CNET Receivables Turnover from 2010 to 2026

CNET Stock  USD 0.80  0.06  8.11%   
Over recent reporting cycles, Receivables Turnover is advancing amid very volatile fluctuations. Compared with the previous period, Receivables Turnover is up roughly 50.00%, supporting projections near 7.22. From 2010 to 2026, the annual regression model for ZW Data Receivables Turnover reported a mean deviation of 4.11 . alongside coefficient of variation of 53.66 . View All Fundamentals
 
Receivables Turnover  
 First Reported
2010-12-31
 Previous Quarter
3.61
 Current Value
7.22
 Quarterly Volatility
4.88257083
Macro event markers
 
Credit Downgrade
 
Yuan Drop
 
Covid
 
Interest Hikes
Review ZW Data financial statements over time to add context on performance and capital structure. It connects Depreciation And Amortization of 1.3 M, Interest Expense of 1.7 M or Selling General Administrative of 6.2 M and ratios such as Price To Sales Ratio of 0.26, Dividend Yield of 1.0E-4 or PTB Ratio of 0.94 with ZW Data Valuation and Volatility context.
  
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The evolution of Receivables Turnover for ZW Data Action provides essential context for understanding the company's financial health trajectory. By analyzing this metric's behavior over time, investors can assess whether recent trends align with long-term patterns, and how ZW Data compares to historical norms and industry peers.

Latest ZW Data's Receivables Turnover Growth Pattern

Below is the plot of the Receivables Turnover of ZW Data Action over the last few years. It is ZW Data's Receivables Turnover historical data analysis aims to capture in quantitative terms the overall pattern of either growth or decline in ZW Data's overall financial position and show how it may be relating to other accounts over time.
Receivables Turnover10 Years Trend
Very volatile
   Receivables Turnover   
       Timeline  

CNET Receivables Turnover Regression Statistics

Arithmetic Mean 9.10
Geometric Mean 7.79
Coefficient Of Variation 53.66
Mean Deviation 4.11
Median 7.75
Standard Deviation 4.88
Sample Variance 23.84
Range14.8985
R-Value 0.02
Mean Square Error 25.42
R-Squared 0.0005
Significance 0.93
Slope 0.02
Total Sum of Squares 381.43

CNET Receivables Turnover History

2026 7.22
2025 3.61
2024 4.02
2023 8.41
2022 15.03
2021 13.52
2020 15.56

Stock Overview, Methodology & Data Sources

ZW Data Action Technologies Inc., through its subsidiaries, provides omni-channel advertising, precision marketing, and data analysis management systems in the Peoples Republic of China. ZW Data Action Technologies Inc. was founded in 2003 and is headquartered in Beijing, the Peoples Republic of China. Chinanet Online operates under Advertising Agencies classification in the United States and is traded on NASDAQ Exchange. It employs 85 people. The profile for ZW Data integrates fundamentals, price behavior, and sector exposure. Historical patterns suggest somewhat reduced sensitivity to broader economic swings. ZW Data has a market cap of 2.45 M, ROE of -49.51%.

Methodology

Unless otherwise specified, financial data for ZW Data Action is derived from periodic company reporting (annual and quarterly where available). Asset-level metrics are computed daily by Macroaxis LLC and refreshed regularly based on asset type. CNET (USA Stocks:CNET) prices are typically delayed by approximately 20 minutes from primary exchanges for listed equities. Data may be delayed depending on reporting sources and market conventions. Assumptions: We use public filings and market reference sources with disclosures published by U.S. Securities and Exchange Commission (SEC) via EDGAR as reference inputs. Data may be normalized and can be delayed. All analytics are generated using standardized, rules-based models designed to promote consistency and comparability across instruments. Model assumptions, reference parameters, and selected computational inputs are available in the Model Inputs section. If you have questions about our data sources or methodology, please contact Macroaxis Support.

Analyst Sources

ZW Data Action may have analyst coverage included in Macroaxis-derived consensus inputs when available. Updates may occur throughout the day.

This content is curated and reviewed by:

Rifka Kats - Member of Macroaxis Editorial Board

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