Optimal Portfolio Construction

We use advanced forecasting techniques to obtain predicted returns on a large universe of stocks.

We use advanced Risk measurement techniques.

We combine both in an Optimal Portfolio Construction Process to obtain superior Return to Risk ratios


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April 19, 2012: Death of a great investment counselor, Carl H. Otto

Updated: April 20, 2012

Optimal Portfolio Construction

As of today, there are still many investment managers using ad-hoc and trial & error methods in working on enhancing a portfolio’s expected return while maintaining proper diversification and portfolio characteristics. Yet, well understood tools and techniques allow for easily obtaining a portfolio which:

  1. maximizes its exposure to a managers’ insights and forecast of (excess) return,
  2. maintains a portfolio’s expected risk within some budgetary constraints and controlled portfolio characteristics.

Refer to my history of risk controls and optimal portfolio construction page for more information on the evolution of these tools and techniques.

Efficient Frontier

Ad-hoc methods always lead to sub-optimal use of a manager’s insight as in Portfolio C in the above chart. Using the same manager’s insight, one can obtain a portfolio with much higher expected return for the same risk level (Portfolio B), or much lower risk for the same expected return (Portfolio A). Thus any portfolio on the efficient frontier between portfolio A and B is far more interesting than ad-hoc portfolio C. With these tools and techniques easily available today, it is surprising to see investment managers still using ad-hoc methods of portfolio construction.

The Optimal investment process can easily be summarized by:

  1. Forecast returns or active returns on a large universe of stocks. See my page on Alpha forecasting for more information which is not complete without a clear understanding of a manager’s Investment Skill as measured by one’s Information Coefficient (IC).
  2. Predicted Risk (active or total) using some multi-factor risk models based on factors closely related to the driving factors in a manager’s forecast. While some managers still use a trial and error ad-hoc method to improve their portfolio, simple techniques achieve more optimal solution delivering higher “return to risk” portfolios.
  3. Estimated/predicted transaction costs. Various factors affect the implementation cost of trading like a firm‘s size, liquidity, volatility, etc. An estimate of these costs allows for an integrated investment process which takes into account all critical information: a manager’s insights, risk and cost.
  4. Then it is just a question of putting these three together in an integrated optimal portfolio construction process which seeks to maximize a portfolio’s exposure to a manager’s insight subject to some risk budget constraint and risk controls.
Dominic Clermont's Optimal Portfolio Construction Process

The above approach is very much standard and used by all modern investment managers who understand the trade-off between risk and return.

While some managers still think they can do better using ad-hoc portfolio construction techniques, a simple test with a universe of 3 stocks – thus 3 variances and 3 covariances – shows that no managers can achieve an optimal solution. No human brain (no matter how intelligent your manager is…) can handle such complexity. Imagine when the number of stocks involved is in the hundreds, or even in the thousands. If your manager is pretentious to the point that he seriously thinks he can build better portfolios based on his judgment of the risk, you should move on.

Fortunately, there are simple tools to assist any managers in building better balanced portfolios. These tools are used by a majority of managers whether they are Traditional Active or a Quant and in Equity, Fixed Income or Asset Allocation.

Dominic Clermont, ASA, MBA, CFA


State of the Art Investment Management