Modeling Liquidity and Income in Modern Portfolios

Todd E Petzel, CIO Offit Capital Advisors

QWAFAFEW New York

March 24, 2009

• Outline of Presentation– Traditional Models and Assumptions– Incorporating Liquidity and Income

Theoretically– Practical Issues and Approaches

• Traditional Approaches– Linear or non-linear optimization in return

space– Monte Carlo simulation in return space– “Total Return” spending rules

• Major implicit assumption: portfolio adjustments are frictionless and costless

•Optimizers have multiple problems

• Thousands of data points; one history

• Corner solutions are the norm

• “Solutions” more likely to reflect constraints than truth

•Monte Carlo is supposed to cure these issues

• Thousands of simulations, but based on same history

• Distribution of outcomes versus a single expected characterization

•Monte Carlo approach still has severe issues

• Covariance assumptions are subject to abrupt changes

• Path dependency is fairly rudimentary

• Still backward looking

December 31, 2008

June 30, 2008

Total Return Spending Rules

• The exception rather than the rule 40 years ago

• Assumes sufficient liquidity to create payments from portfolio and to rebalance

• Ignores actual operations side of enterprise and covenants

Private Equity Simulation Rules

• First cousin to Monte Carlo portfolio analysis

• Used to plan transition to “long-term” portfolio containing illiquid partnerships

• Usual conclusion: Over allocate to illiquid partnerships in order to reach goal

• Keep money in equities while waiting for calls

Major Unstated Assumptions

• Bull markets provide early distributions and funding sources for following calls

• There will always be enough liquid securities to sell when capital calls appear

• Simulations based on a decidedly bull market history

Reality in 2008

• PE obligations slowed down, but still remain dollar liabilities to the investor

• Intended source of funding hammered by bear market

• Liquid securities have been sold down to meet regular spending and capital calls

• Major institutions borrow to pay bills

Where do Liquidity and Income Fit In?

• In the traditional approaches there is no difference between liquid and illiquid investments, or between income and total return

• Recommendations for illiquid private investments are usually only bounded by initial constraints

How to Improve the Models

• Don’t maximize wealth, maximize utility

• U = f(W, L, I) [Wealth, Liquidity, Income]

• Downward sloping marginal utility of all factors

• Upward sloping transactions costs associated with less income or liquidity

• Higher opportunity costs of more income and liquidity

Conceptually This Isn’t Too Difficult

• Problems arise in execution

• Do organizations understand their marginal utilities of liquidity and income in good times?

• Very similar problem to estimating the marginal utility of storage between times of full inventories and shortages.

Practical Approaches

• Throw away your total return spending rule

• Integrate the operational budget and investment processes

• Understand how much cash you’ll need in the near term

Practical Approaches II

• Split the portfolio into two components:

•Sleep well at night money

•Long-term portfolio

• Try to cover cash needs with income producing assets

• If that is not possible, decrease illiquid assets to lower impact of asset sales

Practical Approaches III

• Forecast future capital calls

• Set aside “sleep well at night money” for these liabilities extending some period

• Do not over allocate to partnerships to try to build up positions quickly

Conclusions• Inability to properly model income or liquidity benefits skewed portfolio construction toward higher risks

• Too many institutions are revisiting these topics now after suffering permanent losses

• Ad hoc rules are better than inadequate models