var case study_quartetfs

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8/8/2019 VaR Case Study_QuartetFS

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Quartet’s ActivePivot for Value at Risk “Quartet’s ActivePivot solution for VaR resolves many key issues we had as it allowed us to

 properly handle, with large volumes, the non-linear nature of the VaR calculation while

 providing us a exible and diverse portfolio view, with drill down, of our market risk data.” 

Head of Market Risk IT, Large European Bank 

Current SituationOur client, a large European bank, has implemented a state-of-the-art Monte Carlo

simulation application for Value at Risk (VaR). Their portfolio includes plain vanilla productsas well as options, credit derivatives, and hybrid structures. All calculations are deployed on

their grid computing architecture in order to complete the process during their overnight

batch schedule. All reports are prepared during this overnight process after the grid has

updated a database with its results.

Problems FacedRisk managers need to easily analyze the results, preferably within Excel, and to drill down

into the risk from a business area level into individual desks or strategies. Since their current

solution was based on reports produced during the nightly end-of-day process, it did

not allow for real-time, interactive “slicing & dicing” of the data. Solving this requirement

is complex because VaR measures are non-additive in nature and traditional business

intelligence solutions all assume that measures can be aggregated.

Another problem the Bank faced was that once the simulation is completed by their

grid, the results are stored in a data warehouse. Producing the VaR reports requires a

large allocation of time in the batch schedule because the data store is massive therefore

creating a bottleneck, resulting in time consuming reporting.

Finally, risk managers need the ability to simulate “what-if” changes to their portfolios such

as the addition of new trades or the removal of some sections (for example, a counterparty

default), capabilities not currently possible in real-time.

 

FSUARTET

ActivePivotTM 

CUSTOMER CASE STUDY

LISTED

OTC

 Total

Product Desk A Desk B Total

-12%

-15%

-23%

-8%

-10% -12%

-7%

-28%

Desk 

25

20

15

10

5

0

  -   2   5  %

  -  1   5  %   -   5

  %    5  %   1   5  %

   2   5  %

   3   5  %

  4   5  %

Vector Drill In-30%

5th Loss VaR

Vector Aggregation: Enabling

Interactive “Slice & Dice” of VaR

ActivePivot is able to aggregate the actual

vectors of risk and produce, on the y, the

VaR measures (closed form or statistic)

needed – all within a split second.

1) ActivePivot is object-oriented and

can aggregate objects as well as

simple numbers whereas standard

OLAP solutions are built on databases

and therefore can aggregateonly simple numbers.

2) ActivePivot is able to compute,

interactively, additional measures

based on the data aggregated in thecube. For example, based on a vector

of risk, ActivePivot can easily compute

its variances, or its nth loss. So using

the aggregated vectors of risk,

ActivePivot can display VaR statistics

for any level of aggregation inthe cube.

Risk managers can now not only look at

statistical measures such as nth loss, mean,

variance, etc., but they can also display

a graphical representation of the P&Ldistribution - all accomplished within

Excel, a format familiar to users.

Screenshot of 

 ActivePivot’sVaR results with

details of P&L

distribution

8/8/2019 VaR Case Study_QuartetFS

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FSUARTET

Incremental Update: Solution for Removing the Database

Bottleneck 

“With their object oriented approach, we were able to immediately cost justify this innovative

solution as not only was our end-of-day reporting period shortened, but less hardware and database support was required as well.”   Head of Market Risk IT, Large European Bank 

ActivePivot is designed to work incrementally. The in-memory “cube” is updated each time

a new object is inserted. The Bank’s grid is able to produce the risk vectors continuously

and, as they are produced, ActivePivot then detects these changes and updates its

cube. This process works in parallel with the grid calculation, so when the last vectoris computed, the cube is immediately ready for analysis by risk managers. The new

architecture results in a decrease in expenses at two levels:

1) Eliminates the need for an expensive database server, and

2) Decreases the time allocated for reporting in the nightly batch, allowing the Bank 

to grow its trading volume without needing to increase the size of the grid farm.

Other OLAP tools try to address these issues by adding an additional layer on top of the

data warehouse which results in nothing more than additional processing time.

 The Bank used ActivePivot in such a way as to maintain their proprietary Monte Carlo

calculation - an imperative from the start. With ActivePivot, all the simulations performed

by the calculation engine are fed into its server however it is the manner in whichActivePivot aggregates and then stores this data that makes this solution truly unique.

How this data is now provided - through paper reports, web browsers, or even Excel - is

irrelevant as it can be delivered in any format. Both with Excel and web browsers, users

now have the added ability to drill down into each VaR number by changing search criteria

on-the-y. The previous solution was very efcient at producing data, but ActivePivot

now allows users to transform their at information into intelligent, actionableinformation and enables users to understand and manage their risk more effectively.

 

Aggregation

 Time

Time Saved

Time Lost

Data

Warehouse

Static

Reports

Interactive

Reports

Drill Down

into Risk 

Continuous Vector AggregationNEW

 TimeOLD

London43 Eagle streetLondon WC1R 4AT, UK  Tel: +44 20 7632 6910Fax: +44 20 7831 7700

New York 11 Skyline DriveHawthorne, NY 10532 USA Tel: +1 646 688 4442Fax: +1 646 688 4451

Paris130 rue de Rivoli75001 Paris, France Tel: +33 1 40 13 91 00

Email: info@quartetfs.comWeb: www.quartetfs.com

About Quartet FSQuartet FS was founded in responseto a demand by industries withcomplex business models and timely

decision-making requirements. Todate this has seen Quartet FS work largely with the nancial sectorbut our technology crosses manydisciplines including risk management,e-commerce, transportation,telecommunication, logistics, andof course nancial markets, all of which demand accurate and currentinformation to perform real-timeanalysis and render timely decisions.

ActivePivot, our real-time, eventdriven, object oriented business

intelligence (BI) component can beeasily and quickly integrated intoexisting architecture to provide proven,exible, true real-time answers that areadaptable to meet different businessrequirements.

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