Our Investment Process
Our Investment Process (IP) aims at implementing the main tenets of our Investment Philosophy. In particular, our decision making process is design in such a way as to (i) avoid dependence on “hunches” or “emotions”, (ii) take into account both market fundamentals as well as changes in perception about them, (iii) be structured, disciplined and sensitive to the arrival of new information.
More specifically, IP’s main goals are (i) to identify the risk factors that are likely to affect the major asset classes in the near future, (ii) to assess their likelihoods and (iii) to evaluate their impacts. To achieve these desiderata, IP employs a variety of sub-procedures which may be classified in two broad categories, namely the so-called qualitative and quantitative ones.
The qualitative procedures rely on thorough analysis on current economic conditions (both at the macro and micro levels), which in turn forms the basis for forecasting changes in market’s expectations about the evolution of prices of different asset classes.
These procedures are based on statistical and econometric models which aim at producing forecasts for (i) key macroeconomic variables, (ii) changes in market trends with special emphasis on market momentum at the macro level, (iii) the direction of looming economic surprises.
At the center of IP lies our Investment Committee whose aim is to merge the information coming from the Qualitative and Quantitative procedures into a single active asset allocation decision. The “merging of information” step is a critical one, designed to represent the tendencies, trends and beliefs of the market at each particular point in time. Each member of the Investment Committee acts independently of each other, so that potential biases stemming from “herding-type behavior” or “artificially correlated beliefs” are mitigated.
Risk Management and Risk Monitoring – Stress Testing
Any given portfolio of risky assets exhibits certain risk/return characteristics. Our Investment Procedure, outlined above, aims at minimizing portfolio risk for any given level of expected returns. Nonetheless, a certain amount of risk is unavoidable. In order to quantify and manage this residual risk, a particular set of procedures is required. To this end, we have developed algorithmic procedures that assess whether given current and anticipated economic conditions the portfolio risk is indeed minimized. However, this is not the end of the story. Economic and market conditions often turn out to be quite different than those currently anticipated. This situation brings about the following question: How will the portfolio behave if such unanticipated (and possibly extreme) conditions materialize? To answer this question we have developed stress-testing methods which examine portfolio performance under severe conditions. More specifically, using computer simulations we create alternative sets of unfavorable market conditions and examine portfolio reactions under each of those sets. If we identify a set of such unfavorable, still plausible conditions that increase portfolio risk to unacceptable limits, then we adapt our asset allocation decisions in a manner that brings the overall portfolio risk back to normal levels. This type of analysis constitutes a sine qua non condition for mitigating portfolio risk in bad times.