pc.slippageImpact)

	// Calculate costs
	dailyGasCosts := successfulTrades * pc.gasPerTransaction * pc.gasPremiumFactor

	// Add failed transaction costs
	failedTrades := float64(dailyOpportunities) * pc.failureRate
	dailyGasCosts += failedTrades * pc.gasPerTransaction * 0.5 // Partial gas on failure

	// Calculate net revenue
	dailyNetRevenue := dailyGrossRevenue - dailyGasCosts

	// Monthly calculations
	monthlyGrossRevenue := dailyGrossRevenue * 30
	monthlyGasCosts := dailyGasCosts * 30
	monthlyOperatingCosts := monthlyGasCosts + pc.infrastructureCostMonthly + pc.developmentCostMonthly
	monthlyNetProfit := monthlyGrossRevenue - monthlyOperatingCosts

	// Annual calculations
	annualNetProfit := monthlyNetProfit * 12
	annualOperatingCosts := monthlyOperatingCosts * 12

	// ROI calculation
	roiPercentage := (annualNetProfit / pc.capitalRequirement) * 100

	// Break-even calculation
	breakEvenDays := int(pc.capitalRequirement / math.Max(dailyNetRevenue, 1))

	// Profit per trade
	profitPerTrade := dailyNetRevenue / successfulTrades

	// Risk calculations
	maxDrawdownDaily := math.Min(pc.maxDailyLoss, dailyNetRevenue*0.5)
	worstCaseScenario := monthlyNetProfit * 0.3 // 70% reduction scenario

	// Profitability score (0-100)
	profitabilityScore := pc.calculateProfitabilityScore(roiPercentage, float64(breakEvenDays), profitPerTrade)

	return &ProfitabilityResults{
		DailyOpportunities:    dailyOpportunities,
		DailyGrossRevenue:     dailyGrossRevenue,
		DailyNetRevenue:       dailyNetRevenue,
		MonthlyNetProfit:      monthlyNetProfit,
		AnnualNetProfit:       annualNetProfit,
		DailyGasCosts:         dailyGasCosts,
		MonthlyOperatingCosts: monthlyOperatingCosts,
		AnnualOperatingCosts:  annualOperatingCosts,
		ROIPercentage:         roiPercentage,
		BreakEvenDays:         breakEvenDays,
		ProfitPerTrade:        profitPerTrade,
		MaxDrawdownDaily:      maxDrawdownDaily,
		WorstCaseScenario:     worstCaseScenario,
		ProfitabilityScore:    profitabilityScore,
	}
}

// calculateProfitabilityScore creates a composite score for profitability
func (pc *ProfitabilityCalculator) calculateProfitabilityScore(roi, breakEven float64, profitPerTrade float64) float64 {
	// ROI component (0-40 points)
	roiScore := math.Min(roi/10, 40) // 10% ROI = 1 point, capped at 40

	// Break-even component (0-30 points)
	breakEvenScore := math.Max(30-(breakEven/2), 0) // Faster break-even = higher score

	// Profit per trade component (0-30 points)
	profitScore := math.Min(profitPerTrade*3, 30) // $10 per trade = 30 points

	return roiScore + breakEvenScore + profitScore
}

// RunScenarioAnalysis runs multiple scenarios for sensitivity analysis
func (pc *ProfitabilityCalculator) RunScenarioAnalysis() map[string]*ProfitabilityResults {
	scenarios := make(map[string]*ProfitabilityResults)

	// Store original values
	originalSuccess := pc.successRate
	originalCompetition := pc.competitionLevel
	originalMarketShare := pc.marketSharePercentage

	// Conservative scenario
	pc.successRate = 0.65
	pc.competitionLevel = 0.8
	pc.marketSharePercentage = 1.5
	scenarios["Conservative"] = pc.CalculateProfitability()

	// Moderate scenario
	pc.successRate = 0.75
	pc.competitionLevel = 0.6
	pc.marketSharePercentage = 2.5
	scenarios["Moderate"] = pc.CalculateProfitability()

	// Optimistic scenario
	pc.successRate = 0.85
	pc.competitionLevel = 0.4
	pc.marketSharePercentage = 4.0
	scenarios["Optimistic"] = pc.CalculateProfitability()

	// Restore original values
	pc.successRate = originalSuccess
	pc.competitionLevel = originalCompetition
	pc.marketSharePercentage = originalMarketShare

	return scenarios
}

// PrintDetailedReport prints a comprehensive profitability report
func PrintDetailedReport(results *ProfitabilityResults, scenario string) {
	fmt.Printf("\n=== %s SCENARIO PROFITABILITY REPORT ===\n", scenario)
	fmt.Printf("📊 REVENUE METRICS:\n")
	fmt.Printf("  Daily Opportunities: %d\n", results.DailyOpportunities)
	fmt.Printf("  Daily Gross Revenue: $%.2f\n", results.DailyGrossRevenue)
	fmt.Printf("  Daily Net Revenue: $%.2f\n", results.DailyNetRevenue)
	fmt.Printf("  Monthly Net Profit: $%.2f\n", results.MonthlyNetProfit)
	fmt.Printf("  Annual Net Profit: $%.2f\n", results.AnnualNetProfit)

	fmt.Printf("\n💸 COST METRICS:\n")
	fmt.Printf("  Daily Gas Costs: $%.2f\n", results.DailyGasCosts)
	fmt.Printf("  Monthly Operating Costs: $%.2f\n", results.MonthlyOperatingCosts)
	fmt.Printf("  Annual Operating Costs: $%.2f\n", results.AnnualOperatingCosts)

	fmt.Printf("\n📈 PERFORMANCE METRICS:\n")
	fmt.Printf("  ROI Percentage: %.1f%%\n", results.ROIPercentage)
	fmt.Printf("  Break-even Days: %d\n", results.BreakEvenDays)
	fmt.Printf("  Profit per Trade: $%.2f\n", results.ProfitPerTrade)

	fmt.Printf("\n⚠️ RISK METRICS:\n")
	fmt.Printf("  Max Daily Drawdown: $%.2f\n", results.MaxDrawdownDaily)
	fmt.Printf("  Worst Case Monthly: $%.2f\n", results.WorstCaseScenario)
	fmt.Printf("  Profitability Score: %.1f/100\n", results.ProfitabilityScore)
}

// GetProfitabilityGrade returns a letter grade based on profitability score
func GetProfitabilityGrade(score float64) string {
	switch {
	case score >= 90:
		return "A+ (Exceptional)"
	case score >= 80:
		return "A (Excellent)"
	case score >= 70:
		return "B+ (Very Good)"
	case score >= 60:
		return "B (Good)"
	case score >= 50:
		return "C+ (Fair)"
	case score >= 40:
		return "C (Marginal)"
	default:
		return "D (Poor)"
	}
}

func main() {
	fmt.Println("🏦 MEV Bot Profitability Calculator")
	fmt.Println("=====================================")

	calculator := NewProfitabilityCalculator()

	// Run base scenario
	fmt.Println("\n🎯 BASE SCENARIO ANALYSIS:")
	baseResults := calculator.CalculateProfitability()
	PrintDetailedReport(baseResults, "BASE")

	// Run scenario analysis
	fmt.Println("\n🔄 SCENARIO SENSITIVITY ANALYSIS:")
	scenarios := calculator.RunScenarioAnalysis()

	for scenario, results := range scenarios {
		PrintDetailedReport(results, scenario)
		fmt.Printf("  Profitability Grade: %s\n", GetProfitabilityGrade(results.ProfitabilityScore))
	}

	// Summary comparison
	fmt.Println("\n📋 SCENARIO COMPARISON SUMMARY:")
	fmt.Println("Scenario      | Annual Profit | ROI    | Break-even | Grade")
	fmt.Println("------------- | ------------- | ------ | ---------- | -----")

	for scenario, results := range scenarios {
		fmt.Printf("%-13s | $%11.0f | %5.1f%% | %8d d | %s\n",
			scenario,
			results.AnnualNetProfit,
			results.ROIPercentage,
			results.BreakEvenDays,
			GetProfitabilityGrade(results.ProfitabilityScore))
	}

	// Investment recommendation
	fmt.Println("\n💡 INVESTMENT RECOMMENDATION:")
	avgROI := (scenarios["Conservative"].ROIPercentage +
		scenarios["Moderate"].ROIPercentage +
		scenarios["Optimistic"].ROIPercentage) / 3

	if avgROI > 200 {
		fmt.Println("🟢 HIGHLY RECOMMENDED - Exceptional returns with manageable risk")
	} else if avgROI > 100 {
		fmt.Println("🟡 RECOMMENDED - Good returns, monitor competition carefully")
	} else if avgROI > 50 {
		fmt.Println("🟠 PROCEED WITH CAUTION - Moderate returns, higher risk")
	} else {
		fmt.Println("🔴 NOT RECOMMENDED - Returns too low for risk level")
	}

	fmt.Printf("\nAverage ROI across scenarios: %.1f%%\n", avgROI)
	fmt.Printf("Risk-adjusted recommendation: Deploy with conservative parameters\n")
}