python - 使用 Alpha Vantage API 计算投资回报率

Question

我正在尝试使用Alpha Vantage API计算投资资本回报率。谁能帮我验证下面的代码？

其他来源

我不确定我得到了正确的结果，因为我什至找不到 2 个股票分析网站来就这些值达成一致。

资源	2016 年	2017	2018	2019	2020
晨星：DAVA	35.34	27.77	23.38	18.70	8.77
MSN：达瓦					9.90
大师焦点：DAVA	28.57	26.01	20.76	23.07	11.86
规则 1 投资：DAVA	56.0	34.5	27.3	14.4	9.1
下面的算法结果（与其他结果有点远）	53.65	36.70	28.16	15.80	7.84

公式

ROIC = 税后净营业利润 /（总股本 + 总有息债务）

1. 计算 NOPAT（计算税率并乘以营业收入）
2. 计算投资资本
3. 计算投资回报率

Alpha Vantage 响应属性

获取资产负债表（来自 alpha vantage）。我从这里得到了“totalShareholderEquity”和“currentDebt”。

获取损益表。我计算了 NOPAT = "operatingIncome" * (1 - "incomeTaxExpense" / "incomeBeforeTax")

代码

import requests
import json
import pandas as pd

ALPHA_KEY = '________'
symbol = 'DAVA'

def request_function(func: str, symbol: str, key: str):
    url = f'https://www.alphavantage.co/query?function={func.upper()}&symbol={symbol.upper()}&apikey={key.upper()}'
    response = requests.request("GET", url)
    return response.json()

data_income_statement = request_function('income_statement', symbol, ALPHA_KEY)
data_balance_sheet = request_function('balance_sheet', symbol, ALPHA_KEY)

## Income statement
# tax rate = "incomeTaxExpense" / "incomeBeforeTax"
# NOPAT = "operatingIncome" * (1 - tax rate)
# NOPAT = "operatingIncome" * (1 - "incomeTaxExpense" / "incomeBeforeTax")

inc_stmt = pd.json_normalize(data_income_statement['annualReports'])

inc_stmt['operatingIncome'] = pd.to_numeric(inc_stmt['operatingIncome'], downcast="float")
inc_stmt['incomeTaxExpense'] = pd.to_numeric(inc_stmt['incomeTaxExpense'], downcast="float")
inc_stmt['incomeBeforeTax'] = pd.to_numeric(inc_stmt['incomeBeforeTax'], downcast="float")

inc_stmt['nopat'] = inc_stmt['operatingIncome'] * (1 - inc_stmt['incomeTaxExpense'] /  inc_stmt['incomeBeforeTax'])
inc_stmt['nopat'] = pd.to_numeric(inc_stmt['nopat'])


## Balance sheet 
# "interestAndDebtExpense" ? "currentDebt" ?
# "totalAssets" - "totalLiabilities"

bs = pd.json_normalize(data_balance_sheet['annualReports'])
# bs['equity'] = pd.to_numeric(bs['totalAssets']) - pd.to_numeric(bs['totalLiabilities'])
bs['equity'] = pd.to_numeric(bs['totalShareholderEquity'])
bs.replace('None', '0', inplace=True)
bs['currentDebt'] = pd.to_numeric(bs['currentDebt'])


df = pd.merge(bs, inc_stmt, on='fiscalDateEnding')
df['returnOnCapitalInvested'] = df['nopat'] / (df['equity'] - df['currentDebt'])

帮助

那么我的计算与现实相差多远？我尝试了在网上找到的不同公式，但由于我缺乏财务经验，我无法将它们与我从 Alpha Vantage 获得的值完美匹配。

标签： pythonalpha-vantage