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Risk Attribution Framework
› Risk attribution is not a new concept. The term stems from
the term "return attribution" or "performance attribution",
which is a process of attributing the return of a portfolio to
different factors according to active investment decisions.
The purpose is to evaluate the ability of asset managers. The
literature on return attribution or performance attribution
started in the 60s,2 when mutual funds and pension funds
were hotly debated. Whereas the literature on risk attribution,
which is related to return attribution, didn’t start until the mid
90’s. Risk attribution di¤ers from return attribution 5 in two
major aspects. First, as is clear from their names, the
decomposing objectives are risk measures for the former and
returns for the latter. Second, the latter uses historical data
and thus is ex-post while the former is an ex- ante analysis.
› The general framework of decomposing risk measures
was …rst introduced by Litterman (1996), who uses the fact
that the volatility, de…ned as the standard deviation, of a
portfolio is linear in position size. His …nding is generalized
to risk measures that possess this property, which we call
later positive homogeneity. We shall formally de…ne the
general measure of risk.
› We are more interested in risk measures which have the
property of posi- tive homogeneity because this is one of
the properties possessed by the class of coherent
measures, which we de…ne in the next section. In
Litterman’s framework, positive homogeneity plays a
central role in decomposing risk measures into
meaningful components. When all position sizes are
multi- plied by a common factor k > 0, the overall
portfolio risk is also multiplied by this common factor. As
we can see from the following proposition that each
component can be interpreted as the marginal risk
contribution of each individual asset or a subset of
assets in the portfolio from small changes in the
corresponding portfolio position sizes.
› 3Some authors use the term positive homogeneity for
simplicity to mean the case when 1; i.e. the risk measure
is homogeneous of degree one. But this term can cause
confusion in some cases thus is not adopted in this
paper.
› Deviding both sides of the above equation by k􀀀1 gives
the result. In particular, we are more interested in the
case when = 1, since most widely used risk measures fall
into this category. The above proposition (known as the
Euler’s Formula) is fundamental in risk attribution. It
facilitates identifying the main source of risk in a
portfolio.
› is called marginal risk which represents the marginal
impact on the overall risk from a small change in the
position size of asset i, keeping all other positions …xed. If
the sign of marginal risk of one asset is positive, then
increasing the position size of the asset by a small
amount will increase the total risk; If the sign is negative,
then increasing the position 4Tasche (1999) has a slightly
more general assumption. He shows that if the risk
measure is 􀀀homogeneous, continuous and partially
di¤erentiable with respect to mi; i = 2; : : : ;N; then it is
also di¤erentiable with respect to m1: 7size of the asset
by a small amount will reduce the total risk. Thus the
asset with negative marginal risk behaves as a hedging
instrument.
› But there is one important limitation of this approach ([16]). The
decomposition process is only a marginal analysis, which implies that
only small changes in position sizes make the risk contribution terms
more meaningful. For example, if the risk contribution of asset one–in a
portfolio consisting of only two assets–is twice that of asset two, then a
small increase in the position of asset one will increase the total risk
twice as much as the one caused by the same amount of increase in
asset two’s position. However, it doesn’t imply that removing asset one
from the portfolio will reduce the overall risk by 2/3. In fact, the marginal
risk and the total risk will both change as the position size of asset one
changes. This is because of the de…nition of marginal risk.
› Only if an increase (say "1) in asset one’s position size is small enough,
the additional risk, or incremental risk,5 can be approximated by @(X)
@m1"1:6 The larger "1 is, the poorer the approximation would be.
Removing asset one entirely represents a large change in the position
size and thus the approach is not suitable in this situation.
Contact us
› Website : http://www.indxx.com/analytics.php
› Address:
› USA: 470 Park Avenue South, Suite 8S
New York, NY 10016
1 844 55 INDXX (46399)
› India: 930 B3, Spaze I Tech Park,
Sec-49, Sohna Road,
Gurgaon 122018
+91 124 4291430/31
› UK: 40 Bank Street, 30th Floor,
London E14 5NR
+44 (0) 203 290 3623

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Risk Attribution Framework

  • 2. › Risk attribution is not a new concept. The term stems from the term "return attribution" or "performance attribution", which is a process of attributing the return of a portfolio to different factors according to active investment decisions. The purpose is to evaluate the ability of asset managers. The literature on return attribution or performance attribution started in the 60s,2 when mutual funds and pension funds were hotly debated. Whereas the literature on risk attribution, which is related to return attribution, didn’t start until the mid 90’s. Risk attribution di¤ers from return attribution 5 in two major aspects. First, as is clear from their names, the decomposing objectives are risk measures for the former and returns for the latter. Second, the latter uses historical data and thus is ex-post while the former is an ex- ante analysis.
  • 3. › The general framework of decomposing risk measures was …rst introduced by Litterman (1996), who uses the fact that the volatility, de…ned as the standard deviation, of a portfolio is linear in position size. His …nding is generalized to risk measures that possess this property, which we call later positive homogeneity. We shall formally de…ne the general measure of risk.
  • 4. › We are more interested in risk measures which have the property of posi- tive homogeneity because this is one of the properties possessed by the class of coherent measures, which we de…ne in the next section. In Litterman’s framework, positive homogeneity plays a central role in decomposing risk measures into meaningful components. When all position sizes are multi- plied by a common factor k > 0, the overall portfolio risk is also multiplied by this common factor. As we can see from the following proposition that each component can be interpreted as the marginal risk contribution of each individual asset or a subset of assets in the portfolio from small changes in the corresponding portfolio position sizes.
  • 5. › 3Some authors use the term positive homogeneity for simplicity to mean the case when 1; i.e. the risk measure is homogeneous of degree one. But this term can cause confusion in some cases thus is not adopted in this paper.
  • 6. › Deviding both sides of the above equation by k􀀀1 gives the result. In particular, we are more interested in the case when = 1, since most widely used risk measures fall into this category. The above proposition (known as the Euler’s Formula) is fundamental in risk attribution. It facilitates identifying the main source of risk in a portfolio.
  • 7. › is called marginal risk which represents the marginal impact on the overall risk from a small change in the position size of asset i, keeping all other positions …xed. If the sign of marginal risk of one asset is positive, then increasing the position size of the asset by a small amount will increase the total risk; If the sign is negative, then increasing the position 4Tasche (1999) has a slightly more general assumption. He shows that if the risk measure is 􀀀homogeneous, continuous and partially di¤erentiable with respect to mi; i = 2; : : : ;N; then it is also di¤erentiable with respect to m1: 7size of the asset by a small amount will reduce the total risk. Thus the asset with negative marginal risk behaves as a hedging instrument.
  • 8. › But there is one important limitation of this approach ([16]). The decomposition process is only a marginal analysis, which implies that only small changes in position sizes make the risk contribution terms more meaningful. For example, if the risk contribution of asset one–in a portfolio consisting of only two assets–is twice that of asset two, then a small increase in the position of asset one will increase the total risk twice as much as the one caused by the same amount of increase in asset two’s position. However, it doesn’t imply that removing asset one from the portfolio will reduce the overall risk by 2/3. In fact, the marginal risk and the total risk will both change as the position size of asset one changes. This is because of the de…nition of marginal risk. › Only if an increase (say "1) in asset one’s position size is small enough, the additional risk, or incremental risk,5 can be approximated by @(X) @m1"1:6 The larger "1 is, the poorer the approximation would be. Removing asset one entirely represents a large change in the position size and thus the approach is not suitable in this situation.
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