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Financil Contracts (FCs) specify rights and obligations that parties are legally
bind.Hence effective management of FCs is vital.Domain Specific Language (DSL)
approach provides a method of defining rights and obligations of contracts using fixed
and precisely defined set of combinators and observables.As a result, any contract can
be composed using fixed set of symbols, the contract management becomes efficient and effective.The Haskell Contract Combinator Library (HCCL) is the driving forcebehind the DSL approach in finance sector

Financil Contracts (FCs) specify rights and obligations that parties are legally
bind.Hence effective management of FCs is vital.Domain Specific Language (DSL)
approach provides a method of defining rights and obligations of contracts using fixed
and precisely defined set of combinators and observables.As a result, any contract can
be composed using fixed set of symbols, the contract management becomes efficient and effective.The Haskell Contract Combinator Library (HCCL) is the driving forcebehind the DSL approach in finance sector

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Domain Specific Language for Specify Operations of a Central Counterparty(CCP)

  1. 1. L.G.H.C. Nalinda 2011CS005 11000058 Domain Specific Language for Specify Operations of a Central Counterparty Supervisor: Dr. Chamath Keppetiyagama
  2. 2. Domain Specific Language to Define Operations for Central Counterparty ▷Domain – Financial Market ▷Central Counterparty (CCP) – Financial Institute Financial Market Specific Language to CCP
  3. 3. Road Map ▷Financial Contracts ▷Motivation ▷Research Hypothesis ▷Research Literature ▷Design ▷Representation Of CCP Operations ▷Evaluation & Analysis ▷Conclusion And Future Work
  4. 4. Financial Contracts
  5. 5. Financial Contract ▷Financial Contract = Promise + Legal ▷Transfer $100 On 31st Dec. 2016 Future Date Promise Future Cash Flow ▷Different Contracts  Different Purposes Different Interests Contract Definitions Different Different Operations
  6. 6. Motivation
  7. 7. DSL for Finance Sector Motivation
  8. 8. Haskell Contract Combinator Library
  9. 9. Peyton Jones, Marc-Eber, Julian (2000) ▷Fixed, Precisely Specified Set of Combinators (Unified Mechanism) ▷Describe a Contract ▷Process a Contract ▷Find Value of a Contract ▷Compositional Nature – (Can Glue Combinators Together) Contract Primitives + Observable Primitives IntroductionHCCL
  10. 10. Primitives for Defining Contracts | HCCL IntroductionHCCL
  11. 11. Primitives for Defining Observables IntroductionHCCL
  12. 12. Composing Contracts
  13. 13. Composing ZCB “Receive £200 on Future Date t1” C1 = one GBP C2 = truncate t1 (one GBP) = truncate t1 (C1) C3 = scale 200 (truncate t1(one GBP)) = scale 200 (C2) C4 = get (scale 200 (truncate t1(one GBP))) get (C3) IntroductionComposing Contracts ZCB :: Date -> Double -> Currency -> Contract
  14. 14. Contract Definitions IntroductionComposing Contracts ▷ZCB :: Date  Double  Currency  Contract ▷EU_OPTION :: Date  Contract  Contract ▷AMERICAN_OPTION :: (Date,Date)  Contract  Contract
  15. 15. Central Counterparty
  16. 16. Absence of CCP CCP
  17. 17. With CCP CCP
  18. 18. Operations of CCP ▷Margin Calculation Purpose : No Counterparty Default Occur At the End of Each Business Day . ▷Possibilities Dr. Trader Account Cr. Trader Account Restate to Initial Margin CCP
  19. 19. Rule 9102 – Long Option Position Margin Requirement . Methodology the period to expiry is greater or equal to 9 months, 50% of the option’s time value, else 100% of the option’s time value Future Cash Flow .
  20. 20. Research Hypothesis
  21. 21. If we can use Peyton Jones’s language to compose FC/FD, we can use the same language to compose CCP Rules
  22. 22. Research Literature
  23. 23. Summary IntroductionResearch Literature DSL for Finance Sector Has been a Major Requirement Since Early Days Payton, Eber, Julian HCCL Mediratta Complex Derivatives Gaillourdet Software Language Approach Bahr, Jost, Elsman Symbolic Management of Finance Contracts & Symbolic Management of Multiparty Contracts CCP Operations Have Not Yet Addressed using DSL Approach
  24. 24. Design
  25. 25. Rule | Design Architecture IntroductionDesign
  26. 26. Seed Contract | Hypothesis IntroductionDesign
  27. 27. Operations of CCP IntroductionDesign
  28. 28. Representation of CCP Operations
  29. 29. Sell 100 Dell shares for a price of £4800 anywhere from today to 240 days from today, or DO NOTHING at all during the time
  30. 30. Contract | Analysis ▷Giving user a “Choice”  Option Contract
  31. 31. Compose Option Contract using HCCL ▷Receive £ 4800 : C1 = (Get (Scale (Obs [4800.0]) (One GBP))) ▷Transfer(Sell) 100 Dell Shares : C2 : (Give (Scale(Obs [100.0]) (OneE DEL))
  32. 32. Compose Option Contract using HCCL (Cntd.) ▷Composite Contract : C3 = And C1 C2 ▷Adding Option to Contract : C4 = Or C3 Zero ▷Maturity @240th day: C5 = Truncate 240 C4
  33. 33. Instrument ▷Easy Way to Introduce ▷Grasp underlying rights and obligations  Name
  34. 34. Option Premium ▷Amount Pay For The Instrument ▷Option Premium Is A Contract ▷Pay £ 200 To Purchase “ABC_Instrument” TruncateT ((),1) (Scale (Obs [200.0]) (One GBP))
  35. 35. Trade Creation Buyer Is The OWNER
  36. 36. Data Type| Trade data Trade = Trade Instrument Contract ▷Trade Option Premium Paid – £ 200 Instrument Purchased – “ABC_Instrument” Underlying Contract – Option Created This Trade Brings To CCP
  37. 37. Rights and Obligations Defined In Trade ▷Owner -Sell 100 Dell + Receive 4800 GBP or - DO NOTHING
  38. 38. Trade Novation ▷Buyer | Owner – Long Position ▷Seller | Option Writer – Short Position
  39. 39. Analyze Trade ▷Get Instrument From Trade ▷Get Option Premium From Trade Progress
  40. 40. Analyze Instrument ▷Equity (Equity) - Dell ▷Maturity Date (Int) - 240 ▷Number Of Shares – (Obs Double) – (Obs 100.0) ▷Amount To Be Paid – (Obs Double) – (Obs 4800) ▷Currency – (Currency) – GBP (£) ▷Amount Paid (Obs Double) – (Obs 200) ▷Currency – (Currency) – GBP (£) Progress Analyze Option Premium
  41. 41. Long Option Position Progress
  42. 42. Composing Rule 9102 | (a) ▷Options’ Time Value - Time Varying Quantity - Observable Double (Obs Double (eg. Obs 200)) - Compute following, Option Premium Paid (Obs Double) - lift2 Operator Of HCCL - Convert (Obs Double) to Double using Haskell inbuilt functions
  43. 43. Composing Rule 9102 | (b) ▷Normal Margin (o1) - Time Varying Quantity - Observable Double (Obs Double) ▷In The Money Value (o2) - Time Varying Quantity - Observable Double (Obs Double) ▷Lesser - Observable Comparison lift2 min o1 o2
  44. 44. Composing Rule 9102
  45. 45. Composing Rule 9102 ▷rule9102One ▷rule9102Two ▷rule9102Composite
  46. 46. Research Hypothesis Proved
  47. 47. Evaluation & Analysis
  48. 48. Environment ▷Facts About Observables and Choices – Symbolic Management of Derivatives - External to the FC/FD - Direct impact on the FC/FD IntroductionResearch Literature
  49. 49. Rule Equivalence(via Contract Equivalence) ▷Contract Equivalence Same Environments Two Different Contracts Contracts Are Identical In That Environment Evaluation And Analysis Patrick Bhar
  50. 50. ▷Rule Equivalence Same Environments Two Different Rules Rules Are Identical In That Environment GIVEN NOVATED CONTRACT Evaluation And Analysis
  51. 51. Rules Transformation (via Contract Transformation) ▷Contract Transformation Specialization Function “f” Partial Evaluation Of Contract “C”  f(C,ρ) New Environment - ρʹ Same Cash Flows Evaluation And Analysis Patrick Bhar
  52. 52. ▷Rules (Seed Contract) Transformation Specialization Function “f” Partial Evaluation Of Contract “Cseed”  f(Cseed,ρ) New Environment - ρʹ Same Cash Flows Evaluation And Analysis
  53. 53. Rule Decomposition(via Contract Decomposition) ▷Rule 9102 rule9102One rule9102Two Evaluation And Analysis
  54. 54. Data Types: Instrument Evaluation And Analysis
  55. 55. Equality of Two Instruments Evaluation And Analysis
  56. 56. New Instruments From Existing Instruments Evaluation And Analysis
  57. 57. Data Types: Trade Evaluation And Analysis ▷Purpose – Isolating Operations That Can Perform On Data Types ▷Decouple Each Level Of Contract Management Via New Data Types ▷Only Core Operations
  58. 58. Margin Calculation Engine For CCP Evaluation And Analysis
  59. 59. Conclusion and Future Work
  60. 60. Conclusion Conclusion and Future Work
  61. 61. Conclusion ▷ Proved Hypothesis – Haskell Contract Combinator Library  CCP Rules ▷DSL approach “Margin Calculation” lucrative Easy (fixed set of combinators and observables) ▷Symbolic Management Rule Equivalence Rule Transformation Rule Decomposition (Rule Monotonicity) ▷Base research for CCP Conclusion And Future Work
  62. 62. Future Work ▷Put Option Only (Other Contract types) ▷Novation – Only one side analyzed - Two Option Positions - Long Option Position  - Short Option Position ??? - Netting and Position Calculation (new observables ?) ▷One Rule – Rule 9102 ▷Type Conversion ▷Margin Calculation Engine IntroductionConclusion And Future Work Mediratta CS+Finance+Maths UI Skilled People
  63. 63. THANK YOU 
  64. 64. Q&A
  65. 65. Rule Monotonicity (via Contract Monotonicity) ▷Contract Monotonicity Two Different Environments Partially Agree Given Contract Yield Same Cash Flow Evaluation And Analysis Patrick Bhar
  66. 66. ▷Rule Monotonicity - Two Different Environments - Partially Agree - Given Rules Yield Same Cash Flow - GIVEN NOVATED CONTRACT Evaluation And Analysis
  67. 67. Financial Markets
  68. 68. Peyton Jones, Marc-Eber, Julian (2000) ▷Fixed, Precisely Specified Set of Combinators ▷Describe a Contract ▷Process a Contract ▷Find Value of a Contract ▷Compositional Nature Contract Primitives + Observable Primitives IntroductionResearch Literature
  69. 69. Market Observables Evaluation And Analysis ▷Addition ▷Division ▷Minimum Gaillardet Observable Values Must Be: - Boolean - Real Number - Integer ▷Options Time Value ▷In The Money Value ▷Margin Required ▷Intrinsic Value
  70. 70. Haskell Pattern Matching IntroductionResearch Literature
  71. 71. Complex Derivatives ▷Mediratta – Credit Default Swap & Power Reverse Dual Currency Swap ▷Valuation – evalC :: Model  Contract - evalO :: Model  Contract More Complex Derivatives Can Compose Using Fixed Set of Combinators & Observables While Preserving Uniqueness of the Contract IntroductionResearch Literature
  72. 72. Composing Rule 9102 | (a) ▷Date ▷Option’s Time Value in Double ▷Currency
  73. 73. Software Language Approach ▷Peyton – Justify that FP Approach Can Use to Define and Value Derivatives - Lacking Highlighting SE Language Concepts - No Unified Approach  ▷Gaillourdet – HCCL in a SW Language Point of View - Provided a Formal Definition for the Language (Syntax) Syntax of Observables Syntax of Contract - Denotational Semantics Observables Contracts IntroductionResearch Literature
  74. 74. Option Time Value ▷Time Value = Option Price – Intrinsic Value ▷Intrinsic Value – Price at which the Commodity is being traded at considered date. Observable  Obs Double ▷In the Money -> Strike Price Vs Spot Rate IntroductionResearch Literature
  75. 75. After Novation ▷Buyer And Seller Treat Separately ▷Margin Calculation Is IMPORTANT ▷Constructing Core Level Contracts ( ▷Partial Contract Implementation ▷Construction of Rule Using HCCL ▷Finalizing Seed Contract ▷Generate All Possible Results Progress Work In Progress
  76. 76. Operations of CCP ▷Get Instrument From Trade ▷Get Option Premium From Trade ▷Analyze Instrument Instrument Name Equity Maturity Number Of Shares Traded Amount Agree To Pay Currency ▷Analyze Option Premium
  77. 77. Stakeholder Interests vs Economic Stability ▷History Enron 2007 2008 Crisis Greek Crisis ▷Minimize Risk– Effective Derivative Management ▷Computer Science Big Data Data Mining Real Time Analytics Neural Networks ++ Financial Markets
  78. 78. Stock Exchanges (SE) ▷Buyers and Sellers Meet ▷Financial Contracts/ Financial Derivatives Legal Contracts Types: Futures, Options, Swaps, Swaptions, Bonds ++ CDS, PRDC Swaps ++ ▷Rules and Regulations Uncertainty Effective Derivative & Contract mgt: Financial Markets
  79. 79. Effective Derivative Mgt ▷Stakeholder Expectations vs Economic Stability ▷History Enron 2007 2008 Crisis Greek Crisis ▷Rules and Regulations Uncertainty Effective Derivative & Contract mgt: Financial Markets
  80. 80. Effective Derivative Mgt(Cntd.) ▷Minimize Risk ▷Types of Risk Operational, Legal Business, Financial ▷Computer Science Big Data Data Mining Real Time Analytics Neural Networks ++ Financial Markets
  81. 81. ZCB(Contd.) “Pay € 100 on Future Date t2” C5 = give (scale 200 (truncate t2 (one EUR))) IntroductionQ&A Currency - €/EUR Date - t2 Action - “Pay” Amount - £200 and :: Contract -> Contract -> Contract C4 = get (scale 200 (truncate t2 (one GBP))) C5 = give (scale 100 (truncate t2 (one EUR))) C6 = and C4 C5
  82. 82. Composing European Option C 7 = European (date “02 Sep 2015”) ( zcb (date “09 Nov 2016”) 0.4 GBP `and` zcb (date “12 Oct 2016”) 8.4 USD `and` zcb (date “18 Nov 2016”) 0.4 GBP `and` give (zcb (date “09 Nov 2016”) 0.4 GBP) C8 = European Option = C7 `or` zero IntroductionQ&A European :: Date -> Contract -> Contract
  83. 83. Peyton Jones (Cntd) ▷Value Process – a Partial Function of Time How Much this Contract Worth Incorporate Environment Conditions Generating Information from Defined Contract ▷Abstract Evaluation – How to Translate Arbitrary Contract into a Value Process - Semantics for Contract Primitives - Semantics for Observables ▷Concrete Implementation – Implementation of Abstract Semantics - Model IntroductionResearch Literature
  84. 84. Peyton Jones (Cntd) IntroductionResearch Literature
  85. 85. Peyton Jones (Cntd) Model IntroductionResearch Literature
  86. 86. Semantics for Contracts | VP IntroductionQ&A
  87. 87. Semantics for Observables | VP IntroductionQ&A
  88. 88. Denotational Semantics | Gaillourdet IntroductionQ&A
  89. 89. Software Language Approach (Cntd.) ▷Observable Value – Boolean | Real | Integer ▷Time – Natural Number ▷Constant K – Boolean | Real | Integer ▷Unknown Observables – “S” ▷Binary Operators & Comparison Operators – Two Arguments of Same Type - Binary – Returns Same Type - Comparison – Returns Boolean ▷Unary – One Argument and Return Same Type ▷Type Casting – (C2D o | D2C o) IntroductionResearch Literature
  90. 90. Software Language Approach (Cntd.) ▷Denotational Semantics – Map Each of Programs to Mathematical Object - Denotation for Observables - Denotation for Contracts ▷Denotation for Observables – (S  N  V)  ( N  V ) ▷Denotation for Contracts – (S  N  V)  ( N  D ) ▷“e” – Environment IntroductionResearch Literature
  91. 91. Symbolic Contract Management ▷Symbolic Contract Management – Why symbolic – Ease of Expressing - Denotational Semantics Information - Expression (Set of Symbols) - Monotonicity (Europe vs Asia) ▷Contract Management and Analysis - Contract Equivalence - Inferring Contract Properties - Contract Dependence (Observables Affect on Cash Flows) - Contract Causality (Future Observable) - Contract Horizon (Life Time) ▷Contract Transformation – Specialization & Reduction IntroductionResearch Literature
  92. 92. Symbolic Contract Management ▷Specialization– ▷Reduction IntroductionResearch Literature
  93. 93. Architecture | Motivation IntroductionQ&A
  94. 94. Tree Representation IntroductionQ&A C5 And Or Or And C4 C3 C2C1
  95. 95. (Obs Double) to Double ▷Contracts (Double) Amount Paid # of Shares Traded ++ ▷Extracted Values + Computations (Obs Double) Time Value Intrinsic Value ++ eg: The Lesser of Normal Margin And In The Money Value Methodology
  96. 96. (Obs Double) to Double (Cntd.) ▷Double  (Obs Double) konst ▷(Obs Double)  (Double) Our Own Function Methodology
  97. 97. (Obs Double) to Double (Cntd.) Methodology A : Show a => a -> String (String representation of the value) B : matchRegex (Regex  String  Maybe[String]) "[-+]?([0-9]*.[0-9]+|[0-9]+)“ C : fromJust :: Maybe a -> a D : Operator (!!) E : read a :: Double

Editor's Notes

  • Expectations vs Stability
    Stakeholders may make higher profits

    Financial Contract / Financial Derivative
    Enron -> Falsify their profits, illegal documentation
    2007 -> Legal loopholes, power centralization with limited player
    Greek  Monetary and Fiscal policies adhere to EU regulations  Solite

    Rules and Regulations
    Why  Environment is uncertain,
    Satisfy conditions to become eligible
    Effective derivative contract mgt:  Meet stakeholder expectations


  • Let’s look at the corporate sector financial markets
  • This is an example of a future date proime that is legally binded.
  • Up to this point, (4)
    we have seen
    How FM evolved
    What kind of Derivatives are trading
    Stakeholder Groups and Interests
    Risk High Economic Segment
    Contract Mgt is Important
    Computer Science is Promising
  • DSL for Finance Sector
    Unified Mechanism for Defining Contracts
    DSL to Embed Properties of Contracts
    Benefits
    Simple Valuation … Complex Back-End Operation Management
  • We ‘ve seen DSL is favorable approach to adapt.

    HCCL facilitates -> DSL approach to FC , to deine Contracts and define Operations of FC
  • Library Offers -> fixed

    Define Observables, Scaling

    Observable -> Time varying quantity,
    value is objective
  • Explain that we can use these to define contrac
  • Two edges of the sails are stitched to the radial lines and the other two edges are free. The edge facing the parachute skirt is called the leading edge and the edge facing the vent is called the trailing edge.
  • The Combinators Can Glue together
  • Pay -> Cash outflow


    One Single Line we can define a contract
  • Last section ,
  • Trader A sees growth in DELL share in the time to come.
    So thought of bying DELL shares at
    There Trader B in the market who is willing to sell DELL share to the price Trader A willing to purchase
    Decides today , to buy X amount of DELL shares at Future Date t, for a Specific price Per share

    At future date t, A wishes to exercise contract, but B says no, or vice versa,
    Counter party risk
  • Trader A and Trader B goes to reliable trusted party Contract Counter Party.
    What CCP does, initial contract  make it two (Contract Novation)
    For a trade - CCP buyer and Seller at same time.
    One con
  • CCP is a highly regulated institutes
    Traders needed to satisfy certain criteria to become members of CCP
    Derivatives are subjected to Rules  Rule Books

    Margin Calculation
    Derivative has a life period of n time.
    At the end of each business day Margin Calculated according to rules specified.
    Margin -> How to make sure that counterparty default does not occur, incorporate uncertainty.

    Explain Possibilities
  • Explain Long Option Position

    Margin Requirement is a cash flow The Rule, by itself reflects a future cash flow



  • And there by Operations of CCP

    Specify Operations of a CCP Using a Domain Specific Language approach
  • Most important reseach related to my research will be highlighted
  • CCP Operations are Summation of all these Respective Research Areas
  • Target -> Checks applicability

    Input  what are the necessary inputs (expiry, current date)

    Logic  Hypothisis – rule implementation using payton jones

  • Research Hypothesis
    ================
    Rule is a finance Contract -> Daily margin calculation
  • Up to this point, (4)
    we have seen
    How FM evolved
    What kind of Derivatives are trading
    Stakeholder Groups and Interests
    Risk High Economic Segment
    Contract Mgt is Important
    Computer Science is Promising
  • The example contract that we choose in our research is this. The contract is , selling 100 dell shares, for 4800 GBP at future date 240
  • When analyzing the above contract, we can clearly see to major parts.
    major parts: buy and sell + do nothing

    (mee slide eke kiyanna, methane contract 2k tiyanawa kiyala)

    Building block of the previously defined contracts

    Futher, we can see, there are two contracts in the this contract as well, selling 100 Del and reciving money
  • Option Contract , clearly see the two options
  • Describing the rights and obligations of contracts evertime when needed, is a tedious task (repeating number of shares, amount to be paid, share type). Complex ones may be even more harder.
    So, via a name it’s easy to introduce a contract  Instruments

    Easy way of introducing to the market.

    In Haskell we can define data type as follows: Data type name | Data tye constructor

    From this way we add the defined contract to a new context called, Instrument. The defined contract is introduced to the market in the form of an instrument.
    Market players knows the inherent properties of this instrument, the commodity, number of shares traded.


    At this point we created our Instrument.
  • Market participant would willing to pay for the instrument

    Cash flow –


    Now, we have an instrument in the market , also a buyer who is willing to pay option premium to purchase the instrument.

  • Option Writer (Seller) – Introduce Instrument to Market

    Buyer – Pay the Premium And Purchase The Option

    Buyer Is The OWNER Of Instrument
    =========================
    Here we are dealing with two data types, Instrument and Option Premium , to represent this trade we create another data type called trade.
  • This trade is brings to CCP

    To represent this trade, we created a new data type called Trade

    Trade data type takes, has the value constructor Trade, that takes two input arguments, The first argument is of data type Instrument.

    The option premium paid 200 GBP and Instrument ABC is wrapped in this data type Trade.
  • LET’S LOOk at the rights and obligations specified in this trade.

    The owner of this ABC instrument has following rights and obligations. Since he purchased the instrument by paying option premium.

    Owner has the right of selling, 100 Dell and receive 4800 GBP from option writer.
    ===========================

    But default risk is there, CCP undertake this risk by novating the above contract and acting as the middle party.
  • Now the both buyer and seller deals with , CCP.

    Here CCP act as the seller to original buyer and buyer to original seller.

    At this time CCP regulations open a state called Long Position to Buyer and state call Short position to Seller. That is the legal requirement.

    Now buyer and seller treat sepeartely.
  • How we did in our research.

    We create the data type trade to incorporate the scenario of , purchasing instrument by paying Option Premium.

    Our research we use HCCL and Haskell to their optimum level. We use Haskell pattern matching technique to extract the needed results.
    For example, to obtain the instrument from trade, we defind function as follows,
    Similarly to obtain option premium, we defined function getInstrumentPremiumFromTrade function.

    Accordig to the pattern specified in the function, it retrieves Instrument, this function contract
  • In design phase we identified, it is needed to identify inputs for the rule from the original contract/trade. This analysis is carried our for that.

    Similarly defining set of functions and following Haskell pattern matching technique, we extracted following from both Instrument and Option Premium.
    For example, the underlying equity, Del, maturity date, 240 ,
    With in bracket I specify the , data type of the corresponding values.

  • Th
  • Option time value compute from the amount spent for Option Premium. When economic conditions get vary, this amout we pay for the premium is also get vary. Hence it is also an observable
  • We define rule9102One to determine the cash flow semantic with respect to
  • Th
  • Using combinators, scale, one, and, truncate we prove the amount of adjustment.
    Furter in our way, we used Haskell library inbuilt function in performing compuations
  • And there by Operations of CCP

    Specify Operations of a CCP Using a Domain Specific Language approach
  • Up to this point, (4)
    we have seen
    How FM evolved
    What kind of Derivatives are trading
    Stakeholder Groups and Interests
    Risk High Economic Segment
    Contract Mgt is Important
    Computer Science is Promising
  • CCP is a highly regulated institutes
    Traders needed to satisfy certain criteria to become members of CCP
    Derivatives are subjected to Rules  Rule Books

    Margin Calculation
    Derivative has a life period of n time.
    At the end of each business day Margin Calculated according to rules specified.
    Margin -> How to make sure that counterparty default does not occur, incorporate uncertainty.

    Explain Possibilities
  • CCP is a highly regulated institutes
    Traders needed to satisfy certain criteria to become members of CCP
    Derivatives are subjected to Rules  Rule Books

    Margin Calculation
    Derivative has a life period of n time.
    At the end of each business day Margin Calculated according to rules specified.
    Margin -> How to make sure that counterparty default does not occur, incorporate uncertainty.

    Explain Possibilities
  • CCP is a highly regulated institutes
    Traders needed to satisfy certain criteria to become members of CCP
    Derivatives are subjected to Rules  Rule Books

    Margin Calculation
    Derivative has a life period of n time.
    At the end of each business day Margin Calculated according to rules specified.
    Margin -> How to make sure that counterparty default does not occur, incorporate uncertainty.

    Explain Possibilities
  • CCP is a highly regulated institutes
    Traders needed to satisfy certain criteria to become members of CCP
    Derivatives are subjected to Rules  Rule Books

    Margin Calculation
    Derivative has a life period of n time.
    At the end of each business day Margin Calculated according to rules specified.
    Margin -> How to make sure that counterparty default does not occur, incorporate uncertainty.

    Explain Possibilities
  • CCP is a highly regulated institutes
    Traders needed to satisfy certain criteria to become members of CCP
    Derivatives are subjected to Rules  Rule Books

    Margin Calculation
    Derivative has a life period of n time.
    At the end of each business day Margin Calculated according to rules specified.
    Margin -> How to make sure that counterparty default does not occur, incorporate uncertainty.

    Explain Possibilities
  • To make instrument, while preserving contract properties

    Market players knows the rights and obligations of the underlying contract of the instrument.



    Complex Contracts – Hard to Illustrate

    Name Of The Instrument  Rights & Obligations of Contract

    Identical Names – Similar Instruments && Similar Contracts

    Similar Contracts Can Have Different Instrument Names



  • To make instrument, while preserving contract properties

    Market players knows the rights and obligations of the underlying contract of the instrument.

  • To make instrument, while preserving contract properties

    Market players knows the rights and obligations of the underlying contract of the instrument.

  • To make instrument, while preserving contract properties

    Market players knows the rights and obligations of the underlying contract of the instrument.

  • HCCL driven DSL architecture for CCP
  • Up to this point, (4)
    we have seen
    How FM evolved
    What kind of Derivatives are trading
    Stakeholder Groups and Interests
    Risk High Economic Segment
    Contract Mgt is Important
    Computer Science is Promising
  • Absence of a DSL – Separate mechanisms are there to represent each contract
    Drawback -> When a new Derivative comes to the market, it’s again need to create new mechanism to represent it.
    Suppose 3 management mechanisms such as valuation, deduction et. , for each combination of activities, separate programs needs to write

    With DSL
    One Unified mechanism to Define All Derivatives. What ever the derivative, it will be constructed , utilizing the mechanism,
    The processing activities will also based on same mechanism
    Total Number of Programs can be reduced  Effective Contract Management
    New contract/processing arrive, same mechanism will be used to to define and process contract
  • Large Number of Contracts / Derivatives
    How are we going to define them,
    Each Derivative Different Definition
    How to preserve the properties of each derivative, incorporate complexity, uncertainity
    Eventhough successfully defined, the processing/managemt becomes even cumbersome task

    DSL for Finance Sector
    To eliminate ambiguities and complexities of defining contracts  Unified mechanism suggest
  • CCP is a highly regulated institutes
    Traders needed to satisfy certain criteria to become members of CCP
    Derivatives are subjected to Rules  Rule Books

    Margin Calculation
    Derivative has a life period of n time.
    At the end of each business day Margin Calculated according to rules specified.
    Margin -> How to make sure that counterparty default does not occur, incorporate uncertainty.

    Explain Possibilities
  • Properties of contracts of contracts
  • Let’s look at the corporate sector financial markets
  • Define Observables, Scaling

    Observable -> Time varyig quantity,
    value is objective
  • To make instrument, while preserving contract properties

    Market players knows the rights and obligations of the underlying contract of the instrument.

  • Define Observables, Scaling

    Observable -> Time varyig quantity,
    value is objective
  • Justifies the applicability of HCCL for complex derivatives.

    There will be more derivatives, more complex,

    Identify the cash flow semantics -> precisely define the cash flows, ,  so it can use to
  • We define rule9102One to determine the cash flow semantic with respect to
  • Peyton -> Sense of implementation flavor.
    - Lacking will lead to divese set of approaches, Different researcher can come up with their own approach,  not unified, not suitable in the long term,

    Gaillourdet -> SW point -> to make it a uniform process
    Syntax – arrangement of words so that they make meaningful sentences.
  • Peyton -> Sense of implementation flavor.
    - Lacking will lead to divese set of approaches, Different researcher can come up with their own approach,  not unified, not suitable in the long term,

    Gaillourdet -> SW point -> to make it a uniform process
    Syntax – arrangement of words so that they make meaningful sentences.
  • Design – seed, contract reduction specialization support
    Contract equivalances
    Infor more contracts
    Symbolic management

    Matter of jst simulating the environment
  • This trade is brings to CCP

    To represent this trade, we created a new data type called Trade
  • Expectations vs Stability
    Stakeholders may make higher profits

    Financial Contract / Financial Derivative
    Enron -> Falsify their profits, illegal documentation
    2007 -> Legal loopholes, power centralization with limited player
    Greek  Monetary and Fiscal policies adhere to EU regulations  Solite

    Rules and Regulations
    Why  Environment is uncertain,
    Satisfy conditions to become eligible
    Effective derivative contract mgt:  Meet stakeholder expectations


  • Buyer and Seller
    A place where parties with different interest meet with each other. (Not the conventional buyer and seller)
    Happens through brokerage firms, a legal corporation that undertakes interest of others
    Give an example (one party wishes to sell crude oid, other party wishes to buy crude oil in exchange for Gold)

    Financial Contract / Financial Derivative
    Contract  Legal Obligations where parties are bind to satisfy at future date
    Types: explain each of these type (each type has their own deliverables, responsibilities obligations)
    CDS -> The two derivatives given are highly traded derivatives. (more derivatives will evolve, meet demands  why there will be more devatives  uncertainity in the economy

    Rules and Regulations
    Why  Environment is uncertain,
    Satisfy conditions to become eligible
    Effective derivative contract mgt:  Meet stakeholder expectations


  • Expectations vs Stability
    Stakeholders may make higher profits

    Financial Contract / Financial Derivative
    Enron -> Falsify their profits, illegal documentation
    2007 -> Legal loopholes, power centralization with limited player
    Greek  Monetary and Fiscal policies adhere to EU regulations  Solite

    Rules and Regulations
    Why  Environment is uncertain,
    Satisfy conditions to become eligible
    Effective derivative contract mgt:  Meet stakeholder expectations


  • Minimize Risk
    100% is extremely unlikely, minimize to maximum scale

    Types of Risks
    Operational ->
    Legal ->
    Business ->
    Financial ->

    Computer Science
    Big Data Concepts High Volumes, Wide Variety, Rapid Velocity (3Vs)
    Data Mining -> Customer Churn Analysis, Storck Market Predictions
    Real Time Analytics -> Fraud Detection, Bankruptcy predictions
    Nueral Networks -> So call AI applications in Stock Markets ()
    CS is a dominant pillar

  • Pay -> Cash outflow


    One Single Line we can define a contract
  • This European contract represent,
    3 receipts and one payment, hodler can decide at date 2 Sep 2015, whether to receive it or not.
  • Value Process -> Partial Function of Time
    Abstract -> Use contract primitives and observables to define contract. What are the semantic given to these value process. There n

    Concrete Implementation – Model, model incorporate the time factor, (model models an observable)
    Model -> Forex Mode, Interest Rate Model
  • Entire Value Process in a nutshell
    Here two main important point,
    What are evaluation semantics
    Model
  • Model – models an observable that is an external to the contract over time.

    Model – y model is lattice ?, each node, a value in time,
    each step -> a point in time
    construction is solely depend on valuers intension,  Compare the two

  • Denotation is equivalent to Value Process in Peyton Jones Research,
    This research -> discussed in views of SE Language approach
    Model value process mathematically

    Denotation Observables – Value of unknown Observable -> to its time values
    Example – Int rate fluctuations over time model in mathematically
    Unknown observable – S – Int rate
    Time – N (natural number
    V - Set of values
    Trhough a model, set of values at each time step.


    Denotation of Contracts -> Contract – series of cash flows
    Through a model , contract values at each time point. (Domain D of the Denotation of Contracts)
  • The information generated from Denotational Semantics will be used for symbolic contract mgt.


    Contract Mgt:
    Equivalence – 2 different contracts, semantics are total – same cash flows
    Inferring Properties – Deduce properties from denotational semantics

    Transformation: - Transform to much smaller contracts
    At denotation – Different contracts at different time periods  management more easy (simpler contracts)
  • Specialization -> As time progress -> more info about environment -> more accurate -> replace environment -> better management
    C contract specialized to f(c,rho) -> but will give same cash flows as C, we can replace C with F(c,rho) because more infor better management


    Reduction – Advance contract by one period -> the total contract semantics = semantics of C at period 1 + semantics of contract C’ over (n-1) time
  • We scale values of type “Double”

    Computations : lift lift2
  • Type Double is wrapped in a context

    To take value Double out form this context there was no function I the library.

    Convert the data type (Observable Double) --> Data type Double
  • Goal utilize exiting Haskell functions and operations to their optimum level.

    C: removes the Maybe wrapper

    Purpose:: HCCL doesn’t have this option. This is an approach that we propose through our research. To apply lib to CCP operations
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