Pyxis Inventory Turnover from 2010 to 2024

PXSAW Stock  USD 0.50  0.00  0.00%   
Pyxis Tankers Inventory Turnover yearly trend continues to be fairly stable with very little volatility. Inventory Turnover is likely to outpace its year average in 2024. Inventory Turnover is a ratio showing how many times a company's inventory is sold and replaced over a period, indicating the efficiency of inventory management. View All Fundamentals
 
Inventory Turnover  
First Reported
2010-12-31
Previous Quarter
19.18808777
Current Value
29.74
Quarterly Volatility
9.4665419
 
Credit Downgrade
 
Yuan Drop
 
Covid
Check Pyxis Tankers financial statements over time to gain insight into future company performance. You can evaluate financial statements to find patterns among Pyxis Tankers' main balance sheet or income statement drivers, such as Depreciation And Amortization of 6 M, Interest Expense of 3.9 M or Selling General Administrative of 3.3 M, as well as many indicators such as Price To Sales Ratio of 0.93, Dividend Yield of 0.0188 or PTB Ratio of 0.44. Pyxis financial statements analysis is a perfect complement when working with Pyxis Tankers Valuation or Volatility modules.
  
Check out Your Equity Center to better understand how to build diversified portfolios. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in nation.

Latest Pyxis Tankers' Inventory Turnover Growth Pattern

Below is the plot of the Inventory Turnover of Pyxis Tankers over the last few years. It is a ratio showing how many times a company's inventory is sold and replaced over a period, indicating the efficiency of inventory management. Pyxis Tankers' Inventory Turnover historical data analysis aims to capture in quantitative terms the overall pattern of either growth or decline in Pyxis Tankers' overall financial position and show how it may be relating to other accounts over time.
Inventory Turnover10 Years Trend
Slightly volatile
   Inventory Turnover   
       Timeline  

Pyxis Inventory Turnover Regression Statistics

Arithmetic Mean28.92
Geometric Mean27.46
Coefficient Of Variation32.74
Mean Deviation7.66
Median29.74
Standard Deviation9.47
Sample Variance89.62
Range29.6947
R-Value(0.51)
Mean Square Error71.84
R-Squared0.26
Significance0.05
Slope(1.07)
Total Sum of Squares1,255

Pyxis Inventory Turnover History

2024 29.74
2023 19.19
2022 18.81
2021 17.19
2020 28.73
2019 46.3
2018 30.34

About Pyxis Tankers Financial Statements

Pyxis Tankers investors use historical fundamental indicators, such as Pyxis Tankers' Inventory Turnover, 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 Pyxis Tankers. Please read more on our technical analysis and fundamental analysis pages.
Last ReportedProjected for Next Year
Inventory Turnover 19.19  29.74 

Also Currently Popular

Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.

Additional Tools for Pyxis Stock Analysis

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