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Microlesson · 5-min read

Cash Management Models: Baumol vs Miller-Orr

# Cash Management Models: Baumol vs Miller-Orr

Firms must decide how much cash to hold and when to move money between cash and marketable securities. Two classical models address this.

## William J. Baumol's Model (Deterministic / EOQ-style)

Based on the Economic Order Quantity logic. The optimum cash level is the point at which two costs balance out:

  • Carrying cost — interest income foregone by holding cash instead of marketable securities.
  • Transaction cost — clerical, brokerage, and registration costs incurred each time securities are converted to cash to plug a shortfall.

The optimum cash balance occurs where carrying cost equals transaction cost.

### Formula

$$C = \sqrt{\dfrac{2 \times U \times P}{S}}$$

Where:

  • C = Optimum cash balance (per transaction conversion)
  • U = Annual (or monthly) cash disbursements
  • P = Fixed cost per transaction (per conversion of securities to cash)
  • S = Opportunity cost of holding one rupee of cash p.a. (or p.m.)

The model assumes a constant, predictable rate of cash usage.

## Miller-Orr Model (Stochastic)

Designed for situations where net cash flows are random / unpredictable. It decides the timing and size of transfers between an investment account and the cash account.

Three control limits are set on the cash balance:

  • h = Upper limit
  • z = Return point (target level)
  • 0 = Lower limit

### How it operates

Cash balance reachesAction
Upper limit (h)Invest (h − z) in marketable securities. Cash returns to z.
Lower limit (0)Sell securities worth z. Cash returns to z.
Between (0, h)Do nothing — no transaction.

### Inputs that determine h and z

  • Fixed cost per securities transaction
  • Opportunity cost of holding cash
  • Degree of likely fluctuation (variance) in cash balances

The limits are chosen so that demands for cash are met at the lowest possible total cost.

## Quick Comparison

FeatureBaumolMiller-Orr
Cash flow patternSteady, predictableRandom / fluctuating
Type of modelDeterministic (EOQ)Stochastic
OutputOne optimum lot sizeUpper limit, return point, lower limit
Trigger to actCash hits zeroCash hits h or 0

Worked example

### Example 1

Illustration (Baumol): Annual cash disbursements U = ₹12,00,000; fixed cost per conversion P = ₹50; opportunity cost S = 8% p.a.

$$C = \sqrt{\dfrac{2 \times 12{,}00{,}000 \times 50}{0.08}} = \sqrt{15{,}00{,}00{,}000} \approx ₹38{,}730$$

So each time the firm runs out of cash, it converts about ₹38,730 worth of securities into cash. Number of transactions per year ≈ 12,00,000 / 38,730 ≈ 31.

⚠️ Common exam mistakes

  • Confusing the two models — applying Baumol when cash flows are uncertain (it assumes steady disbursement).
  • Treating 'S' in the Baumol formula as a rupee amount instead of an opportunity cost rate (per rupee p.a.).
  • Forgetting that under Miller-Orr no transaction occurs while balance stays between the limits — students sometimes draw transfers at the return point z.
Reference:
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