TEEKAY TANKERS LTD.: total liabilities

What this measure means

Recognized obligations at the reporting date. The definition and scope differ from interest-bearing debt.

Exact concept: us-gaap:Liabilities. Each value is a balance at the reporting date, not a flow earned over a year. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2010-12-31 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Related financial histories

• TEEKAY TANKERS LTD.: total assets
• TEEKAY TANKERS LTD.: stockholders equity
• TEEKAY TANKERS LTD.: cash and cash equivalents
• TEEKAY TANKERS LTD.: net income or loss
• TEEKAY TANKERS LTD.: operating cash flow
• TEEKAY TANKERS LTD.: capital expenditure payments
• TEEKAY TANKERS LTD.: revenue
• TEEKAY TANKERS LTD.: contract revenue excluding tax
• TEEKAY TANKERS LTD.: financing cash flow
• TEEKAY TANKERS LTD.: investing cash flow
• TEEKAY TANKERS LTD.: retained earnings or deficit
• TEEKAY TANKERS LTD.: basic weighted-average shares
• TEEKAY TANKERS LTD.: diluted weighted-average shares
• TEEKAY TANKERS LTD.: basic earnings per share
• TEEKAY TANKERS LTD.: diluted earnings per share
• TEEKAY TANKERS LTD.: income tax expense or benefit
• TEEKAY TANKERS LTD.: net property, plant and equipment
• TEEKAY TANKERS LTD.: operating income or loss
• TEEKAY TANKERS LTD.: current assets
• TEEKAY TANKERS LTD.: interest expense
• TEEKAY TANKERS LTD.: current liabilities
• TEEKAY TANKERS LTD.: current accounts payable
• TEEKAY TANKERS LTD.: goodwill carrying amount
• TEEKAY TANKERS LTD.: net finite-lived intangible assets
• TEEKAY TANKERS LTD.: net current accounts receivable
• TEEKAY TANKERS LTD.: operating expenses
• TEEKAY TANKERS LTD.: net inventory

Inspect the source

Entity

TEEKAY TANKERS LTD. / CIK 0001419945

Captured

2026-09-20T08:02:58.293Z

SEC response SHA-256

265bacf3c9f5626c8498f46d47ec1d9c3a633ef2adecf64d69ff915515e6550e

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/0001419945.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"])))