Dolby Laboratories, Inc.: current liabilities

What this measure means

Obligations classified as current under the operating-cycle or one-year boundary. The balance includes more than short-term borrowing.

Exact concept: us-gaap:LiabilitiesCurrent. 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 2009-09-25 to 2025-09-26. The SEC response was captured on 2026-09-20.

Selected filing history

Related financial histories

• Dolby Laboratories, Inc.: total assets
• Dolby Laboratories, Inc.: total liabilities
• Dolby Laboratories, Inc.: stockholders equity
• Dolby Laboratories, Inc.: cash and cash equivalents
• Dolby Laboratories, Inc.: net income or loss
• Dolby Laboratories, Inc.: operating cash flow
• Dolby Laboratories, Inc.: capital expenditure payments
• Dolby Laboratories, Inc.: revenue
• Dolby Laboratories, Inc.: contract revenue excluding tax
• Dolby Laboratories, Inc.: financing cash flow
• Dolby Laboratories, Inc.: investing cash flow
• Dolby Laboratories, Inc.: retained earnings or deficit
• Dolby Laboratories, Inc.: basic weighted-average shares
• Dolby Laboratories, Inc.: diluted weighted-average shares
• Dolby Laboratories, Inc.: basic earnings per share
• Dolby Laboratories, Inc.: diluted earnings per share
• Dolby Laboratories, Inc.: income tax expense or benefit
• Dolby Laboratories, Inc.: net property, plant and equipment
• Dolby Laboratories, Inc.: share-based compensation expense
• Dolby Laboratories, Inc.: operating income or loss
• Dolby Laboratories, Inc.: current assets
• Dolby Laboratories, Inc.: interest expense
• Dolby Laboratories, Inc.: current accounts payable
• Dolby Laboratories, Inc.: goodwill carrying amount
• Dolby Laboratories, Inc.: net finite-lived intangible assets
• Dolby Laboratories, Inc.: net current accounts receivable
• Dolby Laboratories, Inc.: common-stock repurchase payments
• Dolby Laboratories, Inc.: operating expenses
• Dolby Laboratories, Inc.: net inventory
• Dolby Laboratories, Inc.: gross profit
• Dolby Laboratories, Inc.: cost of revenue
• Dolby Laboratories, Inc.: research and development expense

Inspect the source

Entity

Dolby Laboratories, Inc. / CIK 0001308547

Captured

2026-09-20T07:51:10.545Z

SEC response SHA-256

cc65a6f34013f443da51e389f537bca7ca8bca8cc3e2da20106c70e8530cc05b

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/0001308547.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"])))