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© Brammertz Consulting, 2009 1Date: 19.04.23
Unified Financial AnalysisThe Risk&Finance Lab
Chapter 3: Financial Contracts
Willi Brammertz / Ioannis Akkizidis
Input elements
© Brammertz Consulting, 2009 2Date: 19.04.23
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 4Date: 19.04.23
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: 19.04.23
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 7Date: 19.04.23
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: 19.04.23
Time
Total Principle
Val
ue
Dat
e
Possible solution 1:Classical Bond
. . . .
Mat
urity
Dat
e
© Brammertz Consulting, 2009 9Date: 19.04.23
Time
Total Principle
Val
ue
Dat
e
Possible solution 2:Classical Annuity
IP+PR . . . .
Mat
urity
Dat
e
© Brammertz Consulting, 2009 10Date: 19.04.23
Time
Total Principle
Val
ue
Dat
e
Possible solution 3:Linear amortizer
Mat
urity
Dat
e
. . . .
© Brammertz Consulting, 2009 11Date: 19.04.23
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: 19.04.23
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: 19.04.23
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: 19.04.23
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: 19.04.23
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 20Date: 19.04.23
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 31Date: 19.04.23
Risk factor states, state contingentevents/cash flows and analysis elements
© Brammertz Consulting, 2009 32Date: 19.04.23
An alternative analogyDNA and gene expression
DATA ALGORITHMS
© Brammertz Consulting, 2009 33Date: 19.04.23
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: 19.04.23
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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