China Cost Of Revenue from 2010 to 2025

CAAS Stock  USD 4.07  0.09  2.16%   
China Automotive Cost Of Revenue yearly trend continues to be comparatively stable with very little volatility. Cost Of Revenue will likely drop to about 301.7 M in 2025. From the period from 2010 to 2025, China Automotive Cost Of Revenue quarterly data regression had r-value of  0.67 and coefficient of variation of  31.21. View All Fundamentals
 
Cost Of Revenue  
First Reported
2003-03-31
Previous Quarter
129.3 M
Current Value
137.9 M
Quarterly Volatility
39.9 M
 
Housing Crash
 
Credit Downgrade
 
Yuan Drop
 
Covid
Check China Automotive financial statements over time to gain insight into future company performance. You can evaluate financial statements to find patterns among China Automotive's main balance sheet or income statement drivers, such as Interest Expense of 2 M, Other Operating Expenses of 648.6 M or Operating Income of 47.4 M, as well as many indicators such as Price To Sales Ratio of 0.18, Dividend Yield of 5.0E-4 or PTB Ratio of 0.31. China financial statements analysis is a perfect complement when working with China Automotive Valuation or Volatility modules.
  
Check out the analysis of China Automotive Correlation against competitors.

Latest China Automotive's Cost Of Revenue Growth Pattern

Below is the plot of the Cost Of Revenue of China Automotive Systems over the last few years. Cost of Revenue is found on China Automotive Systems income statement and represents the costs associated with goods and services China Automotive provides. Indirect cost, such as salaries, is not included. In other words, cost of revenue is the total cost incurred to obtain a sale. It is more than the traditional cost of goods sold, since it includes specific selling and marketing activities. It is China Automotive's Cost Of Revenue historical data analysis aims to capture in quantitative terms the overall pattern of either growth or decline in China Automotive's overall financial position and show how it may be relating to other accounts over time.
Cost Of Revenue10 Years Trend
Slightly volatile
   Cost Of Revenue   
       Timeline  

China Cost Of Revenue Regression Statistics

Arithmetic Mean363,370,116
Geometric Mean323,831,614
Coefficient Of Variation31.21
Mean Deviation74,016,536
Median379,299,000
Standard Deviation113,402,359
Sample Variance12860.1T
Range513.1M
R-Value0.67
Mean Square Error7502.4T
R-Squared0.46
Significance0
Slope16,075,894
Total Sum of Squares192901.4T

China Cost Of Revenue History

2025301.7 M
2024543.5 M
2023472.6 M
2022446.2 M
2021425.9 M
2020362.3 M
2019368.1 M

About China Automotive Financial Statements

China Automotive shareholders use historical fundamental indicators, such as Cost Of Revenue, to determine how well the company is positioned to perform in the future. Although China Automotive investors may analyze each financial statement separately, they are all interrelated. The changes in China Automotive's assets and liabilities, for example, are also reflected in the revenues and expenses on on China Automotive's income statement. Understanding these patterns can help investors time the market effectively. Please read more on our fundamental analysis page.
Last ReportedProjected for Next Year
Cost Of Revenue543.5 M301.7 M

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Additional Tools for China Stock Analysis

When running China Automotive's price analysis, check to measure China Automotive's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy China Automotive is operating at the current time. Most of China Automotive's value examination focuses on studying past and present price action to predict the probability of China Automotive's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move China Automotive's price. Additionally, you may evaluate how the addition of China Automotive to your portfolios can decrease your overall portfolio volatility.