COHERENT CORP.: current assets

What this measure means

Assets classified as current under the normal operating cycle or one-year boundary. Not all current assets can be converted immediately into cash.

Exact concept: us-gaap:AssetsCurrent. 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 2010-06-30 to 2026-06-30. The SEC response was captured on 2026-09-19.

Selected filing history

Related financial histories

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

Inspect the source

Entity

COHERENT CORP. / CIK 0000820318

Captured

2026-09-19T11:14:43.151Z

SEC response SHA-256

7d791ad03faf63356a10a6ccd68f119dbacdd41951a34aef227fa2125afed7b6

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/0000820318.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"])))