Shopify Average Inventory from 2010 to 2024
| SHOP Stock | USD 106.48 2.54 2.44% |
Average Inventory | First Reported 2010-12-31 | Previous Quarter 0.45 | Current Value 0.43 | Quarterly Volatility 4 M |
Check Shopify financial statements over time to gain insight into future company performance. You can evaluate financial statements to find patterns among Shopify's main balance sheet or income statement drivers, such as Depreciation And Amortization of 37.7 M, Interest Expense of 1.3 M or Selling General Administrative of 515.5 M, as well as many indicators such as Price To Sales Ratio of 26.28, Dividend Yield of 0.0 or PTB Ratio of 15.57. Shopify financial statements analysis is a perfect complement when working with Shopify Valuation or Volatility modules.
Shopify | Average Inventory |
Latest Shopify's Average Inventory Growth Pattern
Below is the plot of the Average Inventory of Shopify over the last few years. It is the average amount of inventory a company holds over a certain period, which is used to calculate inventory turnover and efficiency in managing stock levels. Shopify's Average Inventory historical data analysis aims to capture in quantitative terms the overall pattern of either growth or decline in Shopify's overall financial position and show how it may be relating to other accounts over time.
| Average Inventory | 10 Years Trend |
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Average Inventory |
| Timeline |
Shopify Average Inventory Regression Statistics
| Arithmetic Mean | 1,500,734 | |
| Geometric Mean | 4.70 | |
| Coefficient Of Variation | 263.90 | |
| Mean Deviation | 2,601,271 | |
| Median | 0.50 | |
| Standard Deviation | 3,960,425 | |
| Sample Variance | 15.7T | |
| Range | 11.3M | |
| R-Value | 0.14 | |
| Mean Square Error | 16.6T | |
| R-Squared | 0.02 | |
| Significance | 0.63 | |
| Slope | 120,595 | |
| Total Sum of Squares | 219.6T |
Shopify Average Inventory History
About Shopify Financial Statements
Shopify shareholders use historical fundamental indicators, such as Average Inventory, to determine how well the company is positioned to perform in the future. Although Shopify investors may analyze each financial statement separately, they are all interrelated. The changes in Shopify's assets and liabilities, for example, are also reflected in the revenues and expenses on on Shopify's income statement. Understanding these patterns can help investors time the market effectively. Please read more on our fundamental analysis page.
| Last Reported | Projected for Next Year | ||
| Average Inventory | 0.45 | 0.43 |
Pair Trading with Shopify
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Shopify position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Shopify will appreciate offsetting losses from the drop in the long position's value.Moving together with Shopify Stock
| 0.73 | DJCO | Daily Journal Corp | PairCorr |
| 0.74 | AI | C3 Ai Inc Trending | PairCorr |
| 0.77 | AZ | A2Z Smart Technologies | PairCorr |
| 0.77 | BL | Blackline | PairCorr |
Moving against Shopify Stock
The ability to find closely correlated positions to Shopify could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Shopify when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Shopify - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Shopify to buy it.
The correlation of Shopify is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Shopify moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Shopify moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Shopify can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Additional Tools for Shopify Stock Analysis
When running Shopify's price analysis, check to measure Shopify'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 Shopify is operating at the current time. Most of Shopify's value examination focuses on studying past and present price action to predict the probability of Shopify's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Shopify's price. Additionally, you may evaluate how the addition of Shopify to your portfolios can decrease your overall portfolio volatility.