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Days in inventory (also known as "Inventory Days of Supply", "Days Inventory Outstanding" or the "Inventory Period" [1]) is an efficiency ratio which measures the average number of days a company holds its inventory before selling it. The ratio measures the number of days funds are tied up in inventory.
The average collection period (ACP) is the time taken by businesses to convert their accounts receivable (AR) to cash. Credit sales are all sales made on credit (i.e. excluding cash sales). A long debtors collection period is an indication of slow or late payments by debtors.
Receivable turnover ratio or debtor's turnover ratio is an accounting measure used to measure how effective a company is in extending credit as well as collecting debts. The receivables turnover ratio is an activity ratio, measuring how efficiently a firm uses its assets. [1] Formula:
An Overview of the Return on Assets Ratio Formula Return on assets is a measure of corporate efficiency. The more a company can earn relative to its total assets, the more productive it is.
A low ratio may indicate the firm's credit policy is too rigorous, which may be hampering sales. Days sales outstanding is often misinterpreted as "the average number of days to fully collect payment after making a sale". The formula for this would be Σ (Sales date) - (Paid date) / (Sale count) . This calculation is sometimes called ...
This convention accounts for days in the period based on the portion in a leap year and the portion in a non-leap year. The days in the numerators are calculated on a Julian day difference basis. In this convention the first day of the period is included and the last day is excluded. The CouponFactor uses the same formula, replacing Date2 by Date3.
The annualized loss expectancy (ALE) [1] is the product of the annual rate of occurrence (ARO) and the single loss expectancy (SLE). It is mathematically expressed as: = ...
The accuracy ratio (AR) is defined as the ratio of the area between the model CAP and random CAP, and the area between the perfect CAP and random CAP. [2] In a successful model, the AR has values between zero and one, and the higher the value is, the stronger the model. The cumulative number of positive outcomes indicates a model's strength.