Journal of Investing · May, 2019

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A risk management system should, at a minimum, explain asset class behavior and provide useful insights. Most current methodologies fall short in either one or both areas. They have inconsistent explanatory power and offer little or no insight, forcing portfolio managers to resort to blind faith. How else can one explain the calamity that befell prominent institutions during the Great Recession of 2007/8?
Understanding the sources of risk is a critical component in managing it. An economic factor model provides this much needed understanding. It not only explains price behavior of diverse assets, but does so in an intuitive manner.
It is our expectation that a better understanding will result in more resilient portfolios, limiting the drawdowns from market corrections and producing more satisfactory outcomes. We also envision novel uses arising from such a system that are heretofore not practical or feasible.

Journal of Investing November  2011

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Implicit in active fund management is the presumption that the S&P capitalization indices (i.e. S&P 500, S&P 400 and S&P 600) can be bested. Needless to say, active fund management on the whole has not lived up to expectations, with portfolios regularly

trailing their respective indices. Thus, the claim by active managers in aggregate that they can beat an index is not indicative and statistically impossible. However, the performance disparity between active and index funds shows that there is a lot of room for improvement. The fact that most managers are unable to beat their respective indices is not indicative of the quality of the selection criteria used to build these benchmarks. Rather, it is indicative of the inherent deficits of active investment management practices. The objective of this paper is to highlight some of these flawed practices, and in the process, suggest ways to improve the state of the art.

Journal of Wealth Management

October 2007

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Saving and retirement planning currently rely on techniques that have proven to be failure prone at best, and completely inadequate under the worst circumstances. Further, existing methods do not provide an understanding of the drivers behind the success or failure of savings plans. This lack of insight, combined with a deficient framework, contributes to the adverse outcomes experienced by many pension plans and individuals. In this paper, we will introduce a new perspective on modeling savings, that borrows extensively from the field of hydrology. To accomplish this, we will apply a modified version of mathematical techniques used by hydrologists in dam building, to savings and retirement planning. Our goal is to present an intuitive decision framework, based on a novel concept. In the process, we hope to open a new path in the dialogue to improve the state of the art in savings and retirement planning.

Journal Of Investing

November 2002

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The size of a portfolio, measured by the number of holdings, is a very important factor in active management. The number of holdings in a portfolio plays a significant role in whether or not the excess return of the strategy is captured. In addition, portfolio size has a considerable impact on the variability of the outcomes; that is whether or not the tracking error between the portfolio and the underlying strategy is minimized. Yet the number of positions held in a portfolio is seldom the topic of a deliberate study by active managers. In this article we will analyze the questions related to ideal portfolio size from three perspectives: as a statistical sampling problem, as the outcome of the fundamental law of investing and as the result of iterative simulations. In the process we hope to not only demonstrate the critical importance of actively selecting the number of holdings for a given strategy but also introduce a set of tools for this purpose.