CHRMs - Customised Hybrid Risk Models

If you can’t measure it, you can’t manage it.

While the range of off-the-shelf risk models is impressive, no single risk model can capture the investment styles of all managers or all portfolios. Only a risk model that reflects how the manager selects factor and stock exposures can identify and measure all the sources of risk in a portfolio and avoid under-estimating risk.

Using a customised risk model enables an investment manager to explicitly identify and quantify the various exposures being made in his or her portfolio, in terms that correspond directly to their investment process. The model will clearly show whether the manager is making any significant factor bets besides those that were intended.

R-Squared builds Customised Hybrid Risk Models (CHRMs) to correspond to each portfolio manager’s particular investment process. This provides an analysis of portfolio risk explicitly in terms of the exposures that the manager had in mind when constructing the portfolio. Since CHRMs are hybrid risk models, combining both defined and statistical factors, they also give a more accurate forecast of the overall risk of the portfolio than standard risk models.

Our risk models are Customised in almost every respect, from the extent of the stock universe included and the industry classification used, to the definition and ordering of the specified factors

R-Squared’s risk models are Hybrid in the sense that they combine the use of both specified factors and statistical factors.

Most risk models are based on a set of specified factors chosen by the vendor. Such models have the obvious advantage that the portfolio risk analysis is then expressed in terms of factors that can be clearly understood – even though they may not necessarily relate directly to the bets the manager had in mind when building the portfolio.

However, such models also have the potential drawback that the particular set of factors chosen may not capture all the common factor effects at work in the portfolio, thus leading to a mis-estimation of its risk.

Statistical factor models, on the other hand, are more likely to capture all the significant common factor effects at work in the portfolio, but suffer from the obvious disadvantage that their portfolio risk analysis is not easily interpretable in real-world terms that have economic or intuitive meaning.

The Hybrid approach captures the best of both worlds, in that it includes recognisable specified factors, which will usually capture most of the common factor effects at work in the portfolio, but also uses a small number of statistical factors to capture any other (possibly transient) common factor effects present in the stock returns data.

R-Squared’s risk models are Customised in almost every respect, from the scope of the stock universe included and the industry classification used to the definition and ordering of the specified factors.

Typically, these would include both the particular common factor bets that the manager intends to make, as well as any other common factors that the manager wishes to monitor or control explicitly.

Any remaining common factor effects are captured by statistical factors, which enable the manager to check that their portfolios are neutral with respect to these other factors, and that there are no unintended factor bets.

Custom Hybrid Risk Models users have the comfort of knowing that all the common factor risk has been accounted for (at least to the desired level of accuracy, depending on the number of statistical factors selected), and that the stock specific risk really is stock specific.

How it works

  • We begin by meeting you to talk about your investment objectives, investment style, investable universe and constraints.
  • This takes into account your investment process, including rebalancing frequency, decision rules and cash-flow management.
  • We then prepare draft model specifications, including the factor hierarchy, update frequency and model universe as well as functional specifications such as optimisation and reverse optimisation.
  • When the specifications are agreed we build a beta version of the risk model for testing and final modification prior to building the production version.

The process usually takes between one and three months.
 

 

Customised Hybrid Risk Models (CHRMs)

Overview document for R-Squared's Customised Hybrid Risk Models.