Lowriskquotes Montecarlo

Name: Lowriskquotes Montecarlo
Author: physics-star-cat

@physics-star-catMCP server · External

Monte Carlo tools: three-point cost estimation and an educational retirement drawdown simulator.

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README6 min readView on GitHub

EstiMate

A mobile-first contractor cost estimation app that uses Monte Carlo simulation to provide probabilistic risk analysis for job quotes. Built natively for iOS (SwiftUI) and Android (Jetpack Compose).

Overview

EstiMate helps tradespeople and contractors move beyond single-point estimates to understand the range of likely costs and risks. Instead of guessing a single number, you input your estimates with uncertainty levels, and the app runs thousands of simulations to show you the probability distribution of total costs.

Key Value Propositions:

Offline-first, no login required
Sophisticated risk analysis on mobile (usually reserved for enterprise desktop software)
Helps contractors avoid under-quoting with statistically safe quote recommendations
Generates professional PDF quotes for clients

Features

Core Estimation

Project Management - Create, save, and manage multiple project estimates
Line Items - Add materials, labor, subcontractors, and other costs
Risk Levels - 5-tier uncertainty system:
- Certain (±2%) - Fixed/contracted prices
- Low (±8%) - Known suppliers with stable pricing
- Medium (±15%) - Standard market variability
- High (±25%) - Volatile or uncertain costs
- Wild Guess (±40%) - Unknown scope items

Duration & Travel Estimation

Job Duration - Estimated days with complexity levels (Routine ±10% to Unknown Scope ±60%)
Labor Configuration - Hourly rates, hours per day, extra workers
Travel Costs - One-way travel time, traffic variability, site visits, mileage tracking
Correlation Modeling - Duration uncertainty automatically affects travel costs

Monte Carlo Simulation

1,000+ iterations with convergence detection
Skewed distribution toward overages (realistic for construction projects)
Percentile outputs: P10, P50, P80, P90, P95
Cost breakdown by category (Materials, Duration, Travel)
Standard deviation and confidence level calculations

Results & Export

Bell Curve Visualization - Color-coded histogram of cost distribution
Quote Recommendations - Conservative (P50), Recommended (P80), Safe (P90)
PDF Export - Professional client-facing quotes with cost breakdowns
Share - Export via platform share sheets

Internationalization

Region	Currency	Distance	Terminology
US	USD ($)	Miles	Contractor, Labor
UK	GBP (£)	Miles	Tradesperson, Labour
Canada	CAD ($)	Kilometers	Contractor, Labour
Australia	AUD ($)	Kilometers	Tradie, Labour
New Zealand	NZD ($)	Kilometers	Tradie, Labour

Tech Stack

iOS

Language: Swift
UI Framework: SwiftUI
Architecture: MVVM
Min iOS: 14.0+
Storage: UserDefaults (local only)
PDF: PDFKit/UIGraphicsPDFRenderer
Charts: Apple Charts framework (iOS 16.4+)

Android

Language: Kotlin
UI Framework: Jetpack Compose
Architecture: MVVM with ViewModel + StateFlow
Min SDK: 26 (Android 8.0)
Target SDK: 34 (Android 14)
Storage: SharedPreferences + GSON
PDF: iText 7
Navigation: Jetpack Navigation Compose

Project Structure

contractors_app/
├── ios/RiskEstimator/           # iOS application
│   └── RiskEstimator/
│       ├── RiskEstimatorApp.swift      # App entry point
│       ├── ContentView.swift           # Root navigation
│       ├── ViewModels/
│       │   └── EstimatorViewModel.swift
│       ├── Models/
│       │   ├── Project.swift
│       │   ├── LineItem.swift
│       │   ├── Worker.swift
│       │   └── SimulationResult.swift
│       ├── Services/
│       │   ├── MonteCarloEngine.swift
│       │   ├── StorageService.swift
│       │   └── PDFService.swift
│       ├── Views/
│       │   ├── Screens/
│       │   │   ├── HomeScreen.swift
│       │   │   ├── EstimatorScreen.swift
│       │   │   └── ResultsScreen.swift
│       │   └── Components/
│       │       ├── RiskSlider.swift
│       │       ├── ComplexitySlider.swift
│       │       ├── TrafficSlider.swift
│       │       ├── BellCurveChart.swift
│       │       └── ...
│       └── Utils/
│           ├── Localization.swift
│           └── CurrencyFormatter.swift
│
├── android/RiskEstimator/       # Android application
│   └── app/src/main/java/com/riskestimator/app/
│       ├── MainActivity.kt
│       ├── ui/
│       │   ├── RiskEstimatorApp.kt
│       │   ├── EstimatorViewModel.kt
│       │   ├── screens/
│       │   │   ├── HomeScreen.kt
│       │   │   ├── EstimatorScreen.kt
│       │   │   └── ResultsScreen.kt
│       │   ├── components/
│       │   │   ├── RiskSlider.kt
│       │   │   ├── BellCurveChart.kt
│       │   │   └── ...
│       │   └── theme/
│       ├── data/
│       │   ├── model/
│       │   └── repository/
│       └── domain/
│           ├── MonteCarloEngine.kt
│           └── PDFService.kt
│
├── icons/                       # App icon assets
├── PROGRESS.md                  # Project roadmap & status
└── contractor_app_market_research.md

Architecture

Both platforms follow the MVVM (Model-View-ViewModel) pattern:

┌─────────────────────────────────────────────────────────┐
│                         Views                            │
│  (SwiftUI Views / Jetpack Compose Screens)              │
└─────────────────────────────────────────────────────────┘
                          │
                          ▼
┌─────────────────────────────────────────────────────────┐
│                     ViewModel                            │
│  - Manages UI state                                      │
│  - Coordinates between Views and Services               │
│  - Triggers simulations                                  │
└─────────────────────────────────────────────────────────┘
                          │
          ┌───────────────┼───────────────┐
          ▼               ▼               ▼
┌─────────────────┐ ┌───────────┐ ┌─────────────────┐
│ MonteCarloEngine│ │StorageRepo│ │   PDFService    │
│                 │ │           │ │                 │
│ - Simulation    │ │ - CRUD    │ │ - Generate PDF  │
│ - Statistics    │ │ - Persist │ │ - Export        │
└─────────────────┘ └───────────┘ └─────────────────┘
                          │
                          ▼
┌─────────────────────────────────────────────────────────┐
│                        Models                            │
│  Project, LineItem, Worker, SimulationResult            │
└─────────────────────────────────────────────────────────┘

Data Models

Project

swift

struct Project {
    id: UUID
    name: String
    clientName: String
    createdAt: Date
    profitMargin: Double        // Default 15%
    lineItems: [LineItem]
    workers: [Worker]           // iOS only
    estimatedDays: Double
    complexityLevel: ComplexityLevel
    hourlyLaborRate: Double
    hoursPerDay: Double
    travelTimeMinutes: Double
    trafficVariability: TrafficVariability
    numberOfSiteVisits: Int     // 0 = auto-calculate
    includeReturnTrip: Bool
    mileageRate: Double
    distance: Double
}

LineItem

swift

struct LineItem {
    id: UUID
    name: String
    estimatedCost: Double
    category: ItemCategory      // Material, Labor, Subcontractor, Other
    riskLevel: RiskLevel        // Certain, Low, Medium, High, WildGuess
}

SimulationResult

swift

struct SimulationResult {
    simulations: [Double]       // All iteration results
    percentile10/50/80/90/95: Double
    mean: Double
    standardDeviation: Double
    min, max: Double
    // Category breakdowns
    materialCostP50/P80: Double
    durationCostP50/P80: Double
    travelCostP50/P80: Double
    iterationsRun: Int
    isConverged: Bool
}

Risk/Variance Multipliers

Level	Variance	Use Case
Certain	±2%	Fixed contracts, locked prices
Low	±8%	Reliable suppliers, stable costs
Medium	±15%	Standard market variability
High	±25%	Volatile materials, uncertain labor
Wild Guess	±40%	Unknown scope, new vendors

Complexity	Variance	Use Case
Routine	±10%	Repeat jobs, familiar scope
Moderate	±25%	Standard projects
Complex	±40%	Multi-trade, custom work
Unknown Scope	±60%	Discovery needed, unknowns

Traffic	Variance	Use Case
Predictable	±10%	Rural, fixed schedule
Variable	±25%	Suburban, normal traffic
High Variability	±50%	Urban, rush hour

Getting Started

iOS

Open ios/RiskEstimator/RiskEstimator.xcodeproj in Xcode
Select your target device or simulator
Build and run (⌘R)

Requirements:

Xcode 14.0+
iOS 14.0+ deployment target
Swift 5.0+

Android

Open android/RiskEstimator in Android Studio
Sync Gradle files
Select your target device or emulator
Build and run

Requirements:

Android Studio Hedgehog or later
JDK 17
Android SDK 26+ (min) / 34 (target)

Monte Carlo Simulation

The simulation engine uses the Box-Muller transform to generate normally distributed random values with optional skew toward overages (reflecting real-world project behavior).

Algorithm

For each iteration (1,000 - 10,000):
    1. For each line item:
       - Generate random variance based on risk level
       - Apply skewed normal distribution (bias toward overages)
       - Calculate simulated cost

    2. For duration:
       - Generate random variance based on complexity
       - Calculate labor cost = days × hours × rate

    3. For travel:
       - Correlate visits with duration uncertainty
       - Generate traffic variance
       - Calculate travel time + mileage costs

    4. Sum all costs + profit margin

Calculate statistics from all iterations
Check for convergence (P80 standard error < 0.5%)