Fair Value MCP Server

com.ascent-partners由 ascent-partners.com 发布官方发布者v0.2.7更新于 Oct 24, 2026

Valuation MCP: DCF/NAV/CCA, WACC, derivatives, credit risk, fixed income, structured products.

发布方自己的服务:Coso Mcp

已验证Streamable HTTP可网页运行金融数据与分析

概览

AI 生成的概览

金融估值 MCP 服务器,提供 14 个 calculate_* 工具,涵盖 DCF、WACC、期权、信用风险、精算与结构性产品,并附 IFRS/IVS 条款引用。

可以做什么
  • 估值企业与现金流:DCF、剩余收益、市场倍数、亏损企业方法、行业指标
  • 推导折现率:WACC、CAPM 股权成本、贝塔去杠杆/再杠杆、国家与规模溢价
  • 定价金融工具:期权与权证及希腊值、固定收益与期限结构曲线、可转债、结构性产品
  • 计量信用与精算项目:IFRS 9 预期信用损失、PD/LGD/EAD、CVA/DVA、精算现值、IFRS 13 公允价值调整
  • 执行 IFRS/HKFRS 计量:商誉与购买价格分摊、减值、瀑布分配、股权结构表、分部加总
  • 返回含中心值、统计量与准则引用的结果封装;加 help=true 可获取透明度记录
适用场景
适合需要按准则执行估值工作的场景,例如企业估值、初创公司估值、减值测试、信用拨备或衍生品定价,且希望得到可复现并附 IVS/IFRS 条款引用的数值,而非自由生成的估算。
运行要求
可使用托管的 Streamable HTTP 端点,或在本地以 Python 3.10+ 通过 uvx 或带 mcp 扩展的 pip 包运行;依赖包括 pandas、numpy、scipy 与 fastmcp,QuantLib 与 OCR 库为可选。未声明任何认证、API 密钥或环境变量。
安装前请注意
输出为计算结果而非投资建议,结果封装中带有免责声明。输入由调用方提供,准确性取决于用户假设。托管端点会接收你发送的财务数据,涉及机密交易数据前应先确认其数据处理方式。未要求任何凭据。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Fair Value MCP Server,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/com.ascent-partners%2Ffair-value/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "mcpServers": {
    "fair-value": {
      "type": "http",
      "url": "https://fair-value.ascent-partners.com/mcp"
    }
  }
}

README

Fair Value

[PyPI] [CI] [License: MIT] [MCP Registry] [TDQS]

Professional financial valuation system for OpenCode with IFRS/IVS compliance.

mcp-name: com.ascent-partners/fair-value

Overview

A single valuation core — exposed as an MCP server, a REST API, and a Python library — whose 14 native calculate_* tools / 135 methods cover corporate, startup, and intangible valuation aligned to IVS 2025 and IFRS/IAS:

  • DCF / NAV / CCA / residual income, market multiples, cost of capital (WACC, Fama-French 5-Factor, build-up)
  • Options, fixed income (term-structure curves), convertible bonds, structured products
  • IFRS 9 / HKFRS 9 credit risk (ECL, PD/LGD, CVA/DVA), actuarial PV (IFRS 17, IAS 19, IAS 37)
  • Fair-value adjustments (IFRS 13), expected value, and loss-making-company methods

Every result is a deterministic-first envelope carrying the centre value, solution_type, statistics (σ / percentiles, and seeded samples for the few stochastic methods), and citations resolving to verbatim IVS/IFRS clauses. 120 / 135 methods carry standards citations and the taxonomy has 0 orphan clauses, enforced by a conformance gate in CI.

Quick start (≤ 5 minutes)

Fastest path — no install:

  • Hosted MCP (Streamable HTTP): https://fair-value.ascent-partners.com/mcp
  • Hosted REST: https://fair-value.ascent-partners.com/v1/health
  • Frontage & docs: https://fair-value.ascent-partners.com/
  • Run locally, no install: uvx --from "fair-value[mcp]" fair-value-mcp

Then call any of the 14 calculate_* tools (add -help / help=true for the generated transparency record). Client config: MCP Server.

Architecture

mermaid
flowchart LR  CLIENT["AI agent / OpenCode"] -->|"stdio (uvx) or Streamable HTTP"| MCP["fair-value-mcp<br/>14 calculate_* tools · 135 methods"]  HOST["Hosted · fair-value.ascent-partners.com<br/>docs/landing at / · MCP at /mcp · REST at /v1"] --> CLIENT  MCP --> REG["method-spec registry<br/>(valuation://methods)"]  REG --> STD["standards taxonomy + corpus<br/>IVS 2025 · IFRS/IAS · (valuation://standards)"]  REG --> CORE["valuation engine<br/>DCF · NAV · CCA · WACC (FF5) · derivatives<br/>credit risk · actuarial"]  CORE --> DATA["inputs from apdb-etl (cited)"]  CORE --> ENV["result envelope<br/>value + statistics + citations"]

Installation

bash
pip install -r requirements.txt   # dev workflow# or, as a package:pip install .                     # base librarypip install ".[mcp]"              # + MCP server dependencies (fastmcp)

The console command fair-value-mcp runs the MCP server (stdio; add --http for Streamable HTTP).

MCP Server

bash
# run locally without installing (stdio)uvx --from "fair-value[mcp]" fair-value-mcp
# or install and runpip install "fair-value[mcp]"fair-value-mcp            # stdiofair-value-mcp --http     # Streamable HTTP

The server exposes 14 native calculate_* tools spanning DCF, cost of capital, market multiples, residual/asset valuation, options, expected value, credit risk, actuarial PV, sector metrics, fair-value adjustments, convertible bonds, structured products, loss-making companies, and fixed income — all derived from one method-spec registry. Add -help to any tool (or help=true) for its generated documentation with formula reference, inputs, and governing clauses.

Adoption target: ≥ 100 PyPI downloads and ≥ 1 directory listing within 90 days of the first release (tracked via the PyPI stats API and the directory listing).

REST API

The same core is exposed at /v1 (served next to MCP by mcp_server.asgi:app):

bash
curl -s localhost:8000/v1/healthcurl -s -X POST localhost:8000/v1/calculate/calculate_dcf \  -H 'content-type: application/json' \  -d '{"method":"dcf","cash_flows":[100,110],"discount_rate":0.1}'

Endpoints: /v1/health, /v1/tools, /v1/methods, /v1/standards, /v1/openapi.json, /v1/docs (Swagger UI), /v1/help/{tool}, POST /v1/calculate/{tool}. See REST API.

Web frontage (Next.js)

The hosted domain serves a Next.js frontage — landing, complete docs, methods catalogue (one page per method), standards browser, and an API playground — alongside the MCP/REST function in one Vercel project. It is data-driven: the catalogue is generated from the registry at build time (scripts/gen_web_data.py → data/catalog.json).

bash
pnpm installpnpm dev          # http://localhost:3000  (expects /v1 from the API for the playground)pnpm build        # prebuild regenerates data/catalog.jsonpnpm typecheck && pnpm lint

Routing: / and /docs/* are Next.js; /mcp and /v1/* are rewritten to the Python function (api/index.py). The frontage is localized — en at /, zh at /zh, hk at /hk — via per-locale root layouts with hreflang.

Quick Start (Python)

python
from valuation_engine import run_valuation
result = run_valuation('9988.HK', 'dcf')  # DCF valuation (shared envelope)

Standards & citations

The standards alignment is data, not code: standards/taxonomy.json maps each method to its IVS and IFRS/IAS clauses, standards/source/*.md holds the verbatim clause text (with standards/provenance.json recording edition and source), and standards/coverage-baseline.json is the coverage ratchet. The engine attaches solution_type and citations to every envelope, and scripts/check_conformance.py fails CI if a published method loses its citation or the taxonomy/corpus drifts. See Standards reference.

Module structure

mermaid
flowchart LR  SEED["method_spec_seed.py<br/>method tables · 135 methods"] --> SPEC["method_spec.py<br/>parameter vocabulary"]  SPEC --> SURF["tool_surface.py<br/>15 calculate_* tools"]  SPEC --> STD["standards.py<br/>taxonomy · citations"]  SURF --> SRV["server.py (FastMCP)"]  SRV --> STDIO["stdio · uvx fair-value-mcp"]  SRV --> HTTP["Streamable HTTP · fair-value-mcp --http"]  ASGI["asgi.py (+ rest.py, openapi.py)"] --> HOST["Hosted · / + /v1"]  SRV --> DOCS["docs.py<br/>-help transparency records"]  STD -.->|resources| RES["valuation://methods · valuation://standards"]  SRV -.-> DOCS
src/├── constants.py            # standards references├── valuation/              # DCF, NAV, CCA, asset standards (relief-from-royalty, MPEEM, residual)├── cost_of_capital/        # WACC, FF5, KMV├── credit_risk/            # ECL, PD/LGD, CVA/DVA├── derivatives/            # options, swaps, convertible bonds, structured products, fixed income└── output/                 # shared result envelope (value + statistics + citations)mcp_server/├── method_spec.py + method_spec_seed.py   # single source of truth for tools/methods├── standards.py                           # taxonomy loader, citations, coverage├── tool_surface.py · engine.py · handlers.py · server.py├── docs.py · rest.py · openapi.py · asgi.py└── catalog.py · prompts.py                # valuation:// resources + guided promptsstandards/                                 # taxonomy.json · source/*.md · provenance · baselinescripts/                                   # check_conformance.py · gen_docs.py

Request lifecycle

mermaid
sequenceDiagram    autonumber    participant C as MCP / REST / Python caller    participant E as validation + dispatch    participant R as method-spec registry    participant S as standards taxonomy    participant M as computation modules (src/)    participant O as output envelope    C->>E: calculate_*(...) / POST /v1/calculate/*    E->>R: resolve method + validate parameters (no defaults)    R-->>E: method spec    E->>M: dispatch to valuation / cost_of_capital / credit_risk / derivatives    E->>S: attach solution_type + citations    M-->>E: value + steps + assumptions    E->>O: ok() / error() envelope (value · statistics · citations)    O-->>C: status · method · value · statistics · assumptions · citations · disclaimer

Development

CI and deployment run through the APG workbench pipeline.

Requirements

  • Python 3.10+
  • pandas, numpy, scipy, python-dateutil
  • fastmcp (MCP extra), openpyxl, pdfplumber, python-docx
  • QuantLib, pandas_datareader, pytesseract/easyocr (all optional, with native fallbacks)

Documentation

Standards compliance

  • IVS 2025 — International Valuation Standards (103, 105, 210, 220, 230, 300, 400, 410, 500)
  • IFRS 13 Fair Value Measurement; IFRS 9 Financial Instruments; IFRS 16 Leases; IFRS 17 Insurance Contracts
  • IAS 36 Impairment of Assets; IAS 19 Employee Benefits; IAS 37 Provisions, Contingent Liabilities and Contingent Assets

License

Released under the MIT License.

来源:README.md,提交 81fcb6a

工具

14

calculate_actuarial_pv

Actuarial present value

Actuarial present value engine. Discount expected cash flows with mortality, survival, and risk adjustment for insurance and benefit obligations, generalising IFRS 17 (fulfilment cash flows), IAS 19 (employee benefits), IFRS 2 (share-based payments), and IAS 37 (provisions). Use this for regulated IFRS/HKFRS obligations only; it does NOT do generic project or scenario probability weighting (use calculate_expected_value). Methods: ifrs17_gmm: cash_flows, discount_rate, risk_adjustment; ifrs17_paa: premiums, claims_cash, acquisition_cash_flows, coverage_periods; ifrs17_vfa: cash_flows, discount_rate, underlying_items_return, risk_adjustment; ias19_puc: projected_benefits, discount_rate, attribution_years; ias37_provision: outcomes, probabilities, discount_rate, periods. Supply exactly one method with its declared inputs (no defaults). An unknown method, a missing input, or an extra field returns an error envelope (code INVALID_ARGUMENT) instead of raising.

输入参数method必填periodsoutcomespremiumscash_flowsclaims_cashdiscount_rateprobabilitiesrisk_adjustmentcoverage_periodsattribution_yearsprojected_benefits另有 2 个

calculate_convertible_bond

Convertible and exchangeable bond valuation

Convertible-bond engine. Value callable and puttable convertible or exchangeable bonds with credit risk using a Tsiveriotis-Fernandes lattice (equity discounted at the risk-free rate, debt at a credit spread), with conversion, issuer call, holder put, coupon schedule, and a straight-bond floor. Use this for convertible and exchangeable bonds; for a plain bond or rate curve use calculate_fixed_income, and for a standalone option or warrant use calculate_option. The lattice_tsf, lattice_intensity, finite_difference, lsmc and quantlib methods are alternative numerical schemes for the same valuation and take identical inputs (Tsiveriotis-Fernandes is the reference, lsmc is Monte Carlo, quantlib needs the optional engine); choose one. Methods: lattice_tsf/lattice_intensity/finite_difference/lsmc/quantlib: spot, face, coupon_rate, maturity, conversion_ratio, volatility, risk_free, credit_spread, call_schedule, put_schedule, rights_priority. Supply exactly one method with its declared inputs (no defaults). An unknown method, a missing input, or an extra field returns an error envelope (code INVALID_ARGUMENT) instead of raising.

输入参数facespotmethod必填maturityrisk_freevolatilitycoupon_rateput_schedulecall_schedulecredit_spreadrights_priorityconversion_ratio

calculate_credit_loss

Credit loss and impairment

Credit-risk engine (IFRS 9 / HKFRS 9). Compute 12-month, lifetime, and staged expected credit loss, PD/LGD/EAD, provision matrices, hazard rates, and CVA/DVA. Use this for impairment, fair-value credit adjustment, and loan-loss provisioning; for the credit component of a specific convertible bond use calculate_convertible_bond, and for liquidity, control or marketability discounts rather than credit loss use calculate_fair_value_adjustment. Methods: ecl_12m: ead, pd, lgd; ecl_lifetime: ead, pd_lifetime, lgd; ecl_staged: ead, pd_12m, pd_lifetime, lgd, stage; provision_matrix: receivables_ageing, loss_rates; pd_from_spread: credit_spread, recovery, tenor_years; cumulative_pd: annual_pd, years; hazard: hazard_rate, tenor_years; cva_dva: exposure_profile, pd, lgd, discount_rate. Supply exactly one method with its declared inputs (no defaults). An unknown method, a missing input, or an extra field returns an error envelope (code INVALID_ARGUMENT) instead of raising.

输入参数pdeadlgdstageyearsmethod必填pd_12mrecoveryannual_pdloss_rateshazard_ratepd_lifetime另有 5 个

calculate_dcf

Discounted cash flow valuation

Discounted cash flow valuation engine. Choose a method and supply its exact inputs to value a business from projected free cash flows, dividends, residual income, or economic profit. Covers FCFF/FCFE DCF, NPV/IRR, terminal values, and multi-stage growth. Use this for going-concern cash-flow businesses; for asset-anchored or financial firms use calculate_residual, for peer-based pricing use calculate_market_multiple, and for pre-profit companies use calculate_loss_making_company. Methods: dcf/npv: cash_flows, discount_rate; annuity: payment, discount_rate, periods; growing_annuity: payment, discount_rate, growth_rate, periods; perpetuity: payment, discount_rate; terminal_gordon: final_cash_flow, discount_rate, perpetual_growth; terminal_multiple: final_cash_flow, exit_multiple; viu_pre_tax: cash_flows, pre_tax_discount_rate; rnpv: cash_flows, discount_rate, probabilities; lease_pv: lease_payments, incremental_borrowing_rate. Supply exactly one method with its declared inputs (no defaults). An unknown method, a missing input, or an extra field returns an error envelope (code INVALID_ARGUMENT) instead of raising.

输入参数method必填paymentperiodscash_flowsgrowth_ratediscount_rateexit_multipleprobabilitieslease_paymentsfinal_cash_flowperpetual_growthpre_tax_discount_rate另有 1 个

calculate_discount_rate

Cost of capital and discount rates

Cost-of-capital engine. Compute WACC, cost of equity (CAPM), cost of debt, unlevered/relevered beta, and country or size premiums from an explicit capital structure and market inputs. Use this to derive the discount rate an income-approach valuation needs; it returns a rate, not a valuation, so feed the result to calculate_dcf, or to calculate_residual for IFRS-basis measurement. Methods: wacc: equity_weight, debt_weight, cost_equity, cost_debt, tax_rate; capm: risk_free, beta, market_return; startup_capm: risk_free, beta, market_risk_premium, size_premium, illiquidity_premium; build_up: risk_free, equity_risk_premium, size_premium, industry_premium, specific_premium; currency_adjusted: base_rate, currency_risk_premium, country_risk_premium; country_risk: sovereign_yield, us_risk_free; esg: base_rate, esg_risk_premium, esg_opportunity_discount; portfolio_beta: weights, betas; ibr: risk_free, credit_spread, tenor_years. Supply exactly one method with its declared inputs (no defaults). An unknown method, a missing input, or an extra field returns an error envelope (code INVALID_ARGUMENT) instead of raising.

输入参数betabetasmethod必填weightstax_ratebase_ratecost_debtrisk_freecost_equitydebt_weighttenor_yearssize_premium另有 14 个

calculate_expected_value

Expected value and probability weighting

Expected-value engine. Compute expected values over discrete, continuous, simulated, or tree-structured uncertainty, plus football-field ranges. Use this for generic probability weighting of scenarios, Monte-Carlo and decision trees; it does NOT perform IFRS/HKFRS measurement of provisions, insurance or employee-benefit obligations (use calculate_actuarial_pv), and it does not price path-dependent payoffs (use calculate_structured_product). Methods: discrete: outcomes, probabilities; continuous: distribution, mean, std, lower, upper; scenario: scenarios; monte_carlo: iterations, distributions, base_params, seed; decision_tree: tree; football_field: estimates. Supply exactly one method with its declared inputs (no defaults). An unknown method, a missing input, or an extra field returns an error envelope (code INVALID_ARGUMENT) instead of raising.

输入参数stdmeanseedtreeloweruppermethod必填outcomesestimatesscenariositerationsbase_params另有 3 个

calculate_fair_value_adjustment

Fair value adjustments (IFRS 13)

Fair-value-adjustment engine (IFRS 13). Compute exit-price adjustments including credit, liquidity, control and marketability discounts, blockage, and the fair-value hierarchy level. Use this to move from an indicated value to the fair value recognised in the accounts; for liquidity/marketability inputs of a listed instrument prefer calculate_market_multiple, and for expected credit loss use calculate_credit_loss. Methods: dlom: base_value, restricted_period, volatility, risk_free; dloc: base_value, transaction_cost_pct; control_premium: base_value, control_premium_pct; minority_discount: base_value, minority_discount_pct; highest_best_use: base_value, alternative_use_values; hierarchy_level: inputs. Supply exactly one method with its declared inputs (no defaults). An unknown method, a missing input, or an extra field returns an error envelope (code INVALID_ARGUMENT) instead of raising.

输入参数inputsmethod必填risk_freebase_valuevolatilityrestricted_periodcontrol_premium_pcttransaction_cost_pctminority_discount_pctalternative_use_values

calculate_fixed_income

Fixed income and term structure analytics

Fixed-income engine. Price plain coupon bonds, solve for yield to maturity, measure interest-rate sensitivity via Macaulay and modified duration and convexity, and build a HIBOR/HKD-style term structure: bootstrap a zero curve from par rates, infer forward rates, and discount cash flows on the curve. Use this for vanilla bonds, rate risk and discount curves; for convertibles use calculate_convertible_bond and for structured payoffs use calculate_structured_product. Methods: bond_price/duration/convexity: face, coupon_rate, years, ytm, frequency; bond_yield: face, coupon_rate, years, price, frequency; matrix_pricing: target_tenor, benchmark_tenors, benchmark_yields; discount_factor: rate, years, frequency; zero_curve: par_rates, tenors, frequency; forward_rate: zero_rates, tenors, t1, t2; pv_curve: cash_flows, times, zero_rates, tenors. Supply exactly one method with its declared inputs (no defaults). An unknown method, a missing input, or an extra field returns an error envelope (code INVALID_ARGUMENT) instead of raising.

输入参数t1t2ytmfaceratepricetimesyearsmethod必填tenorsfrequencypar_rates另有 6 个

calculate_loss_making_company

Loss-making and pre-profit company valuation

Loss-making-company engine. Value currently unprofitable companies with margin-ramp DCF, revenue multiples, Merton structural equity, the VC method, distressed waterfalls, bank residual income, and SPAC deals; every method returns a central value plus a dispersion (sigma, percentiles, long-tail). Use this when earnings-based multiples break down; for standalone probability weighting of arbitrary scenarios use calculate_expected_value, and for a single going-concern DCF use calculate_dcf. Methods: margin_ramp_dcf: revenue, growth_rate, start_margin, target_margin, ramp_years, discount_rate, years, shares_outstanding, net_debt, range_method; revenue_multiple: revenue, ev_revenue_multiple, net_debt, shares_outstanding, range_method; merton_equity: firm_value, firm_volatility, debt, risk_free, maturity, range_method; vc_method: terminal_value, target_return, investment, shares_outstanding, range_method; distressed_waterfall: enterprise_value, claims, range_method; bank_residual_income: book_value, net_income, cost_equity, growth_rate, range_method; spac_deal: trust_cash, shares_outstanding, redemption_price, range_method. Supply exactly one method with its declared inputs (no defaults). An unknown method, a missing input, or an extra field returns an error envelope (code INVALID_ARGUMENT) instead of raising.

输入参数debtyearsclaimsmethod必填revenuematuritynet_debtrisk_freebook_valuefirm_valueinvestmentnet_income另有 15 个

calculate_market_multiple

Market multiples and comparable pricing

Market-multiple engine. Apply peer multiples (P/E, P/B, EV/EBITDA, EV/Sales, PEG and more) or derive implied multiples to price a company on a comparable basis. Use this for market-approach pricing where peers exist; it does peer multiples only — for intrinsic cash-flow value use calculate_dcf, and for residual-income or IFRS-basis measurement use calculate_residual. Methods: ev_revenue: revenue, ev_revenue_multiple; ev_ebitda: ebitda, ev_ebitda_multiple; ev_arr: arr, ev_arr_multiple; ev_gmv: gmv, ev_gmv_multiple; pe: eps, pe_multiple; pb: book_value_per_share, pb_multiple; ps: sales_per_share, ps_multiple; cap_rate: net_operating_income, cap_rate; regression: intercept, growth_rate, growth_coefficient, market_maturity, maturity_coefficient; royalty_cap: revenue, royalty_rate, discount_rate; ddm: dividend_per_share, cost_equity, growth_rate. Supply exactly one method with its declared inputs (no defaults). An unknown method, a missing input, or an extra field returns an error envelope (code INVALID_ARGUMENT) instead of raising.

输入参数arrepsgmvebitdamethod必填revenuecap_rateinterceptcost_equitygrowth_ratepb_multiplepe_multiple另有 14 个

calculate_option

Option and warrant pricing

Option-pricing engine. Price European and American options and warrants (Black-Scholes, Black-76, CRR binomial, Garman-Kohlhagen FX, digital, range, share-based) and their greeks. Use this for a single contingent claim or warrant on one underlying; it does NOT price listed structured payoffs such as CBBCs, inline/derivative warrants or autocallables (use calculate_structured_product). Methods: black_scholes: spot, strike, maturity, risk_free, volatility, option_type; black76: forward, strike, maturity, risk_free, volatility, option_type; binomial_american: spot, strike, maturity, risk_free, volatility, option_type, steps; garman_kohlhagen: spot, strike, maturity, domestic_rate, foreign_rate, volatility, option_type; barrier_first_passage: spot, strike, maturity, risk_free, volatility, option_type, barrier, barrier_type; asian_average: spot, strike, maturity, risk_free, volatility, option_type, average_type; digital: spot, strike, maturity, risk_free, volatility, cash_payout; range: spot, lower_strike, upper_strike, maturity, risk_free, volatility, payout; share_based: share_price, exercise_price, expected_life, volatility, risk_free, dividend_yield. Supply exactly one method with its declared inputs (no defaults). An unknown method, a missing input, or an extra field returns an error envelope (code INVALID_ARGUMENT) instead of raising.

输入参数spotstepsmethod必填payoutstrikebarrierforwardmaturityrisk_freevolatilitycash_payoutoption_type另有 10 个

calculate_residual

IFRS measurement, residual income and non-financial fair value

IFRS/HKFRS measurement engine. Compute goodwill and purchase-price allocation, impairment (IAS 36), inventory net realisable value, held-for-sale, debt waterfalls, cap tables, sum-of-the-parts and SPAC redemption; residual income and justified price-to-book; and non-financial asset fair value: investment property (IAS 40 / HKAS 40), PP&E revaluation via depreciated replacement cost (IAS 16) and biological assets at fair value less costs to sell (IAS 41). Use this for accounting-basis measurement of assets and equity; for going-concern cash flow use calculate_dcf and for peer multiples use calculate_market_multiple. Methods: goodwill: purchase_price, fair_value_net_identifiable_assets; ppa: purchase_price, tangible_assets_fv, identified_intangibles_fv; impairment_fvlcd: carrying_value, fair_value_less_costs_to_dispose; impairment_viu: carrying_value, value_in_use; inventory_nrv: carrying_value, net_realisable_value; held_for_sale: carrying_value, fair_value_less_costs_to_sell; debt_waterfall/cap_table: enterprise_value, claims; sotp: segments, net_debt, holding_discount; spac_redemption: trust_cash, shares_outstanding, redemption_price; investment_property: noi, cap_rate; ppe_revaluation: replacement_cost, accumulated_depreciation; biological_asset: expected_price, quantity, costs_to_sell; residual_income: book_value, net_income, cost_equity; justified_pb: roe, cost_equity, growth_rate; relief_from_royalty: revenue, royalty_rate, discount_rate, periods; mpeem: cash_flows, contributory_charges, discount_rate; with_without: with_cash_flows, without_cash_flows, discount_rate; recoverable_amount: fair_value_less_costs_to_dispose, value_in_use; liability_fulfilment: fulfilment_costs, mark_up, discount_rate; inventory_residual: selling_price, costs_to_complete, profit_allowance; development_residual: gross_development_value, development_costs, developer_profit. Supply exactly one method with its declared inputs (no defaults). An unknown method, a missing input, or an extra

输入参数noiroeclaimsmethod必填mark_upperiodsrevenuecap_ratenet_debtquantitysegmentsbook_value另有 34 个

calculate_sector_metrics

Sector-specific operating metrics

Sector-metric engine. Compute the metrics that anchor valuation in specific industries: SaaS (ARR, NRR, magic number, Rule of 40), marketplaces (take rate, GMV multiple), lending (LTV/CAC), and crypto (NVT, Metcalfe). It returns operating metrics, not a valuation; use them as inputs to calculate_market_multiple or calculate_dcf. Methods: ltv: arpu, gross_margin, churn_rate; cac: sales_marketing_expense, new_customers; arr: subscription_values; nrr: starting_revenue, ending_revenue, expansion_revenue; magic_number: net_new_arr, sales_marketing_expense_prior; rule_of_40: growth_rate, profit_margin; take_rate: revenue, gmv; gmv_multiple: gmv, ev_gmv_multiple; retention: retained_customers, starting_customers; trl: market_size, market_share, margin, exit_multiple, trl_discount; break_even: fixed_costs, asp, variable_cost; gross_margin: asp, variable_cost; token: transaction_volume, price_per_tx, velocity, supply; nvt: market_cap, transaction_volume; metcalfe: n, coefficient. Supply exactly one method with its declared inputs (no defaults). An unknown method, a missing input, or an extra field returns an error envelope (code INVALID_ARGUMENT) instead of raising.

输入参数naspgmvarpumarginmethod必填supplyrevenuevelocitychurn_ratemarket_capcoefficient另有 22 个

calculate_structured_product

Structured product and derivative pricing

Structured-product engine. Value HKEX-listed and OTC structures: CBBCs, derivative and inline warrants, equity-linked notes and investments, autocallables, accumulators and decumulators, credit-linked notes, TRS, and CFDs. Use this for equity-linked and credit-linked payoff structures; for a plain option or warrant use calculate_option, for a convertible or exchangeable bond use calculate_convertible_bond, and for a vanilla bond or term structure use calculate_fixed_income. Methods: cbbc: notional, spot, strike, barrier, barrier_type, maturity, risk_free, volatility, option_type; cbbc_residual: notional, spot, call_price, entitlement, barrier, barrier_type, maturity, risk_free, volatility, option_type; derivative_warrant: notional, spot, strike, maturity, risk_free, volatility, average_type, option_type; inline_warrant: notional, spot, lower_strike, upper_strike, maturity, risk_free, volatility, payout; inline_warrant_avg: notional, spot, lower_strike, upper_strike, maturity, risk_free, volatility, payout, fixing_days; eli/eln: notional, spot, strike, maturity, risk_free, volatility, coupon_rate; autocallable: notional, spot, knock_out_level, observation_dates, coupon_rate_structured, maturity, risk_free, volatility; credit_linked_note: notional, credit_spread, recovery, maturity, risk_free, coupon_rate_structured; accumulator/decumulator: notional, spot, strike, knock_out_level, observation_dates, risk_free, volatility; trs: notional, spot, maturity, risk_free, dividend_yield; cfd: notional, spot, strike, maturity, risk_free. Supply exactly one method with its declared inputs (no defaults). An unknown method, a missing input, or an extra field returns an error envelope (code INVALID_ARGUMENT) instead of raising.

输入参数spotmethod必填payoutstrikebarriermaturitynotionalrecoveryrisk_freecall_pricevolatilitycoupon_rate另有 12 个

版本历史

1
  1. v0.2.7最新Oct 14, 2026

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