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FRITZY TECH INC.: 10-Q filed 2018-02-21

What FRITZY TECH INC. reported in its quarterly report filed 2018-02-21 (fiscal Q2 2018): 14 published measures, 41 facts as tagged in accession 0001640334-18-000382.

This filing

Form
10-Q (quarterly report)
Filed
2018-02-21
Fiscal period
fiscal Q2 2018
Accession
0001640334-18-000382 on SEC EDGAR

Values are as tagged in this filing. A later filing can restate them; each measure links to its history page, which shows the latest-filed value per period. All FRITZY TECH INC. filings.

Reported measures

Total liabilities

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

PeriodValueUnitDays
At 2017-06-3027,794USD

Stockholders equity

The reported residual interest after liabilities. It is an accounting amount, not market capitalization.

PeriodValueUnitDays
At 2017-06-30-27,794USD

Net income or loss

Reported profit or loss for the period. Check the filing for attribution, exceptional items and discontinued operations before comparing companies.

PeriodValueUnitDays
2017-10-01 to 2017-12-311,015USD92
2017-07-01 to 2017-12-3111,616USD184
2016-10-01 to 2016-12-316,785USD92
2016-07-01 to 2016-12-3122,616USD184

Operating cash flow

Cash generated or used by operating activities. Working-capital timing can make this differ substantially from reported income.

PeriodValueUnitDays
2017-07-01 to 2017-12-31-17,329USD184
2016-07-01 to 2016-12-31-1,974USD184

Revenue

Revenue under this specific accounting concept. A missing value is not zero; filers can use other revenue concepts.

PeriodValueUnitDays
2017-10-01 to 2017-12-3111,507USD92
2017-07-01 to 2017-12-3138,855USD184
2016-10-01 to 2016-12-3117,260USD92
2016-07-01 to 2016-12-3134,520USD184

Retained earnings or deficit

Accumulated undistributed earnings or deficit at the reporting date. This balance is not cash available for distribution.

PeriodValueUnitDays
At 2017-12-31-205,463USD
At 2017-06-30-178,641USD

Operating income or loss

Operating revenue less operating expenses for the reporting period. It excludes items outside the reported operating result and is not free cash flow.

PeriodValueUnitDays
2017-10-01 to 2017-12-31-10,575USD92
2017-07-01 to 2017-12-31-26,822USD184
2016-10-01 to 2016-12-31-13,069USD92
2016-07-01 to 2016-12-31-20,093USD184

Interest expense

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

PeriodValueUnitDays
2017-07-01 to 2017-12-31857USD184
2016-10-01 to 2016-12-31857USD92
2016-07-01 to 2016-12-311,714USD184

Operating expenses

Recurring operating costs under this accounting concept, generally excluding production costs included in cost of sales. Check filing presentation before combining expense subtotals.

PeriodValueUnitDays
2017-10-01 to 2017-12-3110,575USD92
2017-07-01 to 2017-12-3125,965USD184
2016-10-01 to 2016-12-3112,212USD92
2016-07-01 to 2016-12-3118,379USD184

Gross profit

Revenue less the costs directly attributed to the goods or services sold. It precedes other operating expenses and is not net income.

PeriodValueUnitDays
2017-10-01 to 2017-12-3111,007USD92
2017-07-01 to 2017-12-3137,855USD184
2016-10-01 to 2016-12-3116,760USD92
2016-07-01 to 2016-12-3133,520USD184

Cost of revenue

Costs attributed to goods produced and sold and services provided during the period. This is not the sum of every operating expense.

PeriodValueUnitDays
2017-10-01 to 2017-12-31500USD92
2017-07-01 to 2017-12-311,000USD184
2016-10-01 to 2016-12-31500USD92
2016-07-01 to 2016-12-311,000USD184

Common shares outstanding

Common shares outstanding at the reporting date. This point-in-time count differs from the weighted-average shares used for earnings per share and can exclude other share classes.

PeriodValueUnitDays
At 2017-12-315,740,000shares
At 2017-06-305,740,000shares

Additional paid-in capital

Capital contributed above par value under this concept. It records historical contributions, not the current value of the equity or cash on hand.

PeriodValueUnitDays
At 2017-12-3176,027USD
At 2017-06-3059,849USD

General and administrative expense

General and administrative costs reported under this concept, separate from selling expense. Filers group overhead differently, so compare presentation before comparing companies.

PeriodValueUnitDays
2017-10-01 to 2017-12-311,005USD92
2017-07-01 to 2017-12-314,494USD184
2016-10-01 to 2016-12-31379USD92
2016-07-01 to 2016-12-31778USD184

Inspect the source

Entity
FRITZY TECH INC. / CIK 0001622408
Captured
SEC response SHA-256
2a90c6459b51adca1bb80286439b3c82e6006e05b94fcae0ae17cba3a8c2e00c

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

Every published concept a filing tagged, with the periods it covered, as reported in that filing at capture time. Forms 10-K, 10-K/A, 10-Q, 10-Q/A, 20-F, 20-F/A, 40-F, 40-F/A. A filing page needs at least 8 published concepts. Later filings can restate these values; the company history pages show the latest-filed value per period.

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.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001622408.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"])))