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2548 Fundamentals E9ba2386
ASecurityReturns key company information, valuation metrics, and financial ratios.
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- Added October 11, 2026
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Security analysis
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[](https://www.skillsdirectory.com/skills/tools-only-2548-fundamentals-e9ba2386)# Fundamental Data APIs
## OVERVIEW — Company Overview
Returns key company information, valuation metrics, and financial ratios.
**Required:** `symbol`
```python
data = av_get("OVERVIEW", symbol="AAPL")
# Key fields returned:
# "Symbol", "AssetType", "Name", "Description", "Exchange", "Currency"
# "Country", "Sector", "Industry", "Address"
# "MarketCapitalization", "EBITDA", "PERatio", "PEGRatio"
# "BookValue", "DividendPerShare", "DividendYield", "EPS"
# "RevenuePerShareTTM", "ProfitMargin", "OperatingMarginTTM"
# "ReturnOnAssetsTTM", "ReturnOnEquityTTM"
# "RevenueTTM", "GrossProfitTTM", "DilutedEPSTTM"
# "QuarterlyEarningsGrowthYOY", "QuarterlyRevenueGrowthYOY"
# "AnalystTargetPrice", "AnalystRatingStrongBuy", "AnalystRatingBuy",
# "AnalystRatingHold", "AnalystRatingSell", "AnalystRatingStrongSell"
# "TrailingPE", "ForwardPE", "PriceToSalesRatioTTM"
# "PriceToBookRatio", "EVToRevenue", "EVToEBITDA"
# "Beta", "52WeekHigh", "52WeekLow", "50DayMovingAverage", "200DayMovingAverage"
# "SharesOutstanding", "DividendDate", "ExDividendDate", "FiscalYearEnd"
print(data["MarketCapitalization"]) # "2850000000000"
print(data["PERatio"]) # "29.50"
print(data["Sector"]) # "TECHNOLOGY"
```
## ETF_PROFILE — ETF Profile & Holdings
**Required:** `symbol`
```python
data = av_get("ETF_PROFILE", symbol="QQQ")
# Fields: "net_assets", "nav", "inception_date", "description",
# "asset_allocation" (stocks/bonds/cash/etc.)
# "sectors" (list of sector weights)
# "holdings" (top holdings list)
for h in data["holdings"][:5]:
print(h["symbol"], h["description"], h["weight"])
```
## DIVIDENDS — Corporate Dividend History
**Required:** `symbol`
```python
data = av_get("DIVIDENDS", symbol="IBM")
divs = data["data"]
for d in divs:
print(d["ex_dividend_date"], d["amount"])
# Fields per record: "ex_dividend_date", "declaration_date",
# "record_date", "payment_date", "amount"
```
## SPLITS — Stock Split History
**Required:** `symbol`
```python
data = av_get("SPLITS", symbol="AAPL")
splits = data["data"]
for s in splits:
print(s["effective_date"], s["split_factor"])
# Fields: "effective_date", "split_factor" (e.g., "4/1" for 4-for-1 split)
```
## INCOME_STATEMENT — Income Statement
Returns annual and quarterly income statements.
**Required:** `symbol`
```python
data = av_get("INCOME_STATEMENT", symbol="IBM")
annual = data["annualReports"] # list, most recent first
quarterly = data["quarterlyReports"] # list, most recent first
yr = annual[0] # Most recent fiscal year
print(yr["fiscalDateEnding"]) # "2023-12-31"
print(yr["totalRevenue"]) # "61860000000"
print(yr["grossProfit"]) # "32688000000"
print(yr["operatingIncome"]) # "..."
print(yr["netIncome"]) # "..."
print(yr["ebitda"]) # "..."
# Other keys: "reportedCurrency", "costOfRevenue", "costofGoodsAndServicesSold",
# "sellingGeneralAndAdministrative", "researchAndDevelopment",
# "operatingExpenses", "investmentIncomeNet", "netInterestIncome",
# "interestIncome", "interestExpense", "nonInterestIncome",
# "otherNonOperatingIncome", "depreciation",
# "depreciationAndAmortization", "incomeBeforeTax",
# "incomeTaxExpense", "interestAndDebtExpense",
# "netIncomeFromContinuingOperations", "comprehensiveIncomeNetOfTax",
# "ebit", "dilutedEPS", "basicEPS"
```
## BALANCE_SHEET — Balance Sheet
**Required:** `symbol`
```python
data = av_get("BALANCE_SHEET", symbol="IBM")
annual = data["annualReports"]
yr = annual[0]
print(yr["totalAssets"]) # "..."
print(yr["totalLiabilities"]) # "..."
print(yr["totalShareholderEquity"]) # "..."
# Other keys: "reportedCurrency", "fiscalDateEnding",
# "cashAndCashEquivalentsAtCarryingValue", "cashAndShortTermInvestments",
# "inventory", "currentNetReceivables", "totalCurrentAssets",
# "propertyPlantEquipmentNet", "intangibleAssets",
# "intangibleAssetsExcludingGoodwill", "goodwill", "investments",
# "longTermInvestments", "shortTermInvestments", "otherCurrentAssets",
# "otherNonCurrrentAssets", "currentAccountsPayable", "deferredRevenue",
# "currentDebt", "shortTermDebt", "totalCurrentLiabilities",
# "capitalLeaseObligations", "longTermDebt", "currentLongTermDebt",
# "longTermDebtNoncurrent", "shortLongTermDebtTotal",
# "otherCurrentLiabilities", "otherNonCurrentLiabilities",
# "totalNonCurrentLiabilities", "retainedEarnings",
# "additionalPaidInCapital", "commonStockSharesOutstanding"
```
## CASH_FLOW — Cash Flow Statement
**Required:** `symbol`
```python
data = av_get("CASH_FLOW", symbol="IBM")
annual = data["annualReports"]
yr = annual[0]
print(yr["operatingCashflow"]) # "..."
print(yr["capitalExpenditures"]) # "..."
print(yr["cashflowFromInvestment"]) # "..."
print(yr["cashflowFromFinancing"]) # "..."
# Other keys: "reportedCurrency", "fiscalDateEnding",
# "paymentsForRepurchaseOfCommonStock", "dividendPayout",
# "dividendPayoutCommonStock", "dividendPayoutPreferredStock",
# "proceedsFromIssuanceOfCommonStock", "changeInOperatingLiabilities",
# "changeInOperatingAssets", "depreciationDepletionAndAmortization",
# "capitalExpenditures", "changeInReceivables", "changeInInventory",
# "profitLoss", "netIncomeFromContinuingOperations"
```
## SHARES_OUTSTANDING — Shares Outstanding History
**Required:** `symbol`
```python
data = av_get("SHARES_OUTSTANDING", symbol="AAPL")
shares = data["data"]
for s in shares[:5]:
print(s["date"], s["reportedShares"])
```
## EARNINGS — Earnings History (EPS)
Returns annual and quarterly EPS + surprise data.
**Required:** `symbol`
```python
data = av_get("EARNINGS", symbol="IBM")
annual = data["annualEarnings"]
quarterly = data["quarterlyEarnings"]
# Annual: "fiscalDateEnding", "reportedEPS"
# Quarterly: "fiscalDateEnding", "reportedDate", "reportedEPS",
# "estimatedEPS", "surprise", "surprisePercentage"
q = quarterly[0]
print(q["reportedEPS"], q["estimatedEPS"], q["surprisePercentage"])
```
## EARNINGS_CALENDAR — Upcoming Earnings Dates
Returns earnings release schedule for the next 3-12 months.
**Optional:** `symbol` (if omitted, returns all companies), `horizon` (`3month`, `6month`, `12month`)
```python
# Returns CSV format - use requests directly
import requests, csv, io, os
resp = requests.get(
"https://www.alphavantage.co/query",
params={"function": "EARNINGS_CALENDAR", "symbol": "IBM", "apikey": os.environ["ALPHAVANTAGE_API_KEY"]}
)
reader = csv.DictReader(io.StringIO(resp.text))
for row in reader:
print(row["symbol"], row["name"], row["reportDate"], row["estimate"])
```
## LISTING_STATUS — Listed/Delisted Tickers
**Optional:** `date` (format `YYYY-MM-DD`), `state` (`active` or `delisted`)
```python
# Returns CSV
resp = requests.get(
"https://www.alphavantage.co/query",
params={"function": "LISTING_STATUS", "state": "active", "apikey": API_KEY}
)
reader = csv.DictReader(io.StringIO(resp.text))
# Fields: "symbol", "name", "exchange", "assetType", "ipoDate",
# "delistingDate", "status"
```
## IPO_CALENDAR — Upcoming IPOs
```python
# Returns CSV
resp = requests.get(
"https://www.alphavantage.co/query",
params={"function": "IPO_CALENDAR", "apikey": API_KEY}
)
reader = csv.DictReader(io.StringIO(resp.text))
for row in reader:
print(row["symbol"], row["name"], row["ipoDate"], row["priceRangeLow"], row["priceRangeHigh"])
```
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