About Us

This page provides a brief description of this Web site, followed by an overview of our investment and analytical philosophy.

About this Web Site

This Web log (“blog”—-an online journal) and the Web site behind it both describe an intermarket, multi-cap, style-variable investment strategy based on Stracia, a philosophy and comprehensive decision-making framework for global portfolio management.

We analyze the global equity, fixed-income, futures/commodities, currency, and derivatives markets for trading and investment opportunities, and publish our thoughts and—-soon, portfolio changes—-to a blog that, like our public discussion forum, is open to all visitors.

Please feel free to explore the site; you are welcome to read or post comments to our blog and the public forum.

The site is optimized to run on the following browsers: Internet Explorer 5.5+, Mozilla Firefox, Google Chrome, and Safari. Click to upgrade to Mozilla Firefox (a good, free browser, available in over 40 languages).

Our Thought Process and Philosophy

Stracia, which is an abstract abbreviation for strategic, cross-category investment allocation, consists of formalized strategies designed to determine optimal thresholds for the rotation of assets among categories as well as the timing of such decisions.

It is a framework for analyzing the markets—by no means a “golden key” or purely mechanized trading system—and it is designed to support a global, multi-strategy, process-based approach to portfolio management.

Specifically, Stracia represents the practical application of sound macroeconomic and “macro-market” theories, described at length throughout this Web site and in various of the blog entries, which support the selection of assets among the stock, bond, futures/commodity, currency, and derivatives markets, as well as the rotation of assets among these markets. Its focus is on learning to anticipate directionality in these markets as a preliminary step to evaluating long/short investment decisions based on intrinsic value analyses and (to a lesser extent) short-term momentum considerations.

Most importantly, Stracia provides a context in which to understand and react to changing macroeconomic and market dynamics on a continuous basis, due to its grasp of both historical market phenomena and practical applications of theory informing performance expectations. Stracia is therefore a probative analysis of what works over the course of an investment cycle; an intellectual framework that explains why; and a process for managing all of the information necessary to make sound, well-informed investment decisions for a multi-cap, multi-strategy, style-variable, international approach.

At its foundation, Stracia is an investment philosophy: Its purpose is to pursue both beta and alpha returns by articulating buy and sell decisions based on critical analyses of how market and macroeconomic conditions may effect the expected performance of various asset classes. It stresses fundamental research supported by rigorous quantitative research methods. On another, nuts-and-bolts level, it is a collection of optimization algorithms, statistical techniques, and valuation methodologies—software—designed to measure and express the credence of this philosophy in quantitative terms. So it is both an intellectual system for approaching trading decisions and the proprietary algorithms—the process—that supports the approach.

It may also be useful to stress what Stracia is not. It is not an automated investment system or “some kind of robot” that seeks to remove the investment manager from the decision-making process, or to replace his own judgment with merely mechanized trading rules or signals. (Most especially, it is not some “elite” investment product or black-box that will help you “make money now!,” “discover cheap stocks!,” etc., etc.) Rather, the emphasis is on using quantitative models to add substantive understanding to what the manager already knows (or to challenge his convictions) about the nature of cross-category asset-class performance, to provide a framework for understanding how asset classes outside of a manager’s specific investment mandate may impact his holdings universe, and to add to his total, qualitative knowledge of these relationships and their expected impact on portfolio performance.

Stracia is designed to support competitive decision-making and as such (and as mentioned), could be used either as the foundation for a global, multi-strategy hedge-fund approach, or to support a fund-of-funds or separately managed accounts (SMA) strategy. More generally, it could be used to support active-indexing or passive-rotation (sector, high-low quality) strategies.

We have endeavored to make Stracia as fully articulated as possible through the creation of several dozen proprietary models. These models consist of three kinds:

  • number-crunching subroutines that either compare time series to one another or conduct stochastic simulations—such as on asset returns, economic or other trend data;
  • risk/return optimizers that incorporate the subroutines’ results at the decision level, supporting our own buy/sell decisions (we do not make investment recommendations); and
  • artificial neural networks.

Models of the first type are generally bivariate, yielding results independent of other subroutines and thereby allowing the manager to evaluate the expected impact of market-moving economic events as they develop and (if desired) in isolation; models of the second type are backward-looking optimizers, translating the output of individual subroutines into a coördinated execution strategy; and the neural networks are generally of the supervised, backward-propagation, or backprop, variety.

Much of this Web site is concerned with describing the use of these models and the interpretation of their results in detail. Since they are the core of the Stracia framework, they deserve a brief introduction.

A Thing Is What It Does: What Does Stracia Do?

The Stracia process starts with certain assumptions about the means by which capital markets allocate resources; tests those assumptions by constructing and back-testing the performance of thousands of hypothetical investment portfolios; uses statistical and other “portfolio durability” techniques to determine the profit-potential of these results on a historical basis, as well as their statistical significance and general adequacy; and finally, supports decision-making in the here-and-now based on these analyses.

Thus, one of Stracia’s virtues is that it breaks the investment process into discrete, manageable chunks: intermarket and macro-economic analyses support the asset allocation process; risk-based analyses of dozens of economic and market indicators support a long-term strategy for market entry and exit; and equity valuation models support individual stock picking in both growth and value contexts—all for the purpose of improving risk-adjusted performance.


Each of the models submits thousands of data points to proprietary algorithms. As noted, the data are typically time series: for example, historical market performance relative to some real-world trend, as measured by an economic indicator. The algorithms, in turn, apply many millions of calculations to the various data sets—including regression analyses and portfolio optimization routines—before finally submitting the results to a framework for coördinated long/short investment allocation among the stock, bond, commodity, currency, and derivative products markets.

The models support portfolio rebalancing with whatever periodicity is required, from daily adjustments to weekly, monthly, quarterly, etc.

The ultimate objective of the modeling process is to make readily actionable those data points that are truly meaningful, supporting a supple, responsive, and forward-looking decision process. Most single data points or releases will not have a major impact on portfolio construction, though many do inform allocation decisions at the margin.

As stated above, the Stracia process encompasses the what of investing: a set of analytical subjective techniques that are tested or qualified using objective modeling methods, supporting specific asset-category decisions at any point in time. However quantitative the approach, of course, it is still largely subjective, as we remain free to interpret the results of the models in the context of economic and market dynamics that, with each new cycle, are unique.

Therefore, Stracia also encompasses the why of investing: the underlying rationale supporting a given asset-allocation stance and more generally, for expecting past relationships to influence future asset performance—or not. The models support Stracia’s explanatory or intellectual aspect. They justify the philosophy and make it actionable.

It is worth repeating that though it may be described as a “system,” Stracia is a system of thought—a framework for action—but not an expert system or “thinking machine.” Neither is it some sort of stock-picking engine: Two independent users of this site may, at any given time, be expected to draw similar conclusions about appropriate asset allocation among investment categories and sectors. But they would still be expected to select different security baskets populating those strategies.

So in summary, this Web site describes the Stracia investment philosophy in the context of the models’ specific results. The algorithms consist principally of proprietary computer code, optimizers and scenario analysis procedures, and customized Monte Carlo simulators; but their nuts-and-bolts explanation, and our software modeling philosophy in general, are beyond the scope of this introduction and inconsistent with the site’s objectives, which are to rationalize an intermarket portfolio strategy and to describe the strategy that we currently expect to yield superior risk-adjusted results. (That said, we do occasionally elaborate on some fundamental considerations that went toward the development of this software.)

While Stracia is capable of expressing an intermarket portfolio management strategy from the ground up, the reader can also use it to tweak her own strategy. For example, a manager considering increasing her exposure to foreign equity markets may employ Stracia’s techniques for eliminating certain kinds of political and country risk, the better to focus on those regions that Stracia determines most investment-worthy based on its well-defined, qualitative and quantitative geopolitical risk and elimination criteria (filters).

Organization of this Site

We begin with a top-down analysis of current economic and market conditions, then proceed through discussions of the various asset classes, from currencies to commodities, stocks, bonds, and derivatives. In each class-specific section, we propose and discuss various long/short ideas that are based on bottoms-up analyses of specific securities and market sectors. Since these ideas are only as valuable as the profits they generate, we also describe specific trading techniques for entering and exiting positions, risk expectations at current price levels, etc.

The business-cycle section demonstrates the importance of the cycle and intermarket phenomena to portfolio performance.

Because no equity strategy is complete without a thesis covering the bond, commodity, and currency markets, we describe the fundamental relationships among markets and certain cyclical phenomena that dramatically influence stock prices.

We then describe how these intermarket and macro-economic factors—in conjunction with fundamental analysis and certain techniques for managing positions—may be used to improve portfolio quality. We explore each market from a variety of perspectives, including its relationships to other investment categories, its behavior at different stages of the business cycle and in terms of the indicators most useful for measuring its fundamental trends and expected direction. The principal focus throughout is on the stock market. Finally, because derivative instruments can enhance a portfolio’s risk/return characteristics, both in terms of its expected alpha and as hedges against deterioration in the underlying asset, derivative strategies are considered in turn.

This site contains no actual investment recommendations. Rather, it contains only ideas for how one may generally consider approaching long/short decisions, and discusses these ideas in the broader context of cyclical, intermarket analysis—which conclusions are subject to changing “on a dime” and throughout the period that this report may circulate. Thus, these discussions are intended only to demonstrate how this type of analysis may be used to support actual decision-making; no such discussion should be considered appropriate for any specific investor. Please read the disclaimer.

Thank you for visiting Stracia, where the focus is on asset allocation and idea generation for global portfolio management.

Go to Main Page (the Blog)