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Microlesson · 5-min read

Baumol vs Miller-Orr Cash Management Models

## Baumol vs Miller-Orr — A Comparison

### Baumol's Model (EOQ for Cash)

#### Concept

The optimum cash level is that level where carrying costs and transaction costs are minimised.

#### Two Costs Trade Off

  • Carrying cost: Interest forgone on marketable securities held as cash.
  • Transaction cost: Cost of converting marketable securities to cash (clerical, brokerage, registration).

#### Optimum Cash Balance Formula

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

Where:

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

#### Assumption

Cash usage is steady and predictable (like inventory EOQ).

### Miller-Orr Model

#### Concept

A stochastic (random) cash flow model. Uses control limits (h, z, 0) — see separate Miller-Orr lesson.

#### Behaviour

  • When cash hits h → invest (h − z) in securities.
  • When cash hits 0 → liquidate z worth of securities.
  • Between limits → no action.

### Side-by-Side Comparison

FeatureBaumolMiller-Orr
Cash flow natureSteady, certainRandom, stochastic
Decision variableSingle quantity C*Limits h and z
When to transactEvery time C is consumedWhen h or 0 is hit
Mathematical baseEOQ formulaControl theory
Best suited forFirms with predictable outflowsFirms with volatile cash flows
TriggerTime-based (cash runs to zero)Threshold-based

Worked example

### Example 1

Baumol Example: U = ₹12,00,000 annual disbursements, P = ₹100 per transaction, S = 8% p.a.

C = √(2 × 12,00,000 × 100 / 0.08) = √(3,00,00,00,000) = ₹54,772 ≈ ₹55,000.

Each time cash runs out, sell ₹55,000 of securities. Number of transactions per year = 12,00,000 / 55,000 ≈ 22.

⚠️ Common exam mistakes

  • Forgetting the √2 in Baumol's formula — it is √(2UP/S), NOT 2UP/S.
  • Confusing the unit period of U with S — if U is annual, S must also be annual.
  • Saying Baumol works for random flows — it assumes STEADY usage.
  • Mixing up Miller-Orr's h and z — h is the UPPER limit, z is the RETURN point.
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