Schweiter Net Working Capital from 2010 to 2026

SWTQ Stock  CHF 263.00  6.00  2.23%   
Schweiter Technologies Net Working Capital yearly trend continues to be fairly stable with very little volatility. Net Working Capital is likely to outpace its year average in 2026. During the period from 2010 to 2026, Schweiter Technologies Net Working Capital regression line of quarterly data had mean square error of 1096.9 T and geometric mean of  364,592,520. View All Fundamentals
 
Net Working Capital  
First Reported
2010-12-31
Previous Quarter
237.2 M
Current Value
269.8 M
Quarterly Volatility
82.7 M
 
Credit Downgrade
 
Yuan Drop
 
Covid
 
Interest Hikes
Check Schweiter Technologies financial statements over time to gain insight into future company performance. You can evaluate financial statements to find patterns among Schweiter Technologies' main balance sheet or income statement drivers, such as Depreciation And Amortization of 27.3 M, Interest Expense of 4.9 M or Selling General Administrative of 25.3 M, as well as many indicators such as Price To Sales Ratio of 0.64, Dividend Yield of 0.0241 or PTB Ratio of 1.41. Schweiter financial statements analysis is a perfect complement when working with Schweiter Technologies Valuation or Volatility modules.
  
This module can also supplement various Schweiter Technologies Technical models . Check out the analysis of Schweiter Technologies Correlation against competitors.
The evolution of Net Working Capital for Schweiter Technologies AG 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 Schweiter Technologies compares to historical norms and industry peers.

Latest Schweiter Technologies' Net Working Capital Growth Pattern

Below is the plot of the Net Working Capital of Schweiter Technologies AG over the last few years. It is Schweiter Technologies' Net Working Capital historical data analysis aims to capture in quantitative terms the overall pattern of either growth or decline in Schweiter Technologies' overall financial position and show how it may be relating to other accounts over time.
Net Working Capital10 Years Trend
Slightly volatile
   Net Working Capital   
       Timeline  

Schweiter Net Working Capital Regression Statistics

Arithmetic Mean373,965,306
Geometric Mean364,592,520
Coefficient Of Variation22.12
Mean Deviation71,895,242
Median368,243,000
Standard Deviation82,704,159
Sample Variance6840T
Range213.1M
R-Value(0.92)
Mean Square Error1096.9T
R-Squared0.85
Slope(15,096,548)
Total Sum of Squares109439.6T

Schweiter Net Working Capital History

2026269.8 M
2025237.2 M
2024263.6 M
2023256.7 M
2022297.7 M
2021365.3 M
2020368.2 M

About Schweiter Technologies Financial Statements

Schweiter Technologies investors use historical fundamental indicators, such as Schweiter Technologies' Net Working Capital, to determine how well the company is positioned to perform in the future. Understanding over-time patterns can help investors decide on long-term investments in Schweiter Technologies. Please read more on our technical analysis and fundamental analysis pages.
Last ReportedProjected for Next Year
Net Working Capital237.2 M269.8 M

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Additional Tools for Schweiter Stock Analysis

When running Schweiter Technologies' price analysis, check to measure Schweiter Technologies' 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 Schweiter Technologies is operating at the current time. Most of Schweiter Technologies' value examination focuses on studying past and present price action to predict the probability of Schweiter Technologies' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Schweiter Technologies' price. Additionally, you may evaluate how the addition of Schweiter Technologies to your portfolios can decrease your overall portfolio volatility.