U.S. patent application number 14/706648 was filed with the patent office on 2015-11-19 for calculating liquidity margin requirements.
The applicant listed for this patent is CHICAGO MERCANTILE EXCHANGE INC.. Invention is credited to Evren Baysal, Kailin Ding, Nick Li, Panos Xythalis, Alice Yang.
Application Number | 20150332403 14/706648 |
Document ID | / |
Family ID | 54538922 |
Filed Date | 2015-11-19 |
United States Patent
Application |
20150332403 |
Kind Code |
A1 |
Baysal; Evren ; et
al. |
November 19, 2015 |
Calculating Liquidity Margin Requirements
Abstract
Systems and methods are provided for calculating margin
requirements and stress testing exposures of cleared credit
portfolios. These margin requirements are calculated using the
following components: spread risk, idiosyncratic risk, interest
rate, and liquidity risk. The calculation of these risk components
is accomplished with a detailed statistical analysis of the risk
factors underlying instruments, such as a credit default swap
instrument.
Inventors: |
Baysal; Evren; (Chicago,
IL) ; Ding; Kailin; (Chicago, IL) ; Li;
Nick; (Chicago, IL) ; Xythalis; Panos; (Scotch
Plains, NJ) ; Yang; Alice; (Chicago, IL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
CHICAGO MERCANTILE EXCHANGE INC. |
Chicago |
IL |
US |
|
|
Family ID: |
54538922 |
Appl. No.: |
14/706648 |
Filed: |
May 7, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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61994624 |
May 16, 2014 |
|
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61994611 |
May 16, 2014 |
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Current U.S.
Class: |
705/36R |
Current CPC
Class: |
G06Q 40/04 20130101;
G06Q 40/06 20130101 |
International
Class: |
G06Q 40/06 20060101
G06Q040/06 |
Claims
1. A system comprising: a data repository storing portfolio
information; a liquidity margin computing device communicatively
coupled to the data repository, the liquidity margin computing
device comprising: a processor; and a non-transitory memory device
storing instructions that, when executed by the processor, cause
the liquidity margin computing device to: calculate a hedge cost
associated with a credit default swap (CDS) portfolio; calculate a
liquidation cost associated with the CDS portfolio; and calculate
an aggregate liquidity charge for the CDS portfolio based on the
hedge cost and the liquidation cost.
2. The system of claim 1, wherein the non-transitory memory device
stores further instructions that, when executed by the processor,
cause the liquidity margin computing device to: calculate a cost of
a dollar value of a 1 basis point change in spread (SDV01) hedge
associated with the CDS portfolio.
3. The system of claim 2, wherein the cost of the SDV01 hedge
associated with the CDS portfolio comprises at least one of a cost
of a SDV01 hedge for an investment grade CDS sub-portfolio and a
cost of a SDV01 hedge for a high-yield CDS sub-portfolio.
4. The system of claim 1, wherein the non-transitory memory device
stores further instructions that, when executed by the processor,
cause the liquidity margin computing device to: retrieve, via a
network, first information associated with an investment grade (IG)
sub-portfolio of the CDS portfolio and second information
associated with a high-yield (HY) sub-portfolio of the CDS
portfolio from the data repository; calculate a hedge cost of a
dollar value of a 1 basis point change in spread (SDV01) hedge of
the IG sub-portfolio based on the first information and a hedge
cost of the SDV01 hedge of the HY sub-portfolio.
5. The system of claim 1, wherein the hedge cost corresponds to: a
cost of hedging an aggregate dollar value of a 1 basis point change
in spread (SDV01) exposure of investment-grade (IG) indices and IG
single names; and a cost of hedging an SDV01 exposure of high-yield
(HY) indices and HY single names
6. The system of claim 1, wherein the non-transitory memory device
stores further instructions that, when executed by the processor,
cause the liquidity margin computing device to: calculate a cost
associated with liquidating hedged index positions of the CDS
portfolio.
7. The system of claim 1, wherein the non-transitory memory device
stores further instructions that, when executed by the processor,
cause the liquidity margin computing device to: calculate a cost
associated with liquidating hedged single-name positions of the CDS
portfolio.
8. The system of claim 1, wherein the non-transitory memory device
stores further instructions that, when executed by the processor,
cause the liquidity margin computing device to: calculate a cost
associated with liquidating hedged index positions of the CDS
portfolio; and calculate a cost associated with liquidating hedged
single-name positions of the CDS portfolio.
9. The system of claim 8, wherein the cost associated with
liquidating hedged index positions of the CDS portfolio corresponds
to a function of the SDV01 of each off-the-run or non-5 year index
series position of the CDS portfolio and the cost associated with
liquidating hedged single-name positions corresponds to a function
of the SDV01 of each single name position.
10. The system of claim 1, wherein the liquidation cost of the CDS
portfolio scales super linearly when the position of a notional is
greater than a criterion.
11. The system of claim 10, wherein the criterion corresponds to a
proportion of a median weekly trading volume of an index series an
tenor combination of a hedged index position or a proportion of the
median weekly trading volume of a reference entity and tenor
combination of a hedged single name position.
12. A non-transitory computer readable medium storing instructions
that, when executed by a processor, cause the processor to:
calculate a hedge cost associated with at least one of an
investment grade (IG) sub-portfolio and a high-yield (HY)
sub-portfolio of a credit default swap (CDS) portfolio; calculate a
liquidation cost associated with hedging at least one of an index
position and a single-name position held in the CDS portfolio; and
calculate an aggregate liquidity charge for the CDS portfolio by
combining the hedge cost and the liquidation cost.
13. The non-transitory computer readable medium of claim 12,
further storing instructions that, when executed by the processor,
cause the processor to: retrieve, via a network, first information
associated with the IG sub-portfolio of the CDS portfolio and
second information associated with a high-yield HY sub-portfolio of
the CDS portfolio from a data repository;
14. The non-transitory computer readable medium of claim 12,
further comprising instructions that, when executed by a processor,
cause the processor to: receive, from a financial market computing
system, pricing information corresponding to the CDS portfolio; and
calculate the aggregate liquidity charge based, at least in part,
on the pricing information across tenors.
15. The non-transitory computer readable medium of claim 14,
further comprising instructions that, when executed by the
processor, cause the processor to: receive, from the financial
market computing system, trading volume information; and calculate
the aggregate liquidity charge based, at least in part, on the
trading volume information.
16. A method comprising: calculating, by an outright exposure
calculator, an outright exposure to an investment grade (IG)
sub-portfolio of a credit default swap (CDS) portfolio;
calculating, by the exposure calculator, an outright exposure to a
high yield (HY) sub-portfolio of the CDS portfolio; calculating, by
a basis exposure calculator, at least one of a basis exposure to an
index-based CDS sub-portfolio and a single name CDS sub-portfolio
of the CDS portfolio; calculating, by a liquidity charge
calculator, a liquidity charge corresponding to the CDS portfolio
based on the outright exposure of the IG sub-portfolio, the
outright exposure of the HY sub-portfolio and the basis exposure of
the CDS portfolio.
17. The method of claim 16, comprising: receiving, via a network,
market information associated with the CDS portfolio; adjusting, by
the basis exposure calculator, the basis exposure based on the
market information.
18. The method of claim 16, comprising: calculating, by a tenor
calibrator, a tenor scalar based on a ratio of Bid/Ask spreads
across tenors associated with the CDS portfolio; calculating, by
the tenor calibrator, a tenor adjustor associated with weekly
volume of swaps associated with the CDS portfolio based on the
market information.
19. The method of claim 18, comprising: calculating, by the tenor
calibrator, the tenor scalar based on Bid/Ask spreads for IG and HY
CDS across different series.
20. The method of claim 19, wherein the Bid/Ask spreads are
associated with 3-year, 5-year, 7-year, and 10-year tenor IG credit
default swaps and 5-year tenor HY credit default swaps associated
with the CDS portfolio.
Description
[0001] This application claims priority to Provisional Application,
U.S. Ser. No. 61/994,624, filed May 16, 2014 and to Provisional
Application, U.S. Ser. No. 61/994,611, filed May 16, 2014 which are
both incorporated herein by reference in their entirety.
FIELD OF THE INVENTION
[0002] Aspects of the invention relate to determining risks and
margin requirements. More particularly, aspects of the invention
relate to determining costs associated with liquidity risks using a
risk model for cleared credit.
BACKGROUND
[0003] Exchanges are typically associated with clearing houses that
are responsible for settling trading accounts, clearing trades,
collecting and maintaining performance bond funds, regulating
delivery and reporting trading data. Clearing is the procedure
through which the clearing house becomes buyer to each seller of a
contract, and seller to each buyer, and assumes responsibility for
protecting buyers and sellers from financial loss by assuring
performance on each contract. This is effected through the clearing
process, whereby transactions are matched.
[0004] Clearing houses establish clearing level performance bonds
(margins) for traded financial products and establishes minimum
performance bond requirements for customers. A performance bond,
also referred to as a margin, is the funds that may be required to
deposited by a customer with his or her broker, by a broker with a
clearing member or by a clearing member with the clearing house,
for the purpose of insuring the broker or clearing house against
loss on open contracts. The performance bond is not a part payment
on a purchase and helps to ensure the financial integrity of
brokers, clearing members and exchanges or other trading entities
as a whole. A performance bond to clearing house refers to the
minimum dollar deposit which is required by the clearing house from
clearing members in accordance with their positions. Maintenance,
or maintenance margin, refers to a sum, usually smaller than the
initial performance bond, which must remain on deposit in the
customer's account for any position at all times. In order to
minimize risk to an exchange or other trading entity while
minimizing the burden on members, it is desirable to approximate
the requisite performance bond or margin requirement as closely as
possible to the actual risk of the account at any given time.
[0005] Risks and margin requirements can be difficult to determine
for illiquid and concentrated positions. Illiquid positions do not
allow a clearing house to quickly liquidate positions, which makes
it difficult to value risks. Concentrated positions can make it
difficult for a clearing house or other entity to find a buyer or
seller. Accordingly, there is a need in the art for systems and
methods for determining risks and margin requirements for illiquid
and concentrated positions.
SUMMARY OF THE INVENTION
[0006] Aspects of the invention overcomes at least some of the
problems and limitations of the prior art by providing systems and
methods for valuing risks and margin requirements for portfolios
that are illiquid or have concentrated positions. In some cases a
model may include four different terms which are added to yield an
aggregate liquidity charge for portfolios consisting of NA indices
(IG, HY) and single names, such as a cost of SDV01 hedge for IG
sub-portfolio, a cost of SDV01 hedge for HY sub-portfolio, a cost
of unwinding hedged index positions, and a cost of unwinding hedged
single name positions. In some embodiments of the invention the
concentration based liquidity charge includes the sum of a
concentration charge for market exposure and a concentration charge
for the basis of the portfolio.
[0007] In other embodiments, the present invention can be partially
or wholly implemented on a computer-readable medium, for example,
by storing computer-executable instructions or modules, or by
utilizing computer-readable data structures.
[0008] Of course, the methods and systems of the above-referenced
embodiments may also include other additional elements, steps,
computer-executable instructions, or computer-readable data
structures. In this regard, other embodiments are disclosed and
claimed herein as well.
[0009] The details of these and other embodiments of the present
invention are set forth in the accompanying drawings and the
description below. Other features and advantages of the invention
will be apparent from the description and drawings, and from the
claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[0010] The present invention may take physical form in certain
parts and steps, embodiments of which will be described in detail
in the following description and illustrated in the accompanying
drawings that form a part hereof, wherein:
[0011] FIG. 1 shows a computer network system that may be used to
implement aspects of the present invention;
[0012] FIG. 2 shows an illustrative liquidity charge computing
device that may be used to implement aspects of the present
invention;
[0013] FIG. 3 shows an illustrative method for determining a
liquidity charge according to aspects of the present invention;
[0014] FIGS. 4 and 5 show illustrative charts for calibrating an
aspect of the liquidity charge associated with a credit default
swap according to aspects of the present invention; and
[0015] FIGS. 6-10 show illustrative charts showing an impact on
margin accounts according to aspects of the present invention.
DETAILED DESCRIPTION
[0016] In some cases, a risk model may be used for risk management
pertaining to clearing of Credit Default Swap (CDS) and related
credit instruments, including but not limited to NA CDX indices, NA
single names, iTraxx indices, iTraxx single names, other credit
indices, futures on indices, etc.
[0017] Sources of risks arising from clearing credit default swaps
may include the cost of liquidating the CDS portfolio of a clearing
member firm in case of default. Efficient modeling and estimation
of this cost may be as important as quantifying the market risk
related costs, if not more, for credit instruments as these
instruments do have varying degrees of liquidity characteristics. A
clearing house may offer clearing services for different indices,
such as NA indices (IG and HY) and is planning to extend its
offering to iTraxx indices (Main, Cross Over), and North American
and European single names. The calculation of liquidity risk
requirements as part of margin and stress exposures may be
important to the success of a risk management model that conforms
to regulatory requirements and to the risk appetite of the Clearing
House. The liquidity risk model may, therefore, be used to provide
good coverage across a representative set of portfolios under a
comprehensive set of historical and hypothetical scenarios
representing distressed liquidity, to take into account liquidity
characteristics of credit instruments based on contract tenors,
index families and series, and reference entities. In some cases,
the liquidity risk model may also be used to consistently and
proportionately model the effect of concentration (position size),
to have a robust, intuitive and justifiable parameterization that
supports a reliable and transparent calibration and replication
process, and to be consistent with a default management
process.
[0018] In some cases, a liquidity model used by an illustrative
clearing house may address liquidity risk of portfolios consisting
of only NA indices (IG and HY). In some cases, the current
liquidity requirement may include two components which are intended
to cover the costs associated with the steps of a typical
liquidation process. The first component may be designed to cover
the cost of hedging the market exposure of a defaulted portfolio
while the second component may address the cost of liquidating the
hedged portfolio. A progressive concentration charge may implicitly
embed into the liquidity requirement through a super-linear
dependence on position size. The Bid/Ask data across different
series and tenors of index instruments may be incorporated in the
model through a liquidity floor which is intended to address the
liquidity risk of smaller size portfolios, which may be transacted
at observed Bid/Ask spreads in case of default.
[0019] A previously used risk model may not differentiate between
on-the-run and off-the-run indices and/or contracts of different
tenors as long as they have similar market risk exposures measured
by their SDV01 (spread adjusted DV01). The model therefore may not
address the drop in liquidity of index series when they become
off-the-run and the relative illiquidity of contracts on non 5-year
tenors. This characteristic of the model makes it harder to extend
to single names and other index instruments without making
significant adjustments.
[0020] Aspects of the present invention are preferably implemented
with computer devices and computer networks that allow users to
exchange trading information. An exemplary trading network
environment for implementing trading systems and methods is shown
in FIG. 1. An exchange computer system 100 receives orders and
transmits market data related to orders and trades to users.
Exchange computer system 100 may be implemented with one or more
mainframe, desktop or other computers. A user database 102 includes
information identifying traders and other users of exchange
computer system 100. Data may include user names and passwords. An
account data module 104 may process account information that may be
used during trades. A match engine module 106 is included to match
bid and offer prices. Match engine module 106 may be implemented
with software that executes one or more algorithms for matching
bids and offers. A trade database 108 may be included to store
information identifying trades and descriptions of trades. In
particular, a trade database may store information identifying the
time that a trade took place and the contract price. An order book
module 110 may be included to compute or otherwise determine
current bid and offer prices. A market data module 112 may be
included to collect market data and prepare the data for
transmission to users. A risk management module 134 may be included
to compute and determine a user's risk utilization in relation to
the user's defined risk thresholds. An order processing module 136
may be included to decompose delta based and bulk order types for
processing by order book module 110 and match engine module
106.
[0021] The trading network environment shown in FIG. 1 includes
computer devices 114, 116, 118, 120 and 122. Each computer device
includes a central processor that controls the overall operation of
the computer and a system bus that connects the central processor
to one or more conventional components, such as a network card or
modem. Each computer device may also include a variety of interface
units and drives for reading and writing data or files. Depending
on the type of computer device, a user can interact with the
computer with a keyboard, pointing device, microphone, pen device
or other input device.
[0022] Computer device 114 is shown directly connected to exchange
computer system 100. Exchange computer system 100 and computer
device 114 may be connected via a T1 line, a common local area
network (LAN) or other mechanism for connecting computer devices.
Computer device 114 is shown connected to a radio 132. The user of
radio 132 may be a trader or exchange employee. The radio user may
transmit orders or other information to a user of computer device
114. The user of computer device 114 may then transmit the trade or
other information to exchange computer system 100.
[0023] Computer devices 116 and 118 are coupled to a LAN 124. LAN
124 may have one or more of the well-known LAN topologies and may
use a variety of different protocols, such as Ethernet. Computers
116 and 118 may communicate with each other and other computers and
devices connected to LAN 124. Computers and other devices may be
connected to LAN 124 via twisted pair wires, coaxial cable, fiber
optics or other media. Alternatively, a wireless personal digital
assistant device (PDA) 122 may communicate with LAN 124 or the
Internet 126 via radio waves. PDA 122 may also communicate with
exchange computer system 100 via a conventional wireless hub 128.
As used herein, a PDA includes mobile telephones and other wireless
devices that communicate with a network via radio waves.
[0024] FIG. 1 also shows LAN 124 connected to the Internet 126. LAN
124 may include a router to connect LAN 124 to the Internet 126.
Computer device 120 is shown connected directly to the Internet
126. The connection may be via a modem, DSL line, satellite dish or
any other device for connecting a computer device to the
Internet.
[0025] One or more market makers 130 may maintain a market by
providing constant bid and offer prices for a derivative or
security to exchange computer system 100. Exchange computer system
100 may also exchange information with other trade engines, such as
trade engine 138. One skilled in the art will appreciate that
numerous additional computers and systems may be coupled to
exchange computer system 100. Such computers and systems may
include clearing, regulatory and fee systems.
[0026] The operations of computer devices and systems shown in FIG.
1 may be controlled by computer-executable instructions stored on
computer-readable medium. For example, computer device 116 may
include computer-executable instructions for receiving order
information from a user and transmitting that order information to
exchange computer system 100. In another example, computer device
118 may include computer-executable instructions for receiving
market data from exchange computer system 100 and displaying that
information to a user.
[0027] Of course, numerous additional servers, computers, handheld
devices, personal digital assistants, telephones and other devices
may also be connected to exchange computer system 100. Moreover,
one skilled in the art will appreciate that the topology shown in
FIG. 1 is merely an example and that the components shown in FIG. 1
may be connected by numerous alternative topologies.
[0028] FIG. 2 shows an illustrative block diagram representation of
a liquidity charge computing system 200 for implementing a model
for determining a liquidity charge associated with a credit default
swap (CDS) portfolio. In some cases, the liquidity charge computing
system may include a liquidity charge computing device 200
communicatively coupled via a network 205 (e.g., a wide area
network (WAN), the LAN 124, the Internet 126, etc.) to a CDS market
computing system 210. The CDS market computing system may include
one or more computing devices configured for receiving and
disseminating information corresponding to a CDS market, such as
pricing information (e.g., bid information, ask information, etc.),
CDS quality information (e.g., investment grade information, high
yield information, etc.), tenor information, and/or the like. The
liquidity charge computing device 210 may be communicatively
coupled to a clearinghouse computing system 240 via the network
205, or otherwise incorporated into the clearinghouse computing
system 240.
[0029] In some cases, the clearinghouse computing system 240 may
include a data repository 242, one or more computing devices 244
and/or a user interface 246. The data repository may store
instructions, that when executed by the one or more computing
devices 244, may cause the one or more computing devices 244 to
perform operations associated with determining performance bond
contributions associated with holdings in products that are based
on various types of credit default swaps. In some cases, the
clearinghouse computing system 240 may present performance bond
and/or margining information to a financial institution via the
network 205, wherein the financial institution holds one or more
portfolios that include a credit default swap. Further, the
clearinghouse computing system 240 may further present the
performance bond and/or margining information via one or more user
interface screens via the user interface 246. The user interface
246 may be local to the clearinghouse computing system 240 and/or
remote from the clearinghouse computing system 240 and accessible
via the network 205. The user interface screens may graphically
and/or textually present information corresponding to a margin
requirement determined for a CDS portfolio as determined by the
liquidity charge computing device 210.
[0030] The liquidity charge computing device 210 may include a
processor 212, one or more non-transitory memory devices 214 (e.g.,
RAM, ROM, a disk drive, a flash drive, a redundant array of
independent disks (RAID) server, and/or other such device etc.), a
user interface 216, a data repository 218, a communication
interface to facilitate communications via the network 205, and/or
the like. The liquidity charge computing device 210 may be
configured to store instructions in the one or more memory devices
214 and/or the data repository 218 that, when executed by the
processor 212, may configure the liquidity charge computing device
210 to execute a model for determining margining requirements
associated with a CDS portfolio. In some cases, the liquidity
charge computing device 210 may process the instructions stored in
the memory device 214 and/or the data repository 218 to calculate
the margining requirements using an outright exposure calculator
220 and/or a basis exposure calculator 230. In some cases, the
outright exposure calculator 220 may be used to calculate an
outright exposure to liquidity charges for holdings held in a CDS
portfolio. For example, the outright exposure calculator 220 may
calculate an exposure associated with hedging an investment grade
(IG) sub-portfolio held in the CDS portfolio using an IG exposure
calculator 222. Similarly, the outright exposure calculator 220 may
calculate an exposure associated with hedging a high yield (HY)
sub-portfolio held in the CDS portfolio using a HY exposure
calculator 224. The basis exposure calculator 230 may be used to
calculate a cost of unwinding hedged positions held in the CDS
portfolio. For example, the basis exposure calculator 230 may
process instructions to calculate a cost of unwinding hedged single
name positions held in the CDS portfolio using a single name basis
exposure calculator 232. Similarly, the basis exposure calculator
230 may process instructions to calculate a cost of unwinding
hedged index positions held in the CDS portfolio using an index
basis exposure calculator 234.
[0031] The liquidity charge computing device 210 may process
instructions corresponding to model to determine a liquidity charge
and/or margin requirement associated with any particular CDS swap
portfolio. This model may be stored as instructions in the one or
more non-transitory memory devices 214 and/or the data repository
218 that, when executed by the processor 212 may cause the
liquidity charge computing device to calculate the liquidity charge
by calculating up to four different terms that may be added to
yield an aggregate liquidity charge for portfolios consisting of
indices (IG, HY) and single names, such as a cost of SDV01 hedge
for IG sub-portfolio, a cost of SDV01 hedge for HY sub-portfolio, a
cost of unwinding hedged index positions, and a cost of unwinding
hedged single name positions. In some cases, the indexes and/or
single name positions may be associated with a North American CDS
market and/or a foreign CDS market (e.g., a European CDS market, an
Asian CDS market, etc.). In some cases, a single name CDS may be
based on a swap associated with a particular single name (e.g.,
corporation). An index may include a plurality of single name
positions. As such, an index based CDS may be similar to a futures
contract and may be based on a value of an index at a given
time.
[0032] The liquidity charge computing device 210 may calculate a
cost associated with liquidating the CDS positions held in a
particular CDS portfolio. This liquidity charge may be used when
determining margin requirements for the accounts holding one or
more CDS portfolios. The liquidity charge may be calculated by the
outright exposure calculator 220 and the basis exposure calculator
of the liquidity charge computing device 210 using the formula:
Liquidity Charge=Outright exposure+Index Basis Exposure+Single Name
Basis Exposure (1)
where,
IG Outright Exposure = .alpha. IG SDV 01 IG max { SDV 01 IG / SDV
01 OTR , IG , 5 Y w ( 5 Y ) .gamma. Q 0 , OTR , IG , 5 Y 0.5 , 1 }
, ( 2 ) where SDV 01 IG = i .di-elect cons. IG IN and SN .tau.
.di-elect cons. { 1 , 3 , 5 , 7 , 10 } SDV 01 i ( 3 ) HY Outright
Exposure = .alpha. HY SDV 01 HY max { SDV 01 HY / SDV 01 OTR , HY ,
5 Y w ( 5 Y ) .gamma. Q 0 , OTR , HY , 5 Y 0.5 , 1 } , ( 4 ) where
SDV 01 HY = i .di-elect cons. HY IN and SN .tau. .di-elect cons. {
1 , 3 , 5 , 7 , 10 } SDV 01 i ( 5 ) Index Basis Exposure = .beta.
IN i .di-elect cons. IN , .tau. .di-elect cons. ( 1 , 3 , 5 , 7 ,
10 ) - IG OTR 5 Y - HY OTR 5 Y f ( .tau. ) SDV 01 i , .tau. max { Q
i w ( .tau. ) .gamma. Q 0 , i 0.5 , 1 } ( 6 ) Single Name Basis
Exposure = .beta. SN i .di-elect cons. SN .tau. .di-elect cons. ( 1
, 3 , 5 , 7 , 10 ) f ( .tau. ) SDV 01 i , .tau. max { Q i w ( .tau.
) .gamma. Q 0 , i 0.5 , 1 } ( 7 ) ##EQU00001##
[0033] Here, Q.sub.0i is a median weekly trading volume and may be
calibrated to most recent 13 weeks for the entity (e.g., single
name) and aggregated across different tenors. Q.sub.0i is a median
weekly trading volume and may be calibrated to most recent 13 weeks
for the entity (e.g., single name) and aggregated across different
tenors. The function f(.tau.) is a tenor scalar for calculating the
liquidity charge and may be based on a ratio of Bid-Ask/Mid prices
across different tenors. The function W(.tau.) is a tenor adjustor
for weekly trading volume and may be a function of f(.gamma.). The
constant .gamma. is associated with a proportion of weekly trading
volume that can be liquidated per day. This constant may be set to
any value and may be set to a same value for the different sub
portfolios (e.g., HY, IG) and/or for index basis exposure and/or
single name basis exposure. For example, .gamma. may be set to a
particular constant value for each equation (2), (4), (6), and (7)
(e.g., about 10%, about 15%, about 5%, etc.). In some cases, y may
be set to different values when determining the IG or HY outright
exposure, the Index basis exposure, and/or the single name basis
exposure.
[0034] In an illustrative example, the cost of an SDV01 hedge for
an IG sub-portfolio may represent the cost of hedging the aggregate
SDV01 exposure of IG indices and IG single names. This cost may be
measured as a function of the IG on-the-run notional required for
hedging the total SDV01 exposure of the IG sub-portfolio. The
charge scales super linearly when the hedge notional may become
relatively large compared to a proportion (e.g., about 10%) of the
median weekly trading volume of on-the-run IG 5-year contract. The
trading volume on the 5-year contract may be estimated by applying
a tenor adjustor on the total trading volume of the on-the-run IG
contracts. The tenor adjustor may be calibrated to Bid/Ask and Mid
spread data on indices.
[0035] The cost of an SDV01 hedge for an HY sub-portfolio may
represent the cost of hedging the aggregate SDV01 exposure of HY
indices and HY single names. This cost may be measured as a
function of the HY on-the-run notional required for hedging the
total SDV01 exposure of the HY sub-portfolio. The charge may scale
super linearly when the hedge notional becomes relatively large
compared to a proportion (e.g., about 10%) of the median weekly
trading volume of on-the-run HY 5-year contract. The trading volume
on the 5-year contract may be estimated by applying a tenor
adjustor on the total trading volume of the on-the-run HY
contracts. The tenor adjustor may be calibrated to Bid/Ask and Mid
spread data on indices.
[0036] A cost of unwinding hedged index positions may represent the
cost of liquidating hedged index positions. This cost may be
measured as a function of the SDV01 of each off-the-run or non-5
year index series position. The charge may scale super linearly
when the position notional becomes relatively large compared to a
proportion (e.g., about 10%) of the median weekly trading volume of
the index series and tenor combination. The trading volume of the
index series and tenor may be estimated by applying a tenor
adjustor on the total trading volume of the index series. The tenor
adjustor may be calibrated to Bid/Ask and Mid spread data on
indices.
[0037] A cost of unwinding hedged single name positions may
represent the cost of liquidating single name positions of the CDS
portfolio hedged by corresponding index positions. This cost may be
measured as a function of the SDV01 of each single name position.
The charge may scale super linearly when the position notional
becomes relatively large compared to a proportion (e.g., about 10%)
of the median weekly trading volume of the reference entity and
tenor combination. The trading volume of the reference entity and
tenor may be estimated by applying a tenor adjustor on the total
trading volume of the reference entity. The tenor adjustor may be
calibrated to Bid/Ask and Mid spread data on single names.
[0038] The liquidity model may include a number of risk aversion
parameters, (e.g., four risk aversion parameters as illustrated)
which may be associated with different terms in the liquidity
formula. These risk aversion parameters may be calibrated and/or
back-tested to dealer polls on liquidity. For example, the risk
aversion parameters may be calibrated to account for pure index CDS
portfolios and/or for single name CDS portfolios. The single name
CDS portfolios may include index positions to cover index-single
name arbitrage portfolios, and/or the like.
[0039] While the model illustrated in equations (1)-(7) may be
configured to cover liquidity exposure (e.g., risk) associated with
North American (e.g., NA) CDS markets, the model can easily be
extended to cover a liquidity risk of portfolios that may contain
other indices (e.g., a European CDS index, an Asian CDS index,
etc.) such as iTraxx. The extension of the model to cover other
product families may be achieved simply by adding terms for hedging
and unwinding such positions (after hedging). Calibration of the
risk aversion parameters for these terms may be done using dealer
polls on portfolios containing such instruments.
[0040] The model for liquidity charge for CDS portfolios, as
executed by the outright exposure calculator 220 and the basis
exposure calculator 230 of the liquidity charge computing device,
may distinguish between on-the-run/off-the-run indices and single
names based on trading volume data, where the different credit
default swaps have different levels of liquidity. The model may
also differentiate between outright and market (e.g., risk) neutral
portfolios, account for an effect of tenors associated with
different CDS swaps held in the portfolio on liquidity, and may
scale super-linearly (e.g., a 1.5 exponential equation) as a
function of notional to account for a concentration of risk. In
some cases, the model may incorporate weekly trading volume data
from the Depository Trust & Clearing Corporation (DTCC), to
differentiate between corporate obligors, on-the-run indexes,
and/or off-the-run indexes. In some cases, the model may account
for an effect of tenor on liquidity.
[0041] FIG. 3 shows an illustrative method 300 for determining a
liquidity charge according to aspects of this disclosure. As
discussed above, the liquidity charge computing device 210 may
process instructions to calculate a liquidity charge, such as by
using equation (1) discussed above. For example, at 310, the
outright exposure calculator 220 may calculate a cost associated
with a SDV01 hedge corresponding to an IG sub-portfolio of a CDS
portfolio. Similarly, at 320, the outright exposure calculator 220
may calculate a cost associated with a SDV01 hedge corresponding to
a HY sub-portfolio o the CDS portfolio. For example, a scalar value
(e.g., .alpha., .beta., etc.) may be calibrated to one or more
dealer polls associated with the representative CDS portfolios. In
some cases, the SDV01 hedge value may be calculated at the CDS
portfolio level, such as by determining an SDV01 for each position
of the portfolio. The SDV01 may be a measure of sensitivity of each
CDS to a 1% change in a power spread curve corresponding to the
contract. The IG outright exposure calculator 222 may calculate the
exposure for the IG sub-portfolio based on a SDV01 determined based
on an on-the-run CDS swap having a 5-year tenor. This SDV01
(SDV01.sub.IG) may be used to determine an amount of notional
corresponding to the on-the-run, 5-year CDS required to hedge the
SDV01 exposure of the overall IG sub-portfolio. In some cases, a
CDS may roll periodically (e.g., March, September), and in such
cases, the calculations will roll (e.g., be based on) the new
series. In some cases, an adjustment value, w(.tau.) may be used to
calibrate the calculation based on a particular tenor (e.g., a
5-year tenor). This adjustment value may be calibrated based on
dealer surveys on a periodic (e.g., semi-annual) basis. In some
cases, such as for large CDS portfolios, the IG outright exposure
may scale super-linearly, such as by a factor of 1.5. In other
cases, such as for small CDS portfolios, the IG outright exposure
may scale linearly, such as by using a maximum value. Additionally,
the outright exposure calculator may further scale the outright
exposure using a median trading volume parameter, such as a trading
volume as reported by the DTCC.
[0042] At 330, the liquidity charge computing device 210 may
calculate a cost associated with unwinding one or more hedged index
positions associated with the CDS portfolio, such as by using the
basis exposure calculator 230. At 340, the liquidity charge
computing device 210 may calculate a cost associated with unwinding
one or more hedged single name positions associated with the CDS
portfolio, such as by using the basis exposure calculator 230. At
350, the liquidity charge computing device 210 may calculate a
liquidity charge associated with the CDS portfolio based on the
cost of the SDV01 hedge of the IG sub-portfolio and the cost of the
SDV01 hedge of the HY sub-portfolio, the cost of unwinding the
hedged index positions and the cost of unwinding the hedged single
name positions. In some cases, the liquidity charge computing
device 210 may communicate the calculated liquidity charge via the
network 205 to the clearinghouse computing system 240. The
clearinghouse computing system 240 may use the liquidity charge in
one or more calculations to determine margining requirements
corresponding the CDS portfolio. The clearinghouse computing system
240 may further communicate the margining requirements to an
account owner of the account containing the CDS portfolio and/or a
financial institution associated with the CDS portfolio.
[0043] FIGS. 4 and 5 show illustrative charts 400, 500 for
calibrating an aspect of the liquidity charge associated with a
credit default swap portfolio. In chart 400, a ratio of
(Bid-Ask/Mid) values associated with a particular tenor (e.g.,
1-year, 3-year, 5-year, 7 year, 10-year, etc.) are compared to a
value of a (Bid-Ask/Mid) ratio associated with a 5-year tenor over
one or more different run-rank series. The surface 410 represents
the ratio (e.g., f(.tau.) 415) across the different tenors 420 and
different run ranks 425. The run ranks correspond to an on-the-run
series (e.g., 0) and different off-the-run series (e.g., -1 year,
-2 year, etc.). The chart 500 shows an illustrative (Bid-Ask/Mid)
ratio f(.tau.) 415 associated with a different tenors 420 over a
particular run-rank series, such as the on-the-run series.
[0044] In some cases, these ratios for indexes may be calibrated to
recent (e.g., weekly, monthly, semiannual, etc.) poll results and
ratios for single names may be calibrated to historical data. For
example, ratios for single name credit default swaps may be
calibrated to historical poll data during a specified time frame,
such as by using a preceding year's poll results. In some cases,
additional calibration may be done by calculating a run-rank
specific tenor scalar function for indexes and/or by polling on
single name bid/ask spreads across tenors for calibration of single
name tenor dependence, and/or the like.
[0045] FIGS. 6-10 show illustrative charts showing an impact on
margin accounts based on use of a model according to aspects of the
invention. For example, FIG. 6 shows an illustrative chart 600
representing a margin impact on a house account of a plurality of
clearing member firms 605. An illustrative chart 650 represents a
margin impact on aggregate customer accounts for a plurality of
clearing member firms 605. For each firm, margin and liquidity 610
are shown based on calculations using a previous model and new
margin and new liquidity 620 are shown based on the model discussed
above, as implemented using the liquidity charge computing device
210. Additionally, for each of the clearing member firms 605, a
change in total margin 630 is shown between the margin and
liquidity 610 calculated using the previous model and the new
margin and new liquidity 620 calculated using the new model. As can
be seen in chart 600, for house accounts, margin requirements
including liquidity charges, have been reduced using the new model
by at least 10%, with an average of about a 30% reduction in margin
costs. For customer accounts, margin requirements including
liquidity charges have mostly been reduced from about 2% to about
10%.
[0046] Chart 700 of FIG. 7 shows an impact of liquidity margin
across margin accounts as a ratio of the newly calculated liquidity
margin to the liquidity margin calculated using a previous model.
As can be seen, in many cases, liquidity margin has increased using
the new model. As can be seen in chart 750, the largest increases
760 in total margin have been seen in credit default swaps having
the most associated liquidity risks, such as in off-the-run HY or
outright 10Y positions.
[0047] FIGS. 8 and 9 show illustrative charts 800, 900 illustrating
changes seen in the margin accounts for firm 6 and firm 12 using
the liquidity charges calculated by the liquidity charge computing
device 210. For example, for both firm 6 and firm 12, margins
without liquidity have decreased significantly due to
decommissioning of the gross notional based curve charge. Also, for
both firms, liquidity margins have increased significantly due to
off-the-run positions held in their respective portfolios. Because
firm 12 has more relative exposure to off-the-run indexes, the
liquidity margin increases more than the liquidity margin increase
seen by firm 6.
[0048] FIG. 10 shows an illustrative chart 1000 showing a rolling
effect seen in margin and liquidity requirements. For example, Firm
7 has a relatively hedged portfolio with concentrated positions in
IG 18 and IG 20 CDS positions. The liquidity charge, as calculated
using equation 1 by the liquidity charge computing device 210,
drops significantly when the concentrated positions are rolled to
IG 20 and IG 21 CDS positions. Previously, using other methods, the
liquidity charge is unaffected by the roll.
[0049] The present invention has been described in terms of
preferred and exemplary embodiments thereof. Numerous other
embodiments, modifications and variations within the scope and
spirit of the invention will occur to persons of ordinary skill in
the art from a review of this disclosure. For example, aspects of
the invention may be used to process and communicate data other
than market data.
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