Lecture 11 – Short-Term Investment: A Portfolio Approach

11.1 Background – Why Manage a Short-Term Portfolio?

• Treasury management ≈ deciding how much of the firm’s liquid resources stay in cash versus are invested in marketable securities (M/S).

• Goal: assemble a basket of very short-dated, low-risk instruments that meets the firm’s investment objectives (liquidity, safety, yield).

• Policy issues the treasurer must pre-define:

  • Allocation of cash vs. M/S (liquidity buffer vs. yield).

  • External (outsourced) vs. internal (in-house) portfolio management.

  • Ongoing monitoring & performance evaluation.

11.2 Short-Term Investment Policy – Laying Down the Rules

• Challenge: Hundreds of money-market instruments with many denominations & maturities → different (but tiny) risk-return trade-offs.

• Risk generally outweighs return in the short end because the #1 objective is preserving principal.

• Specific policy directives normally spell out:

  • Dollar limits, sector limits, credit-rating floors.

  • Permitted strategies (passive buy-and-hold, active trading, maturity matching, etc.).

  • Absolute or relative yield targets (vs. T-bill, CD, etc.).

  • Maximum maturity limits (e.g., no security > 90 days).

  • Internal vs. external management, procedures, controls & reporting frequency.

• 3-step formulation process:

  1. Map the pattern of cash flows → estimate how much permanent cash is needed vs. investible surplus.

  2. Gauge overall risk tolerance of management & shareholders.

  3. Factor in third-party constraints (loan covenants, compensating balances, rating-agency expectations).

• Combining historical liquidity needs + risk tolerance + outside constraints ⇒ usable investment policy.

11.3 Cash & Securities Allocation – How Much Cash Is Enough?

• Working-capital choice = % of total assets sitting in current assets.

• Cash = stock of instantly-available liquidity, but it earns 0 and loses purchasing power → keep only a safety level.

• Minimise total cost = transaction cost + opportunity cost (similar to the EOQ logic used for inventories).

11.3.1 The Baumol Model (Deterministic EOQ for Cash)

• Objective: Min\;TPC = F\times\frac{TCN}{Z} + i\times\frac{Z}{2}

  • F = fixed cost per security sale/purchase.

  • TCN = total cash need over the period.

  • Z = replenishment size (also the starting balance).

  • i = opportunity interest rate.

• Optimal transfer size:
  Z^* = \left( \frac{2 \times F \times TCN}{i} \right)^{0.5}

• Caveats:

  • Requires known & constant disbursement rate.

  • Assumes cash inflows are lump-sum, outflows a smooth stream ⇒ reality demands a safety stock.

11.3.2 The Miller–Orr Model (Stochastic Control Limits)

• Allows unpredictable daily net-cash swings (variance (\sigma^2)).

• Three key points:

  • Lower Control Limit (LCL) – preset minimum cash (management decides).

  • Return Point (target) – Z^* + LCL.

  • Upper Control Limit (UCL) – triggers an automatic purchase of M/S to bring balance back to the return point.

• Optimal transfer size:
  Z^* = \left( \frac{3 \times F \times \sigma^2}{4 \times i} \right)^{\frac{1}{3}}

• Significance: dynamic band-control recognises that cash fluctuates randomly; balances transaction cost vs. opportunity cost in real time.

11.3.3 Cash-Security Mix

• The Baumol or Miller–Orr output = optimum amount of cash; excess = investible in M/S.

11.4 Investment Decision-Making – Security Selection

• Once cash vs. securities split is known, manager selects specific instruments.

External Management

• Outsource to brokers/banks (e.g., Nesbitt Burns, Merrill Lynch, Royal Bank, BMO).

• Advantage: professional research & economies of scale (similar to buying units of a money-market fund) → frees the treasurer.

Internal Management – Decisions Required

• • Domestic vs. foreign instruments.

• • Issuer type: government, agency, corporate.

• • Denominations (\$1 M vs. \$100 k lots).

• • Maturity buckets.

• • Yield expectations.

• • Risk limits (default, market, capital loss).

• Regardless of who manages, performance must be benchmarked (vs. published indices or peer portfolios).

11.5 Computation of Portfolio Returns

Case 1 – Buy & Hold for the Entire Period

• Portfolio return is a weighted arithmetic average:
  E(Rp) = \sum{i} wi \times E(Ri)

11.6 Portfolio Risk Analysis – How Safe Is "Safe"?

• Short-term portfolios support liquidity; any default imperils operations.

• Major risk drivers:

  • Default risk (most critical).

  • Liquidity risk (ability to liquidate quickly without loss).

  • Interest-rate risk (price sensitivity of instruments).

  • Re-investment risk (future rates unknown when proceeds mature).

  • Event risk (sudden issuer-specific shocks).

11.6.1 Measuring Risk in a Two-Asset Portfolio

• Expected return:
  E(Rp) = w1 E(R1) + w2 E(R_2)

• Variance:
  \sigma{Rp}^2 = w1^2 \sigma1^2 + w2^2 \sigma2^2 + 2 w1 w2 Cov(R1, R2) = w1^2 \sigma1^2 + w2^2 \sigma2^2 + 2 w1 w2 \rho \sigma1 \sigma_2

• Minimum variance when \rho = -1 (perfect negative correlation).

• Reality check: Money-market instruments are highly positively correlated (0.98 – 0.997 vs. T-bill), driven by the central-bank-set Bank Rate → diversification offers little risk relief.

11.7 Short-Term Investment Strategies

• Passive strategies: once constructed, very few trades.

  • Buy & Hold / Maturity Matching – align maturities with known cash needs (insurers matching claim payments).

• Active strategies: continual trading to exploit expected rate moves.

  • Historical yield-spread analysis.

  • Riding the yield curve (Lecture 10): buy longer maturities when curve expected to flatten/fall, selling before excessive duration risk emerges.

• Strategy choice depends on policy limits, staff expertise, transaction costs and interest-rate outlook.

Ethical, Practical & Philosophical Implications

• Prioritising liquidity and safety safeguards employees, suppliers and shareholders from disruptive funding crises (ethical stewardship).

• Over-reaching for yield in the short end can be viewed as a breach of fiduciary duty if it endangers principal.

• Active trading may increase operational risk – need robust controls, segregation of duties, audits.

• Outsourcing raises questions of agency problems, fee transparency and alignment with corporate risk tolerance.

Connections to Previous Lectures & Real-World Context

• Lecture 3: Baumol cash model = direct analogue of EOQ for inventories → same calculus-based cost trade-off.

• Lecture 10: Riding the yield curve technique borrowed from bond portfolio management; short-term desk adopts a scaled-down version.

• Central-bank open-market operations (buying/selling T-bills) ripple instantly through CD, CP, Eurodollar, Fed-funds rates → explains high correlations.

High-Level Takeaways

• Treasury’s first mandate = maintain liquidity; yield is secondary.

• Deterministic Baumol works only with predictable cash needs; stochastic Miller–Orr better reflects real-life randomness.

• In money markets, diversification ≠ big risk reduction because instruments move together; credit quality selection becomes paramount.

• Choice between passive and active strategy hinges on outlook for rates, internal expertise and cost-benefit of extra trading.