Financial Modeling Copilot
Financial Modeling Copilot · GPT-Aktionen
Tailored DCF Generator
Based on given parameters, retrieves financial data and generate DCF Model with link and brief summary. Domain is https://www.financialmodeling.tech
POST /generate_dcf_excelGenerate DCF model and reply with link and brief summary of the model result.Generate DCF Excel data based on specified criteria.
POST /add_breakdownAdd breakdown based on existing DCF file.This endpoint validates breakdown data against specific criteria.
Ursprüngliches API-Schema
{
"openapi": "3.1.0",
"info": {
"title": "Tailored DCF Generator",
"description": "Based on given parameters, retrieves financial data and generate DCF Model with link and brief summary. Domain is https://www.financialmodeling.tech",
"version": "v1.0.0"
},
"servers": [
{
"url": "https://www.financialmodeling.tech"
}
],
"paths": {
"/generate_dcf_excel": {
"post": {
"summary": "Generate DCF model and reply with link and brief summary of the model result.",
"description": "Generate DCF Excel data based on specified criteria.",
"operationId": "GenerateDCFExcel",
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"type": "object",
"properties": {
"ticker": {
"type": "string",
"description": "The stock ticker symbol for the company to be analyzed. must input."
},
"historic_periods": {
"type": "integer",
"minimum": 2,
"description": "Optional, default 3. Number of past periods to include in the analysis, at least 2."
},
"estimated_periods": {
"type": "integer",
"minimum": 2,
"description": "Optional, default 5. Number of future periods to estimate in the analysis, at least 2."
}
},
"required": [
"ticker"
]
}
}
}
},
"responses": {
"200": {
"description": "A URL to download the Excel file",
"content": {
"text/plain": {
"schema": {
"type": "string"
}
}
}
}
}
}
},
"/add_breakdown": {
"post": {
"summary": "Add breakdown based on existing DCF file.",
"description": "This endpoint validates breakdown data against specific criteria.",
"operationId": "AddBreakdown",
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"type": "object",
"properties": {
"file_name": {
"type": "string",
"description": "Name of the file containing financial data."
},
"breakdowns": {
"oneOf": [
{
"type": "string",
"enum": [
"Revenue by Segment from DataBase"
]
},
{
"type": "array",
"description": "An array of breakdown objects.",
"items": {
"type": "object",
"properties": {
"target": {
"type": "string",
"description": "Target row name in the Financial Statements, such as [Revenue, CostOfRevenue, etc.]",
"example": "Revenue"
},
"function_between_elements": {
"type": "string",
"enum": [
"plus",
"multiply"
],
"description": "Function to be applied between elements in values."
},
"values": {
"type": "object",
"additionalProperties": {
"description": "key is timeframe, such as FY2023. value is a dictionary of elements and corresponding values.",
"type": "object",
"additionalProperties": {
"type": "number",
"description": "Value of the element. If the value is 100M, then the value should be 100000000."
}
},
"description": "Dictionary of time frames and corresponding values.",
"example": {
"target": "Revenue",
"function_between_elements": "plus",
"values": {
"FY2023": {
"Mac": 29357000000,
"Service": 85200000000,
"Wearables, Home and Accessories": 45000000,
"iPad": 28300000000,
"iPhone": 200583000000
},
"FY2022": {
"Mac": 40177000000,
"Service": 78129000000,
"Wearables, Home and Accessories": 41241000000,
"iPad": 29292000000,
"iPhone": 205489000000
}
}
}
}
}
}
}
]
}
},
"required": [
"file_name",
"breakdowns"
]
}
}
}
},
"responses": {
"200": {
"description": "A URL to download updated Excel file with breakdown",
"content": {
"text/plain": {
"schema": {
"type": "string"
}
}
}
}
}
}
}
}
}