RealVest Real Estate MCP Server

/** * Market Analysis Tool * Analyzes market conditions, comps, and investment opportunities */ export class MarketAnalysisTool { getSchema() { return { type: 'object', properties: { subject_property: { type: 'object', properties: { address: { type: 'string', description: 'Property address' }, property_type: { type: 'string', enum: ['single_family', 'condo', 'townhouse', 'multi_family', 'commercial'], description: 'Type of property' }, bedrooms: { type: 'number', minimum: 0, maximum: 20, description: 'Number of bedrooms' }, bathrooms: { type: 'number', minimum: 0, maximum: 20, description: 'Number of bathrooms' }, square_feet: { type: 'number', minimum: 0, description: 'Total square footage' }, lot_size: { type: 'number', minimum: 0, description: 'Lot size in square feet' }, year_built: { type: 'number', minimum: 1800, maximum: 2030, description: 'Year built' }, asking_price: { type: 'number', minimum: 0, description: 'Current asking price' }, estimated_rent: { type: 'number', minimum: 0, description: 'Estimated monthly rent' } }, required: ['property_type', 'bedrooms', 'bathrooms', 'square_feet'] }, comparable_properties: { type: 'array', items: { type: 'object', properties: { address: { type: 'string', description: 'Comparable property address' }, sale_price: { type: 'number', minimum: 0, description: 'Recent sale price' }, sale_date: { type: 'string', description: 'Date of sale (YYYY-MM-DD)' }, bedrooms: { type: 'number', minimum: 0, description: 'Number of bedrooms' }, bathrooms: { type: 'number', minimum: 0, description: 'Number of bathrooms' }, square_feet: { type: 'number', minimum: 0, description: 'Square footage' }, lot_size: { type: 'number', minimum: 0, description: 'Lot size in square feet' }, year_built: { type: 'number', minimum: 1800, maximum: 2030, description: 'Year built' }, distance_miles: { type: 'number', minimum: 0, description: 'Distance from subject property' }, condition: { type: 'string', enum: ['poor', 'fair', 'good', 'excellent'], description: 'Property condition' }, monthly_rent: { type: 'number', minimum: 0, description: 'Monthly rent if rental' } }, required: ['sale_price', 'sale_date', 'bedrooms', 'bathrooms', 'square_feet'] }, minItems: 1, maxItems: 20 }, rental_comparables: { type: 'array', items: { type: 'object', properties: { address: { type: 'string', description: 'Rental property address' }, monthly_rent: { type: 'number', minimum: 0, description: 'Monthly rent amount' }, lease_date: { type: 'string', description: 'Date of lease (YYYY-MM-DD)' }, bedrooms: { type: 'number', minimum: 0, description: 'Number of bedrooms' }, bathrooms: { type: 'number', minimum: 0, description: 'Number of bathrooms' }, square_feet: { type: 'number', minimum: 0, description: 'Square footage' }, lot_size: { type: 'number', minimum: 0, description: 'Lot size in square feet' }, year_built: { type: 'number', minimum: 1800, maximum: 2030, description: 'Year built' }, distance_miles: { type: 'number', minimum: 0, description: 'Distance from subject property' }, condition: { type: 'string', enum: ['poor', 'fair', 'good', 'excellent'], description: 'Property condition' }, units: { type: 'number', minimum: 1, description: 'Number of units (for multifamily)' } }, required: ['monthly_rent', 'lease_date', 'bedrooms', 'bathrooms', 'square_feet'] }, maxItems: 20 }, market_data: { type: 'object', properties: { zip_code: { type: 'string', description: 'ZIP code of subject property' }, city: { type: 'string', description: 'City name' }, state: { type: 'string', description: 'State abbreviation' }, median_home_price: { type: 'number', minimum: 0, description: 'Area median home price' }, median_rent: { type: 'number', minimum: 0, description: 'Area median rent' }, price_per_sqft: { type: 'number', minimum: 0, description: 'Average price per square foot' }, rent_per_sqft: { type: 'number', minimum: 0, description: 'Average rent per square foot' }, days_on_market: { type: 'number', minimum: 0, description: 'Average days on market' }, inventory_months: { type: 'number', minimum: 0, description: 'Months of inventory' }, appreciation_rate_1yr: { type: 'number', description: '1-year appreciation rate (%)' }, appreciation_rate_5yr: { type: 'number', description: '5-year annualized appreciation rate (%)' }, rental_vacancy_rate: { type: 'number', minimum: 0, maximum: 100, description: 'Rental vacancy rate (%)' }, population_growth: { type: 'number', description: 'Annual population growth rate (%)' }, employment_growth: { type: 'number', description: 'Annual employment growth rate (%)' }, crime_score: { type: 'number', minimum: 0, maximum: 100, description: 'Crime safety score (100 = safest)' }, school_rating: { type: 'number', minimum: 1, maximum: 10, description: 'School district rating' } } }, analysis_options: { type: 'object', properties: { analysis_type: { type: 'string', enum: ['investment', 'primary_residence', 'flip', 'rental'], description: 'Type of analysis to perform' }, max_comp_distance: { type: 'number', minimum: 0, maximum: 10, description: 'Maximum distance for comps (miles)' }, max_comp_age: { type: 'number', minimum: 1, maximum: 365, description: 'Maximum age of comps (days)' }, adjustment_factors: { type: 'object', properties: { condition_adjustments: { type: 'object', properties: { poor: { type: 'number', description: 'Adjustment for poor condition (%)' }, fair: { type: 'number', description: 'Adjustment for fair condition (%)' }, good: { type: 'number', description: 'Adjustment for good condition (%)' }, excellent: { type: 'number', description: 'Adjustment for excellent condition (%)' } } }, size_adjustment_per_sqft: { type: 'number', description: 'Price adjustment per square foot difference' }, age_adjustment_per_year: { type: 'number', description: 'Price adjustment per year of age difference' }, lot_size_adjustment: { type: 'number', description: 'Adjustment for lot size differences (%)' } } } } } }, required: ['subject_property', 'comparable_properties'] }; } calculate(params) { const { subject_property, comparable_properties, market_data = {}, analysis_options = {} } = params; // Set defaults const analysis_type = analysis_options.analysis_type || 'investment'; const max_comp_distance = analysis_options.max_comp_distance || 2.0; const max_comp_age = analysis_options.max_comp_age || 180; // Filter and score comparables const scored_comps = this.scoreComparables( subject_property, comparable_properties, max_comp_distance, max_comp_age ); // Perform CMA (Comparative Market Analysis) const cma_analysis = this.performCMA( subject_property, scored_comps, analysis_options.adjustment_factors ); // Market trends analysis const market_trends = this.analyzeMarketTrends(market_data); // Investment analysis if applicable const investment_analysis = analysis_type === 'investment' || analysis_type === 'rental' ? this.performInvestmentAnalysis(subject_property, cma_analysis, market_data) : null; // Neighborhood analysis const neighborhood_analysis = this.analyzeNeighborhood(market_data); // Risk assessment const risk_assessment = this.assessMarketRisk(market_data, market_trends); // Price recommendations const price_recommendations = this.generatePriceRecommendations( cma_analysis, market_trends, analysis_type ); // Market timing analysis const timing_analysis = this.analyzeMarketTiming(market_data, market_trends); return { subject_property_analysis: { ...subject_property, price_per_sqft: subject_property.asking_price ? subject_property.asking_price / subject_property.square_feet : null, rent_per_sqft: subject_property.estimated_rent ? (subject_property.estimated_rent * 12) / subject_property.square_feet : null }, comparable_analysis: { total_comps_found: comparable_properties.length, qualified_comps: scored_comps.filter(c => c.score >= 70).length, best_comps: scored_comps.slice(0, 5), comp_statistics: this.calculateCompStatistics(scored_comps) }, cma_results: cma_analysis, market_trends: market_trends, neighborhood_analysis: neighborhood_analysis, investment_analysis: investment_analysis, risk_assessment: risk_assessment, price_recommendations: price_recommendations, timing_analysis: timing_analysis, recommendations: this.generateRecommendations( cma_analysis, market_trends, investment_analysis, risk_assessment, analysis_type ) }; } scoreComparables(subject, comps, maxDistance, maxAge) { const currentDate = new Date(); return comps.map(comp => { let score = 100; const reasons = []; // Age of sale const saleDate = new Date(comp.sale_date); const daysSinceSale = (currentDate - saleDate) / (1000 * 60 * 60 * 24); if (daysSinceSale > maxAge) { score -= 30; reasons.push(`Sale is ${Math.round(daysSinceSale)} days old`); } else if (daysSinceSale > 90) { score -= 10; reasons.push('Sale is over 90 days old'); } // Distance if (comp.distance_miles > maxDistance) { score -= 25; reasons.push(`Distance (${comp.distance_miles} mi) exceeds preferred range`); } else if (comp.distance_miles > 1.0) { score -= 10; reasons.push('Distance over 1 mile'); } // Bedroom/bathroom match if (comp.bedrooms !== subject.bedrooms) { score -= Math.abs(comp.bedrooms - subject.bedrooms) * 5; reasons.push(`Bedroom count differs by ${Math.abs(comp.bedrooms - subject.bedrooms)}`); } if (Math.abs(comp.bathrooms - subject.bathrooms) > 0.5) { score -= Math.abs(comp.bathrooms - subject.bathrooms) * 3; reasons.push('Bathroom count differs significantly'); } // Square footage similarity const sqftDiff = Math.abs(comp.square_feet - subject.square_feet); const sqftPctDiff = sqftDiff / subject.square_feet; if (sqftPctDiff > 0.3) { score -= 20; reasons.push(`Square footage differs by ${Math.round(sqftPctDiff * 100)}%`); } else if (sqftPctDiff > 0.15) { score -= 10; reasons.push('Significant square footage difference'); } // Age similarity if (comp.year_built && subject.year_built) { const ageDiff = Math.abs(comp.year_built - subject.year_built); if (ageDiff > 20) { score -= 10; reasons.push(`Age differs by ${ageDiff} years`); } } // Condition adjustment if (comp.condition) { const conditionScores = { poor: -15, fair: -5, good: 0, excellent: 5 }; score += conditionScores[comp.condition] || 0; if (comp.condition === 'poor' || comp.condition === 'fair') { reasons.push(`${comp.condition} condition`); } } return { ...comp, score: Math.max(0, score), score_reasons: reasons, price_per_sqft: comp.sale_price / comp.square_feet, days_since_sale: Math.round(daysSinceSale) }; }).sort((a, b) => b.score - a.score); } performCMA(subject, scoredComps, adjustmentFactors = {}) { const qualifiedComps = scoredComps.filter(c => c.score >= 60); if (qualifiedComps.length === 0) { return { estimated_value: null, confidence: 'low', error: 'No qualified comparables found' }; } // Apply adjustments to comps const adjustedComps = qualifiedComps.map(comp => { let adjustedPrice = comp.sale_price; const adjustments = []; // Square footage adjustment if (adjustmentFactors.size_adjustment_per_sqft) { const sqftDiff = subject.square_feet - comp.square_feet; const sqftAdjustment = sqftDiff * adjustmentFactors.size_adjustment_per_sqft; adjustedPrice += sqftAdjustment; if (Math.abs(sqftAdjustment) > 1000) { adjustments.push(`Size: ${sqftAdjustment > 0 ? '+' : ''}$${Math.round(sqftAdjustment).toLocaleString()}`); } } // Age adjustment if (adjustmentFactors.age_adjustment_per_year && comp.year_built && subject.year_built) { const ageDiff = subject.year_built - comp.year_built; const ageAdjustment = ageDiff * adjustmentFactors.age_adjustment_per_year; adjustedPrice += ageAdjustment; if (Math.abs(ageAdjustment) > 500) { adjustments.push(`Age: ${ageAdjustment > 0 ? '+' : ''}$${Math.round(ageAdjustment).toLocaleString()}`); } } // Condition adjustment if (adjustmentFactors.condition_adjustments && comp.condition) { const conditionAdjustment = (adjustmentFactors.condition_adjustments[comp.condition] || 0) / 100 * comp.sale_price; adjustedPrice += conditionAdjustment; if (Math.abs(conditionAdjustment) > 1000) { adjustments.push(`Condition: ${conditionAdjustment > 0 ? '+' : ''}$${Math.round(conditionAdjustment).toLocaleString()}`); } } return { ...comp, adjusted_price: adjustedPrice, adjustments: adjustments, price_per_sqft_adjusted: adjustedPrice / comp.square_feet }; }); // Calculate value estimates using different methods const adjustedPrices = adjustedComps.map(c => c.adjusted_price); const weights = adjustedComps.map(c => c.score / 100); // Weighted average const weightedSum = adjustedPrices.reduce((sum, price, i) => sum + (price * weights[i]), 0); const weightSum = weights.reduce((sum, weight) => sum + weight, 0); const weightedAverage = weightedSum / weightSum; // Simple average of top 3 comps const top3Average = adjustedPrices.slice(0, 3).reduce((sum, price) => sum + price, 0) / Math.min(3, adjustedPrices.length); // Median const sortedPrices = [...adjustedPrices].sort((a, b) => a - b); const median = sortedPrices.length % 2 === 0 ? (sortedPrices[sortedPrices.length / 2 - 1] + sortedPrices[sortedPrices.length / 2]) / 2 : sortedPrices[Math.floor(sortedPrices.length / 2)]; // Final estimate (weighted average of methods) const finalEstimate = (weightedAverage * 0.5) + (top3Average * 0.3) + (median * 0.2); // Confidence assessment const priceSpread = Math.max(...adjustedPrices) - Math.min(...adjustedPrices); const priceCV = this.calculateCoefficientOfVariation(adjustedPrices); let confidence; if (qualifiedComps.length >= 5 && priceCV < 0.15) { confidence = 'high'; } else if (qualifiedComps.length >= 3 && priceCV < 0.25) { confidence = 'medium'; } else { confidence = 'low'; } return { estimated_value: Math.round(finalEstimate), value_range: { low: Math.round(Math.min(...adjustedPrices)), high: Math.round(Math.max(...adjustedPrices)) }, confidence: confidence, price_per_sqft: Math.round(finalEstimate / subject.square_feet), valuation_methods: { weighted_average: Math.round(weightedAverage), top_3_average: Math.round(top3Average), median: Math.round(median) }, adjusted_comparables: adjustedComps.slice(0, 5), statistics: { comp_count: qualifiedComps.length, price_spread: Math.round(priceSpread), coefficient_of_variation: priceCV, average_score: qualifiedComps.reduce((sum, c) => sum + c.score, 0) / qualifiedComps.length } }; } analyzeMarketTrends(marketData) { if (!marketData || Object.keys(marketData).length === 0) { return { trend_direction: 'unknown', trend_strength: 'unknown', market_conditions: 'insufficient_data' }; } const trends = { price_trend: this.categorizeTrend(marketData.appreciation_rate_1yr, [0, 5, 10]), inventory_level: this.categorizeInventory(marketData.inventory_months), market_velocity: this.categorizeVelocity(marketData.days_on_market), population_trend: this.categorizeTrend(marketData.population_growth, [0, 1, 3]), employment_trend: this.categorizeTrend(marketData.employment_growth, [0, 2, 5]) }; // Overall market condition const positiveIndicators = Object.values(trends).filter(t => t === 'strong_positive' || t === 'moderate_positive' || t === 'fast' || t === 'low' ).length; const negativeIndicators = Object.values(trends).filter(t => t === 'strong_negative' || t === 'moderate_negative' || t === 'slow' || t === 'high' ).length; let marketCondition; if (positiveIndicators >= 3) { marketCondition = 'strong_buyers_market'; } else if (positiveIndicators >= 2) { marketCondition = 'moderate_buyers_market'; } else if (negativeIndicators >= 3) { marketCondition = 'sellers_market'; } else { marketCondition = 'balanced_market'; } return { ...trends, overall_market_condition: marketCondition, market_strength_score: this.calculateMarketStrength(marketData), trend_summary: this.generateTrendSummary(trends, marketCondition) }; } performInvestmentAnalysis(subject, cmaResults, marketData) { if (!cmaResults.estimated_value || !subject.estimated_rent) { return { analysis_possible: false, reason: 'Insufficient data for investment analysis' }; } const propertyValue = subject.asking_price || cmaResults.estimated_value; const monthlyRent = subject.estimated_rent; const annualRent = monthlyRent * 12; // Basic investment metrics const grossRentMultiplier = propertyValue / annualRent; const monthlyGrossYield = (monthlyRent / propertyValue) * 100; const annualGrossYield = monthlyGrossYield * 12; // Cap rate estimation (assuming 40% expense ratio) const estimatedExpenseRatio = 0.40; const noi = annualRent * (1 - estimatedExpenseRatio); const capRate = (noi / propertyValue) * 100; // Cash-on-cash estimation (assuming 25% down) const downPayment = propertyValue * 0.25; const loanAmount = propertyValue * 0.75; const monthlyPayment = this.calculateMonthlyPayment(loanAmount, 0.07, 30); const annualDebtService = monthlyPayment * 12; const annualCashFlow = noi - annualDebtService; const cashOnCashReturn = (annualCashFlow / downPayment) * 100; // 1% rule and 2% rule const onePercentRule = monthlyRent / propertyValue >= 0.01; const twoPercentRule = monthlyRent / propertyValue >= 0.02; // Rent-to-price ratio analysis const marketMedianRent = marketData.median_rent || 0; const marketMedianPrice = marketData.median_home_price || 0; const marketRentRatio = marketMedianPrice > 0 ? (marketMedianRent * 12) / marketMedianPrice : 0; const subjectRentRatio = annualRent / propertyValue; return { analysis_possible: true, basic_metrics: { gross_rent_multiplier: grossRentMultiplier, monthly_gross_yield: monthlyGrossYield, annual_gross_yield: annualGrossYield, estimated_cap_rate: capRate, estimated_cash_on_cash: cashOnCashReturn }, rule_analysis: { one_percent_rule: onePercentRule, two_percent_rule: twoPercentRule, rent_to_price_ratio: subjectRentRatio, market_rent_ratio: marketRentRatio, ratio_comparison: subjectRentRatio > marketRentRatio ? 'above_market' : 'below_market' }, cash_flow_estimate: { annual_rent: annualRent, estimated_noi: noi, estimated_cash_flow: annualCashFlow, down_payment_25pct: downPayment, monthly_payment_estimate: monthlyPayment }, investment_grade: this.gradeInvestment(capRate, cashOnCashReturn, onePercentRule) }; } analyzeNeighborhood(marketData) { if (!marketData) { return { analysis_available: false }; } const scores = { safety: marketData.crime_score || 50, schools: marketData.school_rating ? marketData.school_rating * 10 : 50, growth: this.scoreGrowth(marketData.population_growth, marketData.employment_growth), affordability: this.scoreAffordability(marketData.median_home_price, marketData.median_rent) }; const overallScore = Object.values(scores).reduce((sum, score) => sum + score, 0) / Object.keys(scores).length; let neighborhoodGrade; if (overallScore >= 80) neighborhoodGrade = 'A'; else if (overallScore >= 70) neighborhoodGrade = 'B'; else if (overallScore >= 60) neighborhoodGrade = 'C'; else if (overallScore >= 50) neighborhoodGrade = 'D'; else neighborhoodGrade = 'F'; return { analysis_available: true, scores: scores, overall_score: Math.round(overallScore), neighborhood_grade: neighborhoodGrade, strengths: this.identifyNeighborhoodStrengths(scores), concerns: this.identifyNeighborhoodConcerns(scores) }; } assessMarketRisk(marketData, marketTrends) { const risks = []; const opportunities = []; // Price appreciation risk if (marketData.appreciation_rate_1yr > 15) { risks.push({ category: 'Price Risk', level: 'High', description: 'Rapid price appreciation may indicate bubble conditions' }); } // Inventory risk if (marketData.inventory_months < 2) { risks.push({ category: 'Supply Risk', level: 'Medium', description: 'Very low inventory may lead to unsustainable price increases' }); } else if (marketData.inventory_months > 8) { opportunities.push({ category: 'Buyer Opportunity', description: 'High inventory provides negotiation leverage' }); } // Economic risk if (marketData.employment_growth < 0) { risks.push({ category: 'Economic Risk', level: 'High', description: 'Declining employment may impact property values and rental demand' }); } // Population trends if (marketData.population_growth < 0) { risks.push({ category: 'Demographic Risk', level: 'Medium', description: 'Population decline may reduce long-term demand' }); } else if (marketData.population_growth > 2) { opportunities.push({ category: 'Growth Opportunity', description: 'Strong population growth supports property demand' }); } // Rental market risk if (marketData.rental_vacancy_rate > 10) { risks.push({ category: 'Rental Risk', level: 'Medium', description: 'High vacancy rate indicates rental market challenges' }); } const riskScore = risks.reduce((score, risk) => { return score + (risk.level === 'High' ? 30 : risk.level === 'Medium' ? 20 : 10); }, 0); let overallRisk = 'Low'; if (riskScore >= 60) overallRisk = 'High'; else if (riskScore >= 30) overallRisk = 'Medium'; return { overall_risk_level: overallRisk, risk_score: riskScore, identified_risks: risks, opportunities: opportunities, risk_mitigation: this.generateRiskMitigation(risks) }; } generatePriceRecommendations(cmaResults, marketTrends, analysisType) { if (!cmaResults.estimated_value) { return { recommendations_available: false, reason: 'CMA analysis failed' }; } const estimatedValue = cmaResults.estimated_value; const recommendations = {}; // Buying recommendations if (analysisType === 'investment' || analysisType === 'primary_residence') { const maxOffer = estimatedValue * 0.95; // Start 5% below estimated value const walkAwayPrice = estimatedValue * 1.10; // Don't pay more than 10% above value recommendations.buying = { initial_offer: Math.round(maxOffer), max_offer: Math.round(estimatedValue), walk_away_price: Math.round(walkAwayPrice), negotiation_strategy: this.getNegotiationStrategy(marketTrends.overall_market_condition) }; } // Selling recommendations if (analysisType === 'flip') { const listPrice = estimatedValue * 1.05; // List 5% above estimated value const minAcceptable = estimatedValue * 0.95; // Accept down to 5% below value recommendations.selling = { suggested_list_price: Math.round(listPrice), minimum_acceptable: Math.round(minAcceptable), pricing_strategy: this.getPricingStrategy(marketTrends.overall_market_condition) }; } // Market timing advice recommendations.timing = this.getTimingAdvice(marketTrends); return { recommendations_available: true, estimated_market_value: estimatedValue, confidence_level: cmaResults.confidence, ...recommendations }; } analyzeMarketTiming(marketData, marketTrends) { const indicators = { price_momentum: marketTrends.price_trend, inventory_trend: marketTrends.inventory_level, economic_indicators: [marketTrends.population_trend, marketTrends.employment_trend], market_velocity: marketTrends.market_velocity }; // Score timing (1-10 scale) let timingScore = 5; // Neutral if (indicators.price_momentum === 'strong_positive') timingScore += 2; else if (indicators.price_momentum === 'moderate_positive') timingScore += 1; else if (indicators.price_momentum === 'moderate_negative') timingScore -= 1; else if (indicators.price_momentum === 'strong_negative') timingScore -= 2; if (indicators.inventory_trend === 'low') timingScore += 1; else if (indicators.inventory_trend === 'high') timingScore -= 1; const positiveEconomic = indicators.economic_indicators.filter(i => i === 'strong_positive' || i === 'moderate_positive').length; timingScore += positiveEconomic - 1; // +1 for each positive, -1 for neutral baseline if (indicators.market_velocity === 'fast') timingScore += 1; else if (indicators.market_velocity === 'slow') timingScore -= 1; timingScore = Math.max(1, Math.min(10, timingScore)); let timingRecommendation; if (timingScore >= 8) timingRecommendation = 'excellent_time_to_buy'; else if (timingScore >= 6) timingRecommendation = 'good_time_to_buy'; else if (timingScore >= 4) timingRecommendation = 'neutral_timing'; else timingRecommendation = 'consider_waiting'; return { timing_score: timingScore, timing_recommendation: timingRecommendation, key_factors: this.identifyKeyTimingFactors(indicators), seasonal_considerations: this.getSeasonalAdvice() }; } // Helper methods calculateMonthlyPayment(principal, rate, years) { const monthlyRate = rate / 12; const numPayments = years * 12; return principal * (monthlyRate * Math.pow(1 + monthlyRate, numPayments)) / (Math.pow(1 + monthlyRate, numPayments) - 1); } calculateCoefficientOfVariation(values) { const mean = values.reduce((sum, val) => sum + val, 0) / values.length; const variance = values.reduce((sum, val) => sum + Math.pow(val - mean, 2), 0) / values.length; const stdDev = Math.sqrt(variance); return stdDev / mean; } calculateCompStatistics(comps) { const prices = comps.map(c => c.sale_price); const pricesPerSqft = comps.map(c => c.price_per_sqft); return { average_price: prices.reduce((sum, p) => sum + p, 0) / prices.length, median_price: this.calculateMedian(prices), average_price_per_sqft: pricesPerSqft.reduce((sum, p) => sum + p, 0) / pricesPerSqft.length, median_price_per_sqft: this.calculateMedian(pricesPerSqft), price_range: { min: Math.min(...prices), max: Math.max(...prices) } }; } calculateMedian(arr) { const sorted = [...arr].sort((a, b) => a - b); const mid = Math.floor(sorted.length / 2); return sorted.length % 2 !== 0 ? sorted[mid] : (sorted[mid - 1] + sorted[mid]) / 2; } categorizeTrend(value, thresholds) { if (value === undefined || value === null) return 'unknown'; if (value >= thresholds[2]) return 'strong_positive'; if (value >= thresholds[1]) return 'moderate_positive'; if (value >= thresholds[0]) return 'stable'; if (value >= -thresholds[1]) return 'moderate_negative'; return 'strong_negative'; } categorizeInventory(months) { if (months === undefined || months === null) return 'unknown'; if (months < 3) return 'low'; if (months < 6) return 'balanced'; return 'high'; } categorizeVelocity(days) { if (days === undefined || days === null) return 'unknown'; if (days < 30) return 'fast'; if (days < 60) return 'moderate'; return 'slow'; } calculateMarketStrength(marketData) { let score = 50; // Base score if (marketData.appreciation_rate_1yr > 5) score += 10; if (marketData.inventory_months < 4) score += 10; if (marketData.days_on_market < 45) score += 10; if (marketData.population_growth > 1) score += 10; if (marketData.employment_growth > 2) score += 10; return Math.min(100, Math.max(0, score)); } generateRecommendations(cmaResults, marketTrends, investmentAnalysis, riskAssessment, analysisType) { const recommendations = []; // CMA-based recommendations if (cmaResults.confidence === 'high') { recommendations.push({ category: 'Valuation', priority: 'high', message: `Strong comparable data supports estimated value of $${cmaResults.estimated_value.toLocaleString()}` }); } else if (cmaResults.confidence === 'low') { recommendations.push({ category: 'Valuation', priority: 'high', message: 'Limited comparable data - consider additional market research or professional appraisal' }); } // Investment-specific recommendations if (investmentAnalysis && investmentAnalysis.analysis_possible) { if (investmentAnalysis.rule_analysis.one_percent_rule) { recommendations.push({ category: 'Investment', priority: 'high', message: 'Property meets 1% rule - strong cash flow potential' }); } if (investmentAnalysis.basic_metrics.estimated_cap_rate > 8) { recommendations.push({ category: 'Investment', priority: 'medium', message: 'High cap rate indicates good investment opportunity' }); } } // Market timing recommendations if (marketTrends.overall_market_condition === 'strong_buyers_market') { recommendations.push({ category: 'Timing', priority: 'high', message: 'Favorable market conditions for buyers - good time to purchase' }); } else if (marketTrends.overall_market_condition === 'sellers_market') { recommendations.push({ category: 'Timing', priority: 'medium', message: 'Competitive market - be prepared to act quickly and consider above-asking offers' }); } // Risk-based recommendations if (riskAssessment.overall_risk_level === 'High') { recommendations.push({ category: 'Risk Management', priority: 'high', message: 'High market risk identified - consider conservative financing and exit strategies' }); } return recommendations; } // Additional helper methods for various calculations... gradeInvestment(capRate, cocReturn, onePercentRule) { let score = 0; if (capRate > 10) score += 3; else if (capRate > 8) score += 2; else if (capRate > 6) score += 1; if (cocReturn > 15) score += 3; else if (cocReturn > 10) score += 2; else if (cocReturn > 5) score += 1; if (onePercentRule) score += 2; if (score >= 6) return 'A'; if (score >= 4) return 'B'; if (score >= 2) return 'C'; return 'D'; } scoreGrowth(popGrowth, empGrowth) { const avgGrowth = ((popGrowth || 0) + (empGrowth || 0)) / 2; if (avgGrowth > 3) return 90; if (avgGrowth > 1) return 75; if (avgGrowth > 0) return 60; if (avgGrowth > -1) return 40; return 20; } scoreAffordability(medianPrice, medianRent) { if (!medianPrice || !medianRent) return 50; const rentRatio = (medianRent * 12) / medianPrice; if (rentRatio > 0.15) return 80; if (rentRatio > 0.12) return 70; if (rentRatio > 0.08) return 60; if (rentRatio > 0.05) return 40; return 20; } identifyNeighborhoodStrengths(scores) { const strengths = []; if (scores.safety > 75) strengths.push('High safety rating'); if (scores.schools > 75) strengths.push('Excellent schools'); if (scores.growth > 75) strengths.push('Strong population and job growth'); if (scores.affordability > 75) strengths.push('Good rental yield potential'); return strengths; } identifyNeighborhoodConcerns(scores) { const concerns = []; if (scores.safety < 40) concerns.push('Safety concerns'); if (scores.schools < 40) concerns.push('Poor school ratings'); if (scores.growth < 40) concerns.push('Declining population/employment'); if (scores.affordability < 40) concerns.push('Low rental yields'); return concerns; } generateRiskMitigation(risks) { const mitigation = []; risks.forEach(risk => { switch (risk.category) { case 'Price Risk': mitigation.push('Consider conservative purchase price and financing'); break; case 'Economic Risk': mitigation.push('Focus on properties with diverse tenant base'); break; case 'Rental Risk': mitigation.push('Budget for extended vacancy periods'); break; default: mitigation.push('Monitor market conditions closely'); } }); return [...new Set(mitigation)]; // Remove duplicates } getTimingAdvice(marketTrends) { const condition = marketTrends.overall_market_condition; const advice = { strong_buyers_market: 'Excellent time to buy - negotiate aggressively', moderate_buyers_market: 'Good buying conditions - reasonable negotiations expected', balanced_market: 'Neutral market - focus on property-specific value', sellers_market: 'Competitive environment - be prepared to pay market value' }; return advice[condition] || 'Monitor market conditions'; } getNegotiationStrategy(marketCondition) { const strategies = { strong_buyers_market: 'Aggressive negotiations, multiple contingencies acceptable', moderate_buyers_market: 'Standard negotiations, reasonable contingencies', balanced_market: 'Fair market offers, minimal contingencies', sellers_market: 'Competitive offers, waive contingencies if possible' }; return strategies[marketCondition] || 'Standard negotiation approach'; } getPricingStrategy(marketCondition) { const strategies = { strong_buyers_market: 'Price competitively, expect negotiations', moderate_buyers_market: 'Market pricing, some negotiation room', balanced_market: 'Fair market pricing', sellers_market: 'Premium pricing, expect multiple offers' }; return strategies[marketCondition] || 'Market-based pricing'; } identifyKeyTimingFactors(indicators) { const factors = []; if (indicators.price_momentum && indicators.price_momentum.includes('positive')) { factors.push('Rising prices favor buyers entering now'); } if (indicators.inventory_trend === 'high') { factors.push('High inventory provides buyer leverage'); } if (indicators.market_velocity === 'fast') { factors.push('Fast-moving market requires quick decisions'); } return factors; } getSeasonalAdvice() { const month = new Date().getMonth() + 1; if (month >= 3 && month <= 6) { return 'Spring/early summer: Peak buying season with most inventory'; } else if (month >= 7 && month <= 9) { return 'Late summer: Good inventory, motivated sellers'; } else if (month >= 10 && month <= 12) { return 'Fall/winter: Lower inventory but less competition'; } else { return 'Winter: Lowest inventory but best deals from motivated sellers'; } } generateTrendSummary(trends, marketCondition) { const positiveTrends = Object.values(trends).filter(t => t.includes('positive') || t === 'fast' || t === 'low').length; let summary = `Market shows ${positiveTrends} positive indicators out of ${Object.keys(trends).length}. `; switch (marketCondition) { case 'strong_buyers_market': summary += 'Strong conditions favor buyers with multiple positive trends.'; break; case 'moderate_buyers_market': summary += 'Generally favorable conditions for buyers.'; break; case 'balanced_market': summary += 'Balanced conditions with mixed indicators.'; break; case 'sellers_market': summary += 'Market conditions favor sellers with limited inventory.'; break; default: summary += 'Market conditions are mixed with uncertain trends.'; } return summary; } }