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Cash Ratio Calculator
The cash ratio is the most conservative liquidity ratio. It counts only cash, cash equivalents and marketable securities, the assets that can pay a bill today, and divides them by current liabilities. Receivables and inventory are left out entirely, because both depend on customers paying or buying.
Formula
Where
- Cash
- cash and cash equivalents
- Marketable securities
- short-term investments convertible to cash almost immediately
- Current liabilities
- obligations due within a year
Calculator
Result and step-by-step solution
Cash on hand covers 48% of current liabilities.
- Cash and securities40,000.00 + 20,000.00 = 60,000.00
- Divide60,000.00125,000.00 = 0.48
How to use the formula
Creditors use the cash ratio to see how a company would cope if its revenue stopped suddenly. It is rarely close to 1 for a healthy operating business, because holding that much cash is expensive: money in the bank earns little compared with what it could earn invested in the business.
With 40,000 of cash and 20,000 of marketable securities against current liabilities of 125,000, the cash ratio is 0.48, so the business could pay 48% of its short-term obligations immediately. Many analysts see 0.2 to 0.5 as reasonable, but the right level depends on how predictable the company’s cash flows are. Compare it with the quick ratio, which adds receivables, and the broader current ratio.
Frequently asked questions
- What is the cash ratio formula?
- Cash ratio = (cash and cash equivalents + marketable securities) ÷ current liabilities.
- What is a good cash ratio?
- There is no universal target; 0.2 to 0.5 is common. A ratio above 1 means cash alone covers all current liabilities.
- Why is the cash ratio lower than the quick ratio?
- It leaves out accounts receivable, which the quick ratio includes.
- Is a very high cash ratio good?
- It is safe but can mean cash is sitting idle instead of being invested or returned to shareholders.
Last reviewed: September 26, 2026. Calculations run in your browser and were checked against numpy-financial, SciPy and published spreadsheet examples.
