Check out the signboard for The Spaulding Group's PMAR Conference, to be held next week in Philadelphia!  As you can see, our theme is superheroes!  There is still space, if you want to attend, contact Patrick Fowler or Chris Spaulding!

What Risk Measures Are Covered in the CIPM Curriculum?

A former student (and CIPM certificant) from The Spaulding Group's CIPM Prep Courses asked me what risk and risk-adjusted performance measures are now covered in the CIPM curriculum.  I thought it was a good question, given the list has grown considerably over the last few years.  So... here's what that list now looks like (2013 examination window). 

Note #1:  The lighter font is meant to indicate measures covered in the Expert Level curriculum, whereas the black font indicates measures covered in the Principles Level curriculum.

Note #2:  The measures are covered in varying degrees.  Some are part of the Learning Outcome Statements, some are listed in the required formulas documents and some are discussed or mentioned in readings.

Risk Measures

·         Variance

·         Mean Absolute Deviation

·         Tracking Risk

·         Covariance

·         Correlation

·         Standard deviation

·         Beta

·         Semi-variance

·         Target semi-variance

·         Marginal contribution to risk

·         Contribution of asset class to portfolio risk

·         Marginal contribution to tracking risk

·         Drawdown, average drawdown

·         Maximum drawdown

·         Largest individual drawdown

·         Semi-deviation

·         Shortfall risk

·         Expected downside value

·         Downside deviation

·         Skewness

·         Kurtosis

·         Downside potential

·         Upside potential

·         Upside risk

·         Omega ratio

·         Bernardo-Ledoit ratio

·         Variability skewness

·         Ulcer index

·         Active share

Risk Adjusted Performance Measures

·         Information ratio

·         Jensen’s alpha

·         M-squared

·         Sharpe ratio

·         Treynor ratio

·         Differential return (w/ standard deviation)

·         Differential return (w/ beta)

·         Treynor and Mazuy procedure

·         Calmar ratio

·         Sterling ratio

·         Value at Risk (VaR)

·         Sortino ratio

·         Reward to VaR ratio

·         Conditional Sharpe ratio

·         Modified Sharpe ratio

·         Appraisal ratio

·         Adjusted Sharpe ratio

·         Omega-Sharpe ratio

·         Upside potential ratio

·         Prospect ratio

Risk Attribution

·         Bottom-up process, absolute returns

·         Bottom-up process, excess returns

·         Top-down process, excess returns

·         Factor exposure, absolute returns

·         Factor exposure, excess returns

Will You Join the Superheroes of Performance Measurement?

 

Read all about the Superheroes of Performance Measurement here!

(and yes, that's me on the left!)

Expert Level - Common Themes #1: Standard Deviation, Downside Deviation and Tracking Error

It may seem that the list of formulae to memorize for the CIPM Expert Level exam is quite long, but three of the risk measurement formulas are essentially three different applications of the same formula.

Expert level candidates are responsible for knowing the formulae for the following risk statistics:

• standard deviation
• downside deviation
• tracking error

Consider the formulae for each of these:
If you accept and understand that the standard deviation formula measures variability in an account's historical returns, then downside deviation and tracking error are variations of that idea:

• Downside deviation uses the same formula as standard deviation, except that it measures variability in the downside (i.e., losing returns). Losing returns are defined as those that fall below the pre-defined target return T. Thus, T replaces the average return in the standard deviation formula. The other modification to the formula is that any observations that are at or above the target return are treated as having a distance from the target of zero. We still divide by the total number of observations, N.
  

• Tracking error measures the variability of the historical excess returns. Thus, tracking error uses the same formula as standard deviation (because it is, in fact, a standard deviation), but we are using the excess return in each period rather than the account's return in each period as the input data.

Given this, candidates have a couple of different ways to approach these formulae:

1. You can memorize the individual formulae
2. You can memorize the formula for standard deviation, and learn the three different applications for it.

Every candidate learns differently, but I recommend the latter approach be used, as it will give you a more comprehensive understanding of the material.