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io.github.simonplmak-cloud/startup-valuation
serveur MCP (Model Context Protocol) · startup-valuation 2.1.0
Référencé dans l'annuaire. Seul le pentest comportemental fait foi, et il n'a pas encore été exécuté sur ce serveur.
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Les 14 outils
- valuation_advanced≈ 872 tokens
Advanced techniques: Black-Scholes call value, binomial-tree option value, and scenario analysis. Method selects the technique. For a quick expected value over arbitrary outcome lists, prefer valuation_probability with method 'probability_weighted'; scenario_analysis here is for explicit named bull/base/bear scenario tables. Parameters apply per method: black_scholes and binomial need underlying + strike + risk_free_rate + volatility + time_to_maturity (binomial adds steps); scenario_analysis needs scenarios. Not for plain discounted cash flow — for that use valuation_time_value. Only method is required; all other parameters are method-dependent, so supply those the selected method names and omit the rest (defaults apply where defined). Rate and decimal inputs are fractions (0.10 = 10%); probability and weight lists are in [0,1] and sum to 1. Returns value, method, inputs, assumptions, chapter, formula_number and calculation steps; pure arithmetic — no I/O and no external calls — rounded to 2 decimals, with no auth or rate limits. An unknown method, or a missing method-required parameter, returns an error instead of a value.
Paramètres, retour & exemple (8)
Paramètressteps· integer · optionnel
Binomial tree time steps (integer ≥ 1; higher = more accurate).method· string · requis · black_scholes | binomial | scenario_analysis
Formula to apply. Options: black_scholes = C = N(d₁)S - N(d₂)Ke^(-rT).; binomial = Cox-Ross-Rubinstein binomial option value.; scenario_analysis = E[V] = Σ pᵢ·Vᵢ over named scenarios.strike· number · optionnel
Strike / exercise price K, currency units.scenarios· array · optionnel
Scenario objects: {name: str, probability: 0-1, value: currency}; probabilities should sum to 1.underlying· number · optionnel
Underlying asset value S, currency units.volatility· number · optionnel
Annualised volatility σ as a decimal (0.80 = 80%).risk_free_rate· number · optionnel
Risk-free rate as a decimal (e.g. 0.04 for 4%).time_to_maturity· number · optionnel
Time to expiry in years T, must be ≥ 0.
Exemple d'appel{"name": "valuation_advanced", "arguments": {"method": "black_scholes"}}Exemple de retour{"content": [{"type": "text", "text": "…"}], "structuredContent": {"error": "texte", "steps": [], "value": 1, "inputs": {}, "method": "texte", "chapter": "texte", "assumptions": [], "formula_number": "texte", "defaults_applied": []}} - valuation_biotech≈ 882 tokens
Risk-adjusted biotech valuation: peak sales, decision-tree expected value, and full pipeline rNPV across drugs. Method selects the model. Use for pharma/drug pipelines; for hardware or deep tech use valuation_hardware. Parameters apply per method: peak_sales needs patient_population + penetration + price; decision_tree needs probabilities + terminal_value; pipeline needs drugs + discount_rate. Not for hardware or deep tech — for that use valuation_hardware. Only method is required; all other parameters are method-dependent, so supply those the selected method names and omit the rest (defaults apply where defined). Rate and decimal inputs are fractions (0.10 = 10%); probability and weight lists are in [0,1] and sum to 1. Returns value, method, inputs, assumptions, chapter, formula_number and calculation steps; pure arithmetic — no I/O and no external calls — rounded to 2 decimals, with no auth or rate limits. An unknown method, or a missing method-required parameter, returns an error instead of a value.
Paramètres, retour & exemple (9)
Paramètresdrugs· array · optionnel
Pipeline drugs: {name, peak_sales, probability, years_to_market, multiple(optional)}.price· number · optionnel
Price per unit / treatment, currency units.method· string · requis · peak_sales | decision_tree | pipeline
Formula to apply. Options: peak_sales = Peak = population × penetration × price × compliance.; decision_tree = EV = Π pᵢ × terminal value.; pipeline = V = Σ(peak sales × multiple × P_success) / (1+r)^n.compliance· number · optionnel
Compliance / adherence rate as a decimal.penetration· number · optionnel
Market penetration as a decimal (0.10 = 10%).discount_rate· number · optionnel
Discount rate as a decimal (0.12 = 12%).probabilities· array · optionnel
Probability of each outcome or stage, each in [0,1]; the list must sum to 1 where it is exhaustive.terminal_value· number · optionnel
Expected exit / terminal value, currency units.patient_population· number · optionnel
Target patient population treated per year.
Exemple d'appel{"name": "valuation_biotech", "arguments": {"method": "peak_sales"}}Exemple de retour{"content": [{"type": "text", "text": "…"}], "structuredContent": {"error": "texte", "steps": [], "value": 1, "inputs": {}, "method": "texte", "chapter": "texte", "assumptions": [], "formula_number": "texte", "defaults_applied": []}} - valuation_capm≈ 1047 tokens
Estimate the cost of capital: standard CAPM, startup-adjusted CAPM with size and illiquidity premiums, portfolio beta from weighted asset betas, and WACC blending after-tax cost of equity and debt. Method selects the formula. Use to derive the discount rate that feeds valuation_time_value and DCF models; for cross-border rates add valuation_international. Parameters apply per method: capm needs risk_free_rate + beta + market_return; startup_capm adds size_premium and liquidity_premium; portfolio_beta needs weights + betas, which must be equal length; wacc needs equity_value + debt_value + cost_of_equity + cost_of_debt + tax_rate. Only method is required; all other parameters are method-dependent, so supply those the selected method names and omit the rest (defaults apply where defined). Rate and decimal inputs are fractions (0.10 = 10%); probability and weight lists are in [0,1] and sum to 1. Returns value, method, inputs, assumptions, chapter, formula_number and calculation steps; pure arithmetic — no I/O and no external calls — rounded to 2 decimals, with no auth or rate limits. An unknown method, or a missing method-required parameter, returns an error instead of a value.
Paramètres, retour & exemple (14)
Paramètresbeta· number · optionnel
Systematic risk beta (market = 1.0).betas· array · optionnel
Asset betas aligned with weights; typically 0.5–3.0 (market = 1.0).method· string · requis · capm | startup_capm | portfolio_beta | wacc
Formula to apply. Options: capm = E(R) = Rf + β·(E(Rm) - Rf).; startup_capm = r = Rf + β·MRP + size premium + illiquidity premium.; portfolio_beta = βp = Σ wᵢ·βᵢ.; wacc = WACC = (E/V)·Re + (D/V)·Rd·(1 − T).weights· array · optionnel
Portfolio or factor weights, each in [0,1] and summing to 1 (same order as the paired value list).tax_rate· number · optionnel
Effective tax rate as a decimal in [0,1].debt_value· number · optionnel
Market value of debt, in currency units.cost_of_debt· number · optionnel
Pre-tax cost of debt Rd as a decimal.equity_value· number · optionnel
Value of equity offered, currency units.size_premium· number · optionnel
Small-cap / size premium as a decimal.market_return· number · optionnel
Expected market return as a decimal (e.g. 0.10 for 10%).cost_of_equity· number · optionnel
After-tax cost of equity Re as a decimal.risk_free_rate· number · optionnel
Risk-free rate as a decimal (e.g. 0.04 for 4%).liquidity_premium· number · optionnel
Illiquidity premium as a decimal.market_risk_premium· number · optionnel
Market risk premium as a decimal (e.g. 0.06).
Exemple d'appel{"name": "valuation_capm", "arguments": {"method": "capm"}}Exemple de retour{"content": [{"type": "text", "text": "…"}], "structuredContent": {"error": "texte", "steps": [], "value": 1, "inputs": {}, "method": "texte", "chapter": "texte", "assumptions": [], "formula_number": "texte", "defaults_applied": []}} - valuation_comparables≈ 1034 tokens
Market multiples from comparables: P/E, P/S, EV/EBITDA, EV/Revenue, and a regression-adjusted multiple. Method selects the ratio. Use when public comparables exist; for pre-revenue or private startups use valuation_core. Parameters apply per method: pe_ratio needs market_cap + net_income; ps_ratio needs market_cap + revenue; ev_ebitda needs enterprise_value + ebitda; ev_revenue needs enterprise_value + revenue; regression_multiple needs intercept + growth_rate + growth_coefficient (plus optional maturity/stage/geography terms). Only method is required; all other parameters are method-dependent, so supply those the selected method names and omit the rest (defaults apply where defined). Rate and decimal inputs are fractions (0.10 = 10%); probability and weight lists are in [0,1] and sum to 1. Returns value, method, inputs, assumptions, chapter, formula_number and calculation steps; pure arithmetic — no I/O and no external calls — rounded to 2 decimals, with no auth or rate limits. An unknown method, or a missing method-required parameter, returns an error instead of a value.
Paramètres, retour & exemple (15)
Paramètresstage· number · optionnel
Company stage indicator.ebitda· number · optionnel
EBITDA, currency units.method· string · requis · pe_ratio | ps_ratio | ev_ebitda | ev_revenue | regression_multiple
Formula to apply. Options: pe_ratio = P/E = market cap / net income.; ps_ratio = P/S = market cap / revenue.; ev_ebitda = EV/EBITDA = enterprise value / EBITDA.; ev_revenue = EV/Revenue = enterprise value / revenue.; regression_multiple = Multiple = β0 + β1·g + β2·M + β3·S + β4·G.revenue· number · optionnel
Revenue for the period, currency units.geography· number · optionnel
Geography indicator.intercept· number · optionnel
Regression intercept β0 (base multiple).market_cap· number · optionnel
Market capitalisation, currency units.net_income· number · optionnel
Net income (earnings), currency units.growth_rate· number · optionnel
Revenue growth rate as a decimal (0.40 = 40%).market_maturity· number · optionnel
Market maturity indicator.enterprise_value· number · optionnel
Enterprise value (market cap + net debt), currency units.stage_coefficient· number · optionnel
Regression slope on stage.growth_coefficient· number · optionnel
Regression slope on growth (multiple points per unit growth).maturity_coefficient· number · optionnel
Regression slope on market maturity.geography_coefficient· number · optionnel
Regression slope on geography.
Exemple d'appel{"name": "valuation_comparables", "arguments": {"method": "pe_ratio"}}Exemple de retour{"content": [{"type": "text", "text": "…"}], "structuredContent": {"error": "texte", "steps": [], "value": 1, "inputs": {}, "method": "texte", "chapter": "texte", "assumptions": [], "formula_number": "texte", "defaults_applied": []}} - valuation_core≈ 1294 tokens
The textbook's pre-revenue methods: Scorecard, Berkus, Risk-Factor Summation, VC Method (post- and pre-money), and exit terminal value. Use these first for early-stage startups. Method selects the formula, and each method names its own parameters: scorecard needs average_valuation + weights + scores; berkus takes five factor awards; risk_factor needs base_valuation + risk_ratings; vc_post_money needs terminal_value + target_return; vc_pre_money needs post_money + investment; terminal_value needs projected_revenue + multiple; triangulated needs the scorecard inputs plus terminal_value/target_return/investment. Routing: for SAFEs, tokens, ESG, network effects, or data-moat methods use valuation_emerging; for options or bull/base/bear scenario tables use valuation_advanced; for public-comparable multiples use valuation_comparables. Only method is required; all other parameters are method-dependent, so supply those the selected method names and omit the rest (defaults apply where defined). Rate and decimal inputs are fractions (0.10 = 10%); probability and weight lists are in [0,1] and sum to 1. Returns value, method, inputs, assumptions, chapter, formula_number and calculation steps; pure arithmetic — no I/O and no external calls — rounded to 2 decimals, with no auth or rate limits. An unknown method, or a missing method-required parameter, returns an error instead of a value.
Paramètres, retour & exemple (17)
Paramètresmethod· string · requis · scorecard | berkus | risk_factor | vc_post_money | vc_pre_money | terminal_value | triangulated
Formula to apply. Options: scorecard = V = V_avg · Σ(wᵢ·sᵢ) across 7 factors.; berkus = V = Σ factor awards, each capped at $500K.; risk_factor = V = V_base + Σ(rᵢ·$250K) over 12 risks.; vc_post_money = Post = Terminal / target ROI.; vc_pre_money = Pre = Post - Investment.; terminal_value = Terminal = projected revenue × multiple.; triangulated = Runs Scorecard and the VC Method together and returns their mean.scores· array · optionnel
Factor multipliers aligned with weights (1.0 = average, >1 above average).weights· array · optionnel
Portfolio or factor weights, each in [0,1] and summing to 1 (same order as the paired value list).multiple· number · optionnel
Exit or market multiple applied to the metric.prototype· number · optionnel
Berkus award for prototype / technology, 0 to 500,000.investment· number · optionnel
Amount invested, currency units.post_money· number · optionnel
Post-money valuation, currency units.sound_idea· number · optionnel
Berkus award for soundness of the idea, 0 to 500,000 (USD).quality_team· number · optionnel
Berkus award for management team, 0 to 500,000.risk_ratings· array · optionnel
12 risk factor ratings in [-2,2] (very low to very high); each unit shifts value ±250,000.target_return· number · optionnel
VC target return multiple (e.g. 10 for a 10x target).base_valuation· number · optionnel
Pre-adjustment baseline valuation, currency units.terminal_value· number · optionnel
Expected exit / terminal value, currency units.product_rollout· number · optionnel
Berkus award for product rollout / sales, 0 to 500,000.average_valuation· number · optionnel
Average pre-revenue valuation for the sector, currency units.projected_revenue· number · optionnel
Projected revenue at exit, currency units.strategic_relationships· number · optionnel
Berkus award for strategic relationships, 0 to 500,000.
Exemple d'appel{"name": "valuation_core", "arguments": {"method": "scorecard"}}Exemple de retour{"content": [{"type": "text", "text": "…"}], "structuredContent": {"error": "texte", "steps": [], "value": 1, "inputs": {}, "method": "texte", "chapter": "texte", "assumptions": [], "formula_number": "texte", "defaults_applied": []}} - valuation_emerging≈ 1724 tokens
Modern and alternative valuation: SAFE conversion (discount, cap, expected value), token valuation (equation of exchange, NVT), ESG adjustments (rate, premium, discount), Metcalfe network value, data-moat value, and remote-first premium/NPV. Method selects the model. Use for SAFEs, tokens, ESG, network effects, data moats, and remote-first adjustments; for classic pre-revenue methods use valuation_core. Parameters apply per method: safe_discount needs series_a_price + discount; safe_cap needs cap + series_a_price; safe_expected needs investment + cap + discount + series_a_valuation + series_a_price; token_value needs transaction_volume + price_per_tx + velocity + supply; metcalfe needs n; esg_* need base_valuation + a score; data_moat needs data_volume + data_uniqueness + monetization_rate + competitive_advantage_years. Routing: for classic pre-revenue methods (Scorecard, Berkus, Risk-Factor Summation, VC Method) use valuation_core; for options or scenario tables use valuation_advanced; for public-comparable multiples use valuation_comparables. Only method is required; all other parameters are method-dependent, so supply those the selected method names and omit the rest (defaults apply where defined). Rate and decimal inputs are fractions (0.10 = 10%); probability and weight lists are in [0,1] and sum to 1. Returns value, method, inputs, assumptions, chapter, formula_number and calculation steps; pure arithmetic — no I/O and no external calls — rounded to 2 decimals, with no auth or rate limits. An unknown method, or a missing method-required parameter, returns an error instead of a value.
Paramètres, retour & exemple (30)
Paramètresk· integer · optionnel
Number of events k for the Poisson probability P(X=k); integer ≥ 0.n· number · optionnel
Number of users or nodes in the network.cap· number · optionnel
SAFE valuation cap, currency units.rate· number · optionnel
Per-period discount rate as a decimal (0.10 = 10%).method· string · requis · safe_discount | safe_cap | safe_expected | token_value | nvt_ratio | esg_rate | esg_premium | esg_discount
Formula to apply. Options: safe_discount = Price = Series A price × (1 - discount).; safe_cap = Price = cap / pre-money shares (cap-based).; safe_expected = Expected SAFE value across cap and discount outcomes.; token_value = Value = (volume × price) / (velocity × supply).; nvt_ratio = NVT = market cap / daily transaction volume.; esg_rate = r = base + ESG risk premium - ESG opportunity discount.; esg_premium = Valuation uplift = base × (1 + score × premium per point).; esg_discount = Valuation reduction = base × (1 - risk score × discount per point).; metcalfe = V = k · n².; data_moat = Discounted value of monetised proprietary data.; remote_npv = Perpetuity NPV = annual savings / discount rate.; remote_premium = Valuation premium from cost savings, talent access, and productivity.supply· number · optionnel
Circulating token supply.discount· number · optionnel
Conversion discount as a decimal (0.20 = 20% discount).velocity· number · optionnel
Token velocity (turnover of supply per period).esg_score· number · optionnel
ESG score in points (e.g. 0-100).investment· number · optionnel
Amount invested, currency units.market_cap· number · optionnel
Market capitalisation, currency units.data_volume· number · optionnel
Volume of proprietary data held.price_per_tx· number · optionnel
Protocol revenue per transaction, currency units.discount_rate· number · optionnel
Discount rate as a decimal (0.12 = 12%).annual_savings· number · optionnel
Annual cost savings, currency units.base_valuation· number · optionnel
Pre-adjustment baseline valuation, currency units.esg_risk_score· number · optionnel
ESG risk score in points (higher = riskier).series_a_price· number · optionnel
Price per share in the next priced (Series A) round.data_uniqueness· number · optionnel
Uniqueness / scarcity of the data in [0,1].cost_savings_pct· number · optionnel
Cost savings as a fraction of baseline.esg_risk_premium· number · optionnel
ESG risk premium added to the rate, as a decimal.monetization_rate· number · optionnel
Fraction of data value monetisable as a decimal.premium_per_point· number · optionnel
Valuation premium per ESG point as a decimal.productivity_gain· number · optionnel
Productivity gain as a decimal.discount_per_point· number · optionnel
Valuation discount per ESG risk point as a decimal.series_a_valuation· number · optionnel
Series A post-money valuation, currency units.transaction_volume· number · optionnel
Total payment transaction volume, currency units.talent_access_premium· number · optionnel
Talent-access premium as a decimal.esg_opportunity_discount· number · optionnel
ESG opportunity discount subtracted from the rate.competitive_advantage_years· number · optionnel
Years the data moat is expected to last.
Exemple d'appel{"name": "valuation_emerging", "arguments": {"method": "safe_discount"}}Exemple de retour{"content": [{"type": "text", "text": "…"}], "structuredContent": {"error": "texte", "steps": [], "value": 1, "inputs": {}, "method": "texte", "chapter": "texte", "assumptions": [], "formula_number": "texte", "defaults_applied": []}} - valuation_fintech≈ 1027 tokens
Value and size fintech business models: payment revenue, lending valuation, payment-processor DCF, and neobank customer-based valuation. Method selects the model. Use for payments, lending, and neobanks; for SaaS-style unit economics use valuation_saas. Parameters apply per method: payment_revenue needs transaction_volume + take_rate; lending needs loan_book + roe + pe_multiple; payment_processor adds growth_rate + discount_rate + terminal_multiple; neobank needs customers + arpu + gross_margin + churn_rate + pe_multiple. Only method is required; all other parameters are method-dependent, so supply those the selected method names and omit the rest (defaults apply where defined). Rate and decimal inputs are fractions (0.10 = 10%); probability and weight lists are in [0,1] and sum to 1. Returns value, method, inputs, assumptions, chapter, formula_number and calculation steps; pure arithmetic — no I/O and no external calls — rounded to 2 decimals, with no auth or rate limits. An unknown method, or a missing method-required parameter, returns an error instead of a value.
Paramètres, retour & exemple (15)
Paramètresroe· number · optionnel
Return on equity as a decimal (0.20 = 20%).arpu· number · optionnel
Average revenue per user per month, currency units.years· integer · optionnel
Forecast horizon in years; integer ≥ 1.method· string · requis · payment_revenue | lending | payment_processor | neobank
Formula to apply. Options: payment_revenue = Revenue = volume × take rate.; lending = V = loan book × ROE × P/E - NPL reserves.; payment_processor = DCF of payment revenue with a terminal multiple.; neobank = Customer LTV × P/E applied to the customer base.customers· integer · optionnel
Number of customers.loan_book· number · optionnel
Outstanding loan book / principal, currency units.take_rate· number · optionnel
Take rate as a decimal (0.15 = 15% of GMV).churn_rate· number · optionnel
Periodic churn rate as a decimal (0.02 = 2% per month).growth_rate· number · optionnel
Revenue growth rate as a decimal (0.40 = 40%).pe_multiple· number · optionnel
Price/earnings multiple applied to earnings.gross_margin· number · optionnel
Gross margin as a decimal (0.80 = 80%).npl_reserves· number · optionnel
Non-performing loan reserves deducted, currency units.discount_rate· number · optionnel
Discount rate as a decimal (0.12 = 12%).terminal_multiple· number · optionnel
Terminal value multiple applied at the horizon.transaction_volume· number · optionnel
Total payment transaction volume, currency units.
Exemple d'appel{"name": "valuation_fintech", "arguments": {"method": "payment_revenue"}}Exemple de retour{"content": [{"type": "text", "text": "…"}], "structuredContent": {"error": "texte", "steps": [], "value": 1, "inputs": {}, "method": "texte", "chapter": "texte", "assumptions": [], "formula_number": "texte", "defaults_applied": []}} - valuation_hardware≈ 842 tokens
Hardware and deep-tech valuation: TRL-risk-adjusted valuation, gross margin, and break-even volume. Method selects the metric. Use for hardware and deep tech with technology-readiness risk; for drug pipelines use valuation_biotech. Parameters apply per method: trl needs market_size + market_share + margin + multiple + trl_discount; gross_margin needs asp + variable_cost; break_even_volume needs fixed_costs + asp + variable_cost. Not for drug pipelines — for those use valuation_biotech. Only method is required; all other parameters are method-dependent, so supply those the selected method names and omit the rest (defaults apply where defined). Rate and decimal inputs are fractions (0.10 = 10%); probability and weight lists are in [0,1] and sum to 1. Returns value, method, inputs, assumptions, chapter, formula_number and calculation steps; pure arithmetic — no I/O and no external calls — rounded to 2 decimals, with no auth or rate limits. An unknown method, or a missing method-required parameter, returns an error instead of a value.
Paramètres, retour & exemple (9)
Paramètresasp· number · optionnel
Average selling price per unit, currency units.margin· number · optionnel
Profit margin as a decimal.method· string · requis · trl | gross_margin | break_even_volume
Formula to apply. Options: trl = V = market × share × margin × multiple × (1 - TRL discount).; gross_margin = GM = (ASP - COGS) / ASP.; break_even_volume = Units = fixed costs / (ASP - variable cost).multiple· number · optionnel
Exit or market multiple applied to the metric.fixed_costs· number · optionnel
Fixed costs for the period, currency units.market_size· number · optionnel
Total addressable market, currency units.market_share· number · optionnel
Target market share as a decimal in [0,1].trl_discount· number · optionnel
TRL risk discount as a decimal (applied as 1 - discount).variable_cost· number · optionnel
Variable cost per unit, currency units.
Exemple d'appel{"name": "valuation_hardware", "arguments": {"method": "trl"}}Exemple de retour{"content": [{"type": "text", "text": "…"}], "structuredContent": {"error": "texte", "steps": [], "value": 1, "inputs": {}, "method": "texte", "chapter": "texte", "assumptions": [], "formula_number": "texte", "defaults_applied": []}} - valuation_international≈ 858 tokens
Cross-border adjustments: purchasing-power parity, country risk premium, and international CAPM. Method selects the adjustment. Use for cross-border cash flows and country risk; pair with valuation_capm and valuation_time_value. Parameters apply per method: ppp needs spot_rate + inflation_foreign + inflation_domestic; country_risk_premium needs sovereign_yield + us_treasury_yield; intl_capm needs risk_free_rate + beta + mrp + crp. Not for the domestic cost of equity — for that use valuation_capm. Only method is required; all other parameters are method-dependent, so supply those the selected method names and omit the rest (defaults apply where defined). Rate and decimal inputs are fractions (0.10 = 10%); probability and weight lists are in [0,1] and sum to 1. Returns value, method, inputs, assumptions, chapter, formula_number and calculation steps; pure arithmetic — no I/O and no external calls — rounded to 2 decimals, with no auth or rate limits. An unknown method, or a missing method-required parameter, returns an error instead of a value.
Paramètres, retour & exemple (10)
Paramètrescrp· number · optionnel
Country risk premium as a decimal.mrp· number · optionnel
Market risk premium as a decimal.beta· number · optionnel
Systematic risk beta (market = 1.0).method· string · requis · ppp | country_risk_premium | intl_capm
Formula to apply. Options: ppp = Eₜ = E₀·(1+π_foreign)/(1+π_domestic).; country_risk_premium = CRP = sovereign yield - US Treasury yield.; intl_capm = r = Rf + β·MRP + CRP.spot_rate· number · optionnel
Spot FX rate (domestic per foreign), e.g. 7.2 CNY/USD.risk_free_rate· number · optionnel
Risk-free rate as a decimal (e.g. 0.04 for 4%).sovereign_yield· number · optionnel
Foreign sovereign bond yield as a decimal.inflation_foreign· number · optionnel
Foreign inflation rate as a decimal.us_treasury_yield· number · optionnel
US Treasury yield as a decimal.inflation_domestic· number · optionnel
Domestic inflation rate as a decimal.
Exemple d'appel{"name": "valuation_international", "arguments": {"method": "ppp"}}Exemple de retour{"content": [{"type": "text", "text": "…"}], "structuredContent": {"error": "texte", "steps": [], "value": 1, "inputs": {}, "method": "texte", "chapter": "texte", "assumptions": [], "formula_number": "texte", "defaults_applied": []}} - valuation_marketplace≈ 854 tokens
Marketplace health and valuation: take rate, GMV revenue-multiple valuation, buyer retention, and network density. Method selects the metric. Use for two-sided transaction marketplaces; for subscription software use valuation_saas. Parameters apply per method: take_rate needs revenue + gmv; gmv_multiple needs gmv + multiple; buyer_retention needs buyers_period_1 + buyers_repeat; network_density needs active_buyers + active_sellers + total_users. Only method is required; all other parameters are method-dependent, so supply those the selected method names and omit the rest (defaults apply where defined). Rate and decimal inputs are fractions (0.10 = 10%); probability and weight lists are in [0,1] and sum to 1. Returns value, method, inputs, assumptions, chapter, formula_number and calculation steps; pure arithmetic — no I/O and no external calls — rounded to 2 decimals, with no auth or rate limits. An unknown method, or a missing method-required parameter, returns an error instead of a value.
Paramètres, retour & exemple (9)
Paramètresgmv· number · optionnel
Gross merchandise value (total transaction volume), currency units.method· string · requis · take_rate | gmv_multiple | buyer_retention | network_density
Formula to apply. Options: take_rate = Take rate = revenue / GMV.; gmv_multiple = Valuation = GMV × multiple.; buyer_retention = Retention = repeat buyers / base-period buyers.; network_density = Density = active buyers × active sellers / total users.revenue· number · optionnel
Revenue for the period, currency units.multiple· number · optionnel
Exit or market multiple applied to the metric.total_users· integer · optionnel
Total users (buyers + sellers) in the period.active_buyers· integer · optionnel
Active buyers in the period.buyers_repeat· integer · optionnel
Distinct buyers from the base period who purchased again.active_sellers· integer · optionnel
Active sellers in the period.buyers_period_1· integer · optionnel
Distinct buyers in the base period.
Exemple d'appel{"name": "valuation_marketplace", "arguments": {"method": "take_rate"}}Exemple de retour{"content": [{"type": "text", "text": "…"}], "structuredContent": {"error": "texte", "steps": [], "value": 1, "inputs": {}, "method": "texte", "chapter": "texte", "assumptions": [], "formula_number": "texte", "defaults_applied": []}} - valuation_probability≈ 1144 tokens
Compute expected value and probability-weighted outcomes for startup scenarios: discrete E[X], joint probability of sequential events, probability-weighted value, VC portfolio expected return, Poisson event probability, and continuous E[X] over a range. Method selects the formula. Use for probability-weighted central estimates; for named bull/base/bear tables or option pricing use valuation_advanced, and to discount cash flows use valuation_time_value. Parameters apply per method: expected_value_discrete and probability_weighted need outcomes + probabilities; portfolio_return needs weights + returns; poisson needs mean_events + k; expected_value_continuous needs lower + upper. outcomes and probabilities must be equal length, and the probabilities should sum to 1. Routing: use valuation_advanced method 'scenario_analysis' for named bull/base/bear scenario tables, and its black_scholes/binomial methods for option pricing; use this tool for arbitrary outcome lists and probability-weighted central estimates. Only method is required; all other parameters are method-dependent, so supply those the selected method names and omit the rest (defaults apply where defined). Rate and decimal inputs are fractions (0.10 = 10%); probability and weight lists are in [0,1] and sum to 1. Returns value, method, inputs, assumptions, chapter, formula_number and calculation steps; pure arithmetic — no I/O and no external calls — rounded to 2 decimals, with no auth or rate limits. An unknown method, or a missing method-required parameter, returns an error instead of a value.
Paramètres, retour & exemple (9)
Paramètresk· integer · optionnel
Number of events k for the Poisson probability P(X=k); integer ≥ 0.lower· number · optionnel
Lower integration bound (standard-normal domain, e.g. -1.0).upper· number · optionnel
Upper integration bound (standard-normal domain, e.g. 1.0).method· string · requis · expected_value_discrete | joint_probability | probability_weighted | portfolio_return | poisson | expected_value_continuous
Formula to apply. Options: expected_value_discrete = E[X] = Σ xᵢ·P(X=xᵢ) over a discrete outcome list.; joint_probability = P(total) = Π pᵢ for independent sequential events.; probability_weighted = E[V] = Σ pᵢ·Vᵢ.; portfolio_return = E[R] = Σ wᵢ·Rᵢ across a VC portfolio.; poisson = P(X=k) = e^-λ λ^k / k! for rare events.; expected_value_continuous = E[X] = ∫ x·f(x) dx over [lower, upper] on the standard normal.returns· array · optionnel
Return of each asset or scenario as a decimal (0.20 = 20%), aligned with weights.weights· array · optionnel
Portfolio or factor weights, each in [0,1] and summing to 1 (same order as the paired value list).outcomes· array · optionnel
Possible outcome values x_i, in any currency unit (must match probabilities in length/order).mean_events· number · optionnel
Poisson mean λ = expected number of events in the interval.probabilities· array · optionnel
Probability of each outcome or stage, each in [0,1]; the list must sum to 1 where it is exhaustive.
Exemple d'appel{"name": "valuation_probability", "arguments": {"method": "expected_value_discrete"}}Exemple de retour{"content": [{"type": "text", "text": "…"}], "structuredContent": {"error": "texte", "steps": [], "value": 1, "inputs": {}, "method": "texte", "chapter": "texte", "assumptions": [], "formula_number": "texte", "defaults_applied": []}} - valuation_saas≈ 1252 tokens
SaaS unit economics and valuation: LTV, CAC, MRR, ARR, net revenue retention, magic number, Rule of 40, CAC payback, and ARR revenue-multiple valuation. Method selects the metric. Use for subscription software; for marketplace GMV metrics use valuation_marketplace and for payments/lending use valuation_fintech. Parameters apply per method: ltv needs arpu + gross_margin + churn_rate; cac needs sales_marketing_expense + new_customers; arr needs subscription_values; nrr needs starting_revenue + ending_revenue; revenue_multiple needs arr + revenue_multiple. Not for company-level pre-revenue value — for that use valuation_core. Only method is required; all other parameters are method-dependent, so supply those the selected method names and omit the rest (defaults apply where defined). Rate and decimal inputs are fractions (0.10 = 10%); probability and weight lists are in [0,1] and sum to 1. Returns value, method, inputs, assumptions, chapter, formula_number and calculation steps; pure arithmetic — no I/O and no external calls — rounded to 2 decimals, with no auth or rate limits. An unknown method, or a missing method-required parameter, returns an error instead of a value.
Paramètres, retour & exemple (19)
Paramètresarr· number · optionnel
Annual recurring revenue, currency units.cac· number · optionnel
Customer acquisition cost per customer, currency units.arpu· number · optionnel
Average revenue per user per month, currency units.method· string · requis · ltv | cac | mrr | arr | nrr | magic_number | rule_of_40 | cac_payback
Formula to apply. Options: ltv = LTV = ARPU × gross margin / churn.; cac = CAC = S&M expense / new customers.; mrr = MRR = ARR / 12 (reverse of ARR).; arr = ARR = Σ monthly subscriptions × 12.; nrr = NRR = (start + expansion) / start, net of churn.; magic_number = Magic Number = net new ARR / prior-quarter S&M.; rule_of_40 = Score = growth rate + profit margin.; cac_payback = Months to recover CAC from gross profit.; revenue_multiple = Valuation = ARR × multiple.arr_value· number · optionnel
Annual recurring revenue, currency units.churn_rate· number · optionnel
Periodic churn rate as a decimal (0.02 = 2% per month).growth_rate· number · optionnel
Revenue growth rate as a decimal (0.40 = 40%).net_new_arr· number · optionnel
Net new ARR added in the period, currency units.gross_margin· number · optionnel
Gross margin as a decimal (0.80 = 80%).new_customers· integer · optionnel
Number of customers acquired in the period.profit_margin· number · optionnel
Profit margin as a decimal (0.15 = 15%).ending_revenue· number · optionnel
Revenue from the same cohort at period end, currency units.mrr_per_customer· number · optionnel
Monthly recurring revenue per customer, currency units.revenue_multiple· number · optionnel
SaaS revenue multiple (e.g. 8 for 8x ARR).sm_expense_prior· number · optionnel
Sales & marketing expense in the prior period, currency units.starting_revenue· number · optionnel
Revenue from the cohort at period start, currency units.expansion_revenue· number · optionnel
Expansion revenue from the cohort in the period.subscription_values· array · optionnel
Monthly subscription revenue per customer (summed x12 for ARR).sales_marketing_expense· number · optionnel
Sales & marketing spend for the period, currency units.
Exemple d'appel{"name": "valuation_saas", "arguments": {"method": "ltv"}}Exemple de retour{"content": [{"type": "text", "text": "…"}], "structuredContent": {"error": "texte", "steps": [], "value": 1, "inputs": {}, "method": "texte", "chapter": "texte", "assumptions": [], "formula_number": "texte", "defaults_applied": []}} - valuation_stakeholder≈ 1750 tokens
Allocate value across stakeholders and equity classes: single-round dilution, OPM common stock, PWERM, liquidation value, M&A synergy, employee-option values, vesting adjustment, cash-vs-equity break-even, and asset-based loan capacity. Method selects the model. Use only after the company-level value is known (from valuation_core, valuation_saas, or valuation_comparables) to split that value across the cap table; for the company value itself do not use this tool. Parameters apply per method: dilution needs ownership_before + investment + post_money; opm needs enterprise_value + liquidation_pref + time_to_exit + volatility; pwerm and employee_option need scenarios; liquidation needs assets + recovery_rates; risk_adjusted_synergy needs revenue_synergies + cost_synergies; vesting_adjusted needs total_value + vested_fraction; max_asset_loan takes collateral values. Only method is required; all other parameters are method-dependent, so supply those the selected method names and omit the rest (defaults apply where defined). Rate and decimal inputs are fractions (0.10 = 10%); probability and weight lists are in [0,1] and sum to 1. Returns value, method, inputs, assumptions, chapter, formula_number and calculation steps; pure arithmetic — no I/O and no external calls — rounded to 2 decimals, with no auth or rate limits. An unknown method, or a missing method-required parameter, returns an error instead of a value.
Paramètres, retour & exemple (33)
Paramètrescash· number · optionnel
Cash and equivalents, currency units.years· integer · optionnel
Forecast horizon in years; integer ≥ 1.assets· object · optionnel
Map of asset name to book value, e.g. {"cash": 500000}.method· string · requis · dilution | opm | pwerm | liquidation | risk_adjusted_synergy | intrinsic_option | employee_option | vesting_adjusted
Formula to apply. Options: dilution = Ownership = before × (1 - investment / post-money).; opm = Option-pricing allocation of equity value to common shares.; pwerm = Probability-weighted expected return method across exit scenarios.; liquidation = V = Σ(asset × recovery rate).; risk_adjusted_synergy = Probability-weighted, discounted M&A revenue + cost synergies.; intrinsic_option = Intrinsic value = max(0, FMV - strike) × shares.; employee_option = Probability-weighted employee option value across scenarios.; vesting_adjusted = Option value adjusted for vesting schedule and retention probability.; cash_equity_breakeven = Break-even comparing salary reduction against discounted equity.; max_asset_loan = Borrowing capacity from asset collateral values.shares· integer · optionnel
Number of option shares.tax_rate· number · optionnel
Effective tax rate as a decimal in [0,1].equipment· number · optionnel
Equipment, currency units.inventory· number · optionnel
Inventory, currency units.prob_cost· number · optionnel
Probability of realising cost synergies, 0-1.scenarios· array · optionnel
Scenario objects: {name: str, probability: 0-1, value: currency}; probabilities should sum to 1.investment· number · optionnel
Amount invested, currency units.post_money· number · optionnel
Post-money valuation, currency units.volatility· number · optionnel
Annualised volatility σ as a decimal (0.80 = 80%).real_estate· number · optionnel
Real estate, currency units.total_value· number · optionnel
Total grant value, currency units.equity_value· number · optionnel
Value of equity offered, currency units.prob_revenue· number · optionnel
Probability of realising revenue synergies, 0-1.strike_price· number · optionnel
Option strike price, currency units.time_to_exit· number · optionnel
Expected time to exit / liquidity in years.discount_rate· number · optionnel
Discount rate as a decimal (0.12 = 12%).cost_synergies· number · optionnel
Cost synergy value, currency units.recovery_rates· object · optionnel
Map of asset name to recovery rate in [0,1], matching assets.retention_prob· number · optionnel
Probability the holder stays, 0-1.vested_fraction· number · optionnel
Fraction vested in [0,1].years_remaining· integer · optionnel
Years of vesting remaining.annual_vest_rate· number · optionnel
Annual vesting rate as a decimal.enterprise_value· number · optionnel
Enterprise value (market cap + net debt), currency units.liquidation_pref· number · optionnel
Liquidation preference amount, currency units.ownership_before· number · optionnel
Founder ownership before the round as a decimal (0.60 = 60%).salary_reduction· number · optionnel
Annual salary foregone for equity, currency units.fair_market_value· number · optionnel
Current fair market value per share, currency units.revenue_synergies· number · optionnel
Revenue synergy value, currency units.accounts_receivable· number · optionnel
Accounts receivable, currency units.
Exemple d'appel{"name": "valuation_stakeholder", "arguments": {"method": "dilution"}}Exemple de retour{"content": [{"type": "text", "text": "…"}], "structuredContent": {"error": "texte", "steps": [], "value": 1, "inputs": {}, "method": "texte", "chapter": "texte", "assumptions": [], "formula_number": "texte", "defaults_applied": []}} - valuation_time_value≈ 1106 tokens
Discount, compound, and forecast value over time: single future value PV, net present value of a cash-flow stream, annuity present value, discounted cash flow with a Gordon terminal value, constant-rate compound growth of revenue or cash flow, and the implied compound annual growth rate (CAGR). Method selects the formula. Use to convert future cash to today's value, to value a full forecast with a terminal value (dcf), to project a revenue or cash-flow series forward, or to derive the growth rate implied by two values; get the discount rate from valuation_capm or valuation_international. Parameters apply per method: present_value needs future_value + rate + periods; npv needs cash_flows + rate; annuity needs payment + rate + periods; dcf needs cash_flows + rate (optional: terminal_growth); compound_growth needs starting_value + growth_rate + periods; cagr needs starting_value + ending_value + periods. growth_rate must be greater than -1, cagr requires starting_value > 0 and periods > 0, and dcf requires rate greater than terminal_growth. Not for option values (use valuation_advanced) or for expected values over outcomes (use valuation_probability). Only method is required; all other parameters are method-dependent, so supply those the selected method names and omit the rest (defaults apply where defined). Rate and decimal inputs are fractions (0.10 = 10%); probability and weight lists are in [0,1] and sum to 1. Returns value, method, inputs, assumptions, chapter, formula_number and calculation steps; pure arithmetic — no I/O and no external calls — rounded to 2 decimals, with no auth or rate limits. An unknown method, or a missing method-required parameter, returns an error instead of a value.
Paramètres, retour & exemple (10)
Paramètresrate· number · optionnel
Per-period discount rate as a decimal (0.10 = 10%).method· string · requis · present_value | npv | annuity | compound_growth | cagr | dcf
Formula to apply. Options: present_value = PV = C / (1+r)^t.; npv = NPV = Σ Cₜ / (1+r)^t.; annuity = PV = P·[1-(1+r)^-n]/r.; compound_growth = V_n = V_0 (1+g)^n.; cagr = CAGR = (V_n / V_0)^(1/n) - 1.; dcf = DCF = Σ Cₜ/(1+r)^t + [C_n(1+g)/(r−g)]/(1+r)^n.payment· number · optionnel
Recurring payment per period, in currency units.periods· number · optionnel
Number of compounding periods, must be ≥ 1 (may be fractional).cash_flows· array · optionnel
Cash flows by period, first element at t=1; negatives allowed for outflows.growth_rate· number · optionnel
Revenue growth rate as a decimal (0.40 = 40%).ending_value· number · optionnel
Value at t=n to compare against the starting value, in currency units.future_value· number · optionnel
Future cash amount to discount, in currency units.starting_value· number · optionnel
Value at t=0 (revenue or cash flow) to grow forward, in currency units.terminal_growth· number · optionnel
Perpetual growth rate g applied after the forecast window, as a decimal.
Exemple d'appel{"name": "valuation_time_value", "arguments": {"method": "present_value"}}Exemple de retour{"content": [{"type": "text", "text": "…"}], "structuredContent": {"error": "texte", "steps": [], "value": 1, "inputs": {}, "method": "texte", "chapter": "texte", "assumptions": [], "formula_number": "texte", "defaults_applied": []}}
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