Risk Measurement
[this page | pdf | references | back links]
Key to effective investment management is an appropriate
understanding and management of the risks being run within the portfolio.
Portfolio risk measurement is a more mathematical discipline than performance
measurement and attribution but can also be potentially quite data
intensive. Nematrian web functions that may be particularly relevant for risk
measurement and risk management are listed on the Risk Management Functions
page.
An introduction to the theory (and some of the practice) of
risk measurement and management is provided by Kemp (2005)
and Kemp (2009).
A glossary of terms often used in an asset management and pension fund context
is set out in a Glossary.
For further details on risk attribution please see the Risk Attribution Theory
pages. The most common axiomatic way of developing risk measurement theory
involves the concept of a Coherent risk
measure, even if one of the most common risk measures used in practice, Value-at-Risk, is coherent
only for a relatively limited range of probability distributions.
Also of interest to readers of this page may be the
Nematrian pages on Portfolio
Optimisation, Random
Matrix Theory, Clustering
techniques for universe selection, Measuring
the Average Correlation of Stocks in a Universe and Liquidity
Risk.
Readers of Kemp (2009)
will appreciate that for some types of risk measurement (particularly ones that
aim to price risk consistently with prices in the market, it is important to
calibrate risk models to market data. An elaboration of mathematics that can be
arise in such circumstances is set out in Calibrating
probability distributions used for risk measurement purposes to market-implied
data.
References
Kemp, M.H.D. (2005).
Risk Management in a Fair Valuation World. British Actuarial Journal, 11,
No. 4, pp. 595-712
Kemp, M.H.D.
(2009). Market consistency: Model calibration in imperfect markets.
John Wiley & Sons [for further information on this book please see Market Consistency]