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© Brammertz Consulting, 2009 1Date: 20.04.23

Unified Financial AnalysisThe Risk&Finance Lab

Chapter 3: Financial Contracts

Willi Brammertz / Ioannis Akkizidis

Input elements

© Brammertz Consulting, 2009 2Date: 20.04.23

Contract: The focal point of finance

> The contract is the prime container of the financial rules

> The contractual agreement is the only hard fact of finance

> „Mechanical“ part of finance, therefore pivotal

> Modeling of non-mechanical part: Behavior

© Brammertz Consulting, 2009 3Date: 20.04.23

Where is the complexity?

© Brammertz Consulting, 2009 4Date: 20.04.23

The need for standardization

> Risk factors have certain degree of standardization

> Markets: Bloomberg, Reuters

> Counterparties: LEI

> Behavior: Must be an open dimension

> Financial contract is pivotal element

> Most complex part and „mechanically representable“

> Despite this center stage: No standard yet

© Brammertz Consulting, 2009 5Date: 20.04.23

Stock answers

> Data has to be standardized

> Semantic Depositories

> Data Warehouses

Data

A1

A2 …A3

An

ContractAlgorithms

Data

A1

A2A3

An

Contract EventsState Contingent

Cash Flows

© Brammertz Consulting, 2009 6Date: 20.04.23

Emerging standard

© Brammertz Consulting, 2009 7Date: 20.04.23

Why unique data is not sufficientThe rational for Contract Types

> Example of a set of contract data

> Value date: 15.3.00

> Principal: 1000

> Interest payment cycle: quarterly

> Interest rate: 5%, fixed

> Maturity date: 15.3.05

> What are the expected cash flows?

© Brammertz Consulting, 2009 8Date: 20.04.23

Time

Total Principle

Val

ue

Dat

e

Possible solution 1:Classical Bond

. . . .

Mat

urity

Dat

e

© Brammertz Consulting, 2009 9Date: 20.04.23

Time

Total Principle

Val

ue

Dat

e

Possible solution 2:Classical Annuity

IP+PR . . . .

Mat

urity

Dat

e

© Brammertz Consulting, 2009 10Date: 20.04.23

Time

Total Principle

Val

ue

Dat

e

Possible solution 3:Linear amortizer

Mat

urity

Dat

e

. . . .

© Brammertz Consulting, 2009 11Date: 20.04.23

Necessary condition for non-ambiguousinterpretation

> Well defined data

> Knowledge about

> intended cash-flow exchange pattern

> The underlying algorithms

> The algorithms must represent the legally defined intention

> A strict separation between data, algorithms and results is not possible in finance

11

© Brammertz Consulting, 2009 12Date: 20.04.23

Different stages of standardization

1. The cash flow generation rules are defined for each real-life contract individually.

2. Using a set of predefined rules: one defines elementary financial rules such as repricing patterns, amortization patterns and so on. These rules are then combined on an ad hoc basis to replicate the behavior of real life financial contracts.

3. Using a set of predefined standard contract types, where each contract type is a fixed combination of rules. Each real life financial contract is then mapped into one of these contract types.

4. Method 3 for the big bulk (100-x%) and method 1 or 2 for the rest.

© Brammertz Consulting, 2009 13Date: 20.04.23

Principal role of Contract Types(Choice 4)

> CT’s describe the exact transmission mechanics between

> Financial contract

> Risk factor environment

> Expected financial events

> State contingent cash flows

> Given a

> Financial contract

> Exact risk factor environment

> The state contingent cash flows are unambiguously defined

> Special solution for contracts outside the standard.

13

© Brammertz Consulting, 2009 14Date: 20.04.23

Further reasons for choice 4

> Factual low variety of financial contracts

> 98+% of all real life patterns can be represented with two and a half dozen patterns

> Historical Experience

> Practitioners thinking | transaction systems

> Dynamic Simulation

© Brammertz Consulting, 2009 15Date: 20.04.23

Common sub-mechanisms

> Principal amortization

> Principal draw-down

> Interest payment

> Rate adjustment

> FX rates

> Stock and commodity patterns

> Simple options

> Exotic options

> Credit risk related

> Behavioral

On-Balance Loans

© Brammertz Consulting, 2009 16Date: 20.04.23

High level architecture

© Brammertz Consulting, 2009 17Date: 20.04.23

Basic Contract Types

© Brammertz Consulting, 2009 18Date: 20.04.23

Combined Contract Types

© Brammertz Consulting, 2009 19Date: 20.04.23

Parent/child relationships

© Brammertz Consulting, 2009 20Date: 20.04.23

Contract TypesTaxonomy

Mapping Interface

Real-Life financial contracts

Combined Contract_Types

FRA FuturesSwaps

Options

Exotic 1

Various underlying basic CT’s

• IRSWP

• FXSWP

• FXOUT

• IRFRA• IRFUT• SCFUT• FXFUT

• CAXFL• IRXOP• SCXOP• FXXOP

Symmetric

Derivatives Non-Deriv.

Basic

• SWPTN• IROPT• SCOPT• FXOPT

CAPFL

• BNCAF

BNDCP

ex. Dual Currency Bond

Exotic 2Non Maturities SCI Contracts Maturities

• CFL• CLM• DSC• ZCB• PAM• PAX• RGM

• UMP• CSH • STK

COM IDX

RGX

ANNANXNGMNGXPBN

••

•••

••

Fixed Income

Basic Contract_Types

Credit Risk

• CRL• GAR• COL• LIM

Any contract type can have the Collateral role

© Brammertz Consulting, 2009 21Date: 20.04.23

Example 1: Discounted paper

© Brammertz Consulting, 2009 22Date: 20.04.23

Example 2: PAM fixed

© Brammertz Consulting, 2009 23Date: 20.04.23

Example 3: PAM variable

© Brammertz Consulting, 2009 24Date: 20.04.23

Example 4: Classical annuity, fixed

© Brammertz Consulting, 2009 25Date: 20.04.23

Example 5: Classical annuity, variable

© Brammertz Consulting, 2009 26Date: 20.04.23

Example 6: Regular amortizer with step-up

© Brammertz Consulting, 2009 27Date: 20.04.23

Example 7: Plain vanilla swap

© Brammertz Consulting, 2009 28Date: 20.04.23

Example 8: FRA

© Brammertz Consulting, 2009 29Date: 20.04.23

Example 9: European bond option

© Brammertz Consulting, 2009 30Date: 20.04.23

What to do with the 2-%?Non-standard Contract Types

© Brammertz Consulting, 2009 31Date: 20.04.23

Risk factor states, state contingentevents/cash flows and analysis elements

© Brammertz Consulting, 2009 32Date: 20.04.23

An alternative analogyDNA and gene expression

DATA ALGORITHMS

© Brammertz Consulting, 2009 33Date: 20.04.23

Comparing DNA and CT

DNA

>DNA information

>Gene expression

>Context sensitive

>Result: > Proteins

> Some other results

>Important: Cells are autark in reproduction

CT

>Contract information

>CT specific algorithm

>Risk factor sensitive

>Result:> State contingent cash

flows

> Analysis elements

>Contracts must become autark in results production

© Brammertz Consulting, 2009 34Date: 20.04.23

Static Analysis

DynamicAnalysis

Reuters Bloomberg ......

Market Data

Behavioral

Assumptions

Contract Data

Bonds Savings Swaps ....

USD.GOVEUR.SWA USD/EUR ...

Select

Aggregate

Counterparty Data

External Data

Internal Data

Hierarchy

....

ID Name Rating ...

SummixTM

ETL

V_D M_D C_P

Interface

Behavioural

Statistical

+ Adjustment up/down

Qualitativescores

Dataflow in practice

ResultsHistorization

CentralData Store

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