AVALONBAY COMMUNITIES, INC.: interest expense

What this measure means

Borrowing costs recognized as interest expense. This is distinct from cash interest paid and may not include every capitalized borrowing cost.

Exact concept: us-gaap:InterestExpense. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2011-01-01 to 2025-12-31. The SEC response was captured on 2026-09-19.

Selected filing history

Related financial histories

• AVALONBAY COMMUNITIES, INC.: total assets
• AVALONBAY COMMUNITIES, INC.: total liabilities
• AVALONBAY COMMUNITIES, INC.: stockholders equity
• AVALONBAY COMMUNITIES, INC.: cash and cash equivalents
• AVALONBAY COMMUNITIES, INC.: net income or loss
• AVALONBAY COMMUNITIES, INC.: operating cash flow
• AVALONBAY COMMUNITIES, INC.: revenue
• AVALONBAY COMMUNITIES, INC.: contract revenue excluding tax
• AVALONBAY COMMUNITIES, INC.: financing cash flow
• AVALONBAY COMMUNITIES, INC.: investing cash flow
• AVALONBAY COMMUNITIES, INC.: retained earnings or deficit
• AVALONBAY COMMUNITIES, INC.: basic weighted-average shares
• AVALONBAY COMMUNITIES, INC.: diluted weighted-average shares
• AVALONBAY COMMUNITIES, INC.: basic earnings per share
• AVALONBAY COMMUNITIES, INC.: diluted earnings per share
• AVALONBAY COMMUNITIES, INC.: income tax expense or benefit
• AVALONBAY COMMUNITIES, INC.: share-based compensation expense
• AVALONBAY COMMUNITIES, INC.: operating income or loss
• AVALONBAY COMMUNITIES, INC.: common-stock repurchase payments
• AVALONBAY COMMUNITIES, INC.: operating expenses

Inspect the source

Entity

AVALONBAY COMMUNITIES, INC. / CIK 0000915912

Captured

2026-09-19T11:15:24.522Z

SEC response SHA-256

97bca1b997018d0288e4f0e52d4cbcd6d9fbda05c32a89c71eb24125e962f7ec

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

• Get an API key and run your first validation
• Connect the MCP server to your coding assistant
• Inspect the ALPHAC engine on GitHub
• Read the MCP server source and integration examples

import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0000915912.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))