CN105814598B - The method and system of the four value Monte-Carlo Simulations for finance modeling - Google Patents
The method and system of the four value Monte-Carlo Simulations for finance modeling Download PDFInfo
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Abstract
A kind of pillar having become modern finance market with supermatic automated transaction environment.Handling the ability of order and managing risk in systems while keeping the low latency between participant is conclusive for the safety in these markets and mobility.Four value Monte-Carlo Simulations of the disclosed System describe for the stochastic modeling of risk and grammatical pattern matching technique, to facilitate the design of these systems.System from compiling, be can under parallel environment efficient Ground Split, scaling and the machine autonomous system for transmitting more assets tools.System also allows to integrate the computerization finance heuritic approach on financial instrument with the user interface for being used to create trading strategies, with the risk that monitors and liquidate on the transaction platform for financial instrument.
Description
Patent right and trademark gazette
The application includes the substance that is subordinated to or may be subordinated to patent right and/or trademark protection.Due to this patent public affairs
It outputs in the file or record of present Patent and Trademark Office, so the owner of patent right and trade mark is for passing through any this patent
The duplicate of open duplication have no objection, but on the other hand retain all patent right and trade mark right.
Technical field
Present invention relates in general to Monte Carlo (Monte Carlo) emulation.More particularly it relates to device and side
Method.
Background technique
In the prior art, various other flogic systems and truth table have been disclosed.But the prior art lacks current public affairs
The efficiency for the embodiment opened.
Summary of the invention
The present invention by propose reduce traditionally with the test of the data in computer architecture, operation and analyzing and associating when
Between and the method for computing cost, the unobvious and unique combination of system and mode, configuration and use, overcome in the prior art
Deficiency.
Disclosed embodiment allows for syntactic information and semantic information to be both encoded in semantic network by proposing
With the symbol of the associated dibit vector symbol of semantic node, deficiency in the prior art is overcome.Disclosed embodiment is also logical
It crosses and the attribute that each feature is assumed in recursive predicative analysis is encoded to overcome deficiency in the prior art.
Detailed description of the invention
Fig. 1 depicts disclosed logic；
Fig. 2 depicts machine implementation；
Fig. 3 depicts the graphic representation of semantic network；
Fig. 4 depicts the distribution of the attribute for the particular index in array；
Fig. 5 depicts disclosed to the condition test for Monte-Carlo Simulation and the matched marketing data of grammatical pattern；
Fig. 6 depicts the system in disclosed futures contract market.
Based on following detailed description is read in conjunction with associated attached drawing, these and other aspects of the present invention will become
Obviously.
Specific embodiment
Following detailed description is directed toward some specific embodiments of the invention.However, the present invention can be according to such as passing through right
It is required that and their equivalent limits and the multitude of different ways of covering is implemented.In the description, reference is made to attached drawing,
In, run through entire attached drawing, identical component is designated same label.
Unless in addition being referred in the specification or claims, otherwise use in the specification and in the claims
The meaning for being usually attributed to these terms that there are all terms those skilled in the art to be thought.
Unless context clearly requires in addition that, run through specification and claims, word "include", "comprise" and class
As word will be explained by the meaning according to inclusiveness, rather than removing property or the meaning exhausted；That is, according to " including
But be not limited to " the meaning explain.Most or odd number quantity is respectively further comprised using the word of singular or plural quantity.This
Outside, when word " herein ", " more than ", the word of " following " and similar meaning be in this specification by use, what these words should refer to
It is the application as a whole, rather than any specific part of the application.
The detailed description of the upper surface of the embodiment of the present invention is not intended to be exhausted or limits the invention to public above
The clear form opened.Although the particular embodiment of the present invention or example since schematic purpose is described in detail above,
It is as those skilled in the relevant art will be recognized, various equivalent modifications within the scope of the invention are feasible.Example
Such as, although step is presented according to given sequence, optional embodiment is executable to have the step of according to different order
Routine.The teachings of the present invention can be applied to other systems provided herein, rather than just system described herein.It retouches herein
The various embodiments stated can be combined to provide other embodiments.It can make these and its to the present invention according to specific embodiment
He changes.
All above-mentioned references and United States Patent (USP) and application are merged herein by reference.If it is required, then of the invention
Various aspects can be modified, and provide the present invention with system, function and concept using various patents described above and application
Other further embodiments.
Reference label
100 include the non-transitory machine readable media of machine readable instructions sometimes
200 general or specialized processors
300 memories, sometimes nonvolatile memory
The database of 410 one or more semantic networks
The database of 420 vector arrays
The database of 430 logical connectives
The database that 440 grammer word structures are implemented
The database of 450 System Reports
600 runing time stacks and heap
700 system clocks
800 from top to bottom/syntax analyzer from bottom to top
900 are directed to the conract market of futures or other assets
910 for screening the risk engine or risk analysis system of order
Information flow between 920 conract markets 900 and direct market access participant 930
930 direct market access participants
940 hand over automatically for the direct market access between conract market 900 and direct market access participant 930
The risk engine or risk analysis of easy system
950 risk analysis for the client of direct market access and direct market access
Information flow between 960 930 and intermediary of swap market 970
970 intermediary of swap market
980 intermediary of swap market risk analysis engines
Information transmission between 990 intermediary of swap market 970, sometimes occurs in OTC or is occurred by sales counter affairs
1000 market A
1001 market B
1002 market C
1010 participants in the market, Alpha
1020 are mapped to the value in array by Alpha
1022 coding keys
1023 assets Z
1030 data for assets Z from market C
1032 are encoded in quaternary logic and show how number is mapped
1040 condition tests for being directed to assets Z are encoded
1042 condition tests for being directed to assets Z are encoded
Referring to Fig.1, the basic binary opertor and logic NOT described for quaternary logic (is ignored for logic NOT
Dullness demonstration) schematic diagram.These operators are used for the completeness of proof logic class.These logics can pass through various different opinions
Card is derived.It accounts for from the grouping of the Boolean type of true value, or is accounted for from sets theory and recursive definition, by truth table
It is arranged in trellis in advance.It is all these to be configured to save some main axioms in the form of classical logic.By right
Recurrence value is modeled, and clearly assumes that true value simplifies the test of condition and the quantization of variable in semantic network.For
The undefined value of system, the default value of growth allow coding benign for the dynamic of network, and logical attribute can belong to many
Kleene logic.4th attribute allows to carry out variable quantization and constraint appropriate, for eliminating for subsequent in calculating
The influence of the update true value of step.This is also for introducing Markov (Markov) process model building at the decision procedure of logic
Intuitive acceptable " law of excluded middle (terium non datur) " provides possibility.
By that will have the attribute coding of specific bit to bit vectors, linear scale can be kept.The system is creating
The prior art is different from terms of the compiler that symbol table, characteristic test and auxiliary extension heap compiler are implemented.
In the first column of Fig. 1, logic NOT (not) symbol is shown asIn the second column of Fig. 1, with (AND) operation
Symbol is shown asΛ, in the third column of Fig. 1, or (OR) operator is shown as ∨.First column, which is shown, accords with it using inverse
Preceding value.For example, the first row on the first column, value F is shown before application inverse symbol, and T is shown as result.
In the second column, AND operator takes a value from first row, takes a value from the first row, in the value of column and the value of row
Intersection shows the result of logical operator.In third column or operator is answered according to similar mode such as in the second column
With.For example, showing in third column and selecting the last one element D in the first row, in second element F of the first column selection, knot
Fruit is value D.
Referring to Fig. 2, machine being shown using machine readable, non-transitory medium 100 and is implemented, medium 100, which has, to be sent
To the machine readable instructions of general or specialized processor 200.Processor 200 can with memory 300, multiple databases and other
Component (such as, network, user interface and other implementations) is communicated.Multiple databases may include one or more semantic nets
The database 410 (network system of such as Fig. 3) of network, vector array database 420 (vector array can be with each semantic node
Or other networking components association), the database 430 (such as, the conjunction of Fig. 1) of logical connective, grammer word structure implement
Database 440 (such as, the database 440 of Fig. 2) and other disclosed components database.When Fig. 5 further depicts system
Clock 700, from top to bottom/syntax analyzer 800 and runing time stack and heap 600 from bottom to top.
Referring to Fig. 3, the graphic representation of semantic network 500 is shown using object 510 and relationship 520, wherein all objects
With the node that relationship is in memory or database.
Fig. 4 depicts the graphic representation with the associated dibit vector array of semantic node in memory.Fig. 4 is also shown
True value is distributed across two number groups, wherein X be the particular index in insertion array.The size of word is computer architecture in figure
In word size limitation result.This causes the chunking factor of the realization for array.
Referring to Fig. 5, Fig. 5 discloses system, wherein participant in the market's test for attempt in reserve purchase between market
Price variance in the condition of condition or other risk analyses that benefits.Disclosed system is also applied for point after ordering
Analysis.
Referring to 1040, the coding of condition test by class of assets Z from three market A 1000, B 1001 and C 1002 or
It is separated in other markets, this can be used for by specifying par-ticular processor to provide the theme of the particular risk situation for them
It produces and executes risk analysis and be directed to participant in the market's separation calculation time in parallel environment.
The information being replaced belongs to the data from market C.Condition test and filtering are shown as by participant in the market
Alpha is executed.Test can be used for filtering class of assets, risk and for resource allocation.
System and order matching engine are disclosed referring to Fig. 6, Fig. 6, wherein in disclosed system before execution of order,
Risk analysis is performed.Fig. 6 can be considered as futures contract, the Primary Actor in derivative market or other markets and secondary participation
The diagram of person.
These and other changes can be made to the present invention according to detailed description above.In general, in the claims
The term used should not be construed to limit the invention to specific embodiment disclosed in specification, unless above in detail retouch
It states and clearly limits the term.Therefore, the actual scope of the present invention includes disclosed embodiment and is practiced or carried out right and wants
All equivalent ways of invention under asking.
Although some aspects of the invention are presented in the form of specific rights requirement below, the present invention focuses on any number
The various aspects of the invention of the claim form of amount.
Disclosed embodiment includes following item:
First item: the method that the machine of the quaternary logic for modeling to financial instrument is realized, which comprises
A) using including (F, T, U, D) symbol come indicate to be mapped to the false, true, undefined of two vector dynamic arrays and
Defined value；These values are also mapped into the index in the two vectors dynamic array and are stored as the section in semantic network
Point；
B) F, T, U, D are limited to sets theory, wherein { } is " undefined ", and { T } is "true", and { F } is "false", { T, F }
For " defined ", these values are interpreted that attribute { P } is "true",For "false", { } is " undefined ", P,It is "
Definition ", these attributes are for being directed to continuous recursion step test condition in predicate calculus and quantifying the attribute of variable.
C) ignore dull demonstration, logic, the binary system are defined with negative form using following binary system conjunction
Conjunction be logical AND (Λ), it is non-Logic or (∨) conjunction, the binary system conjunction are used for proof logic as follows
Completeness:
It is T
It is F
It is D
It is U；
D) it is directed to conjunctionΛ
ΛF T U D
F F F F F
T F T U D
U F U U F
D F D F D；
E) it is directed to conjunction ∨
∨F T U D
F F T U D
T T T T T
U U T U T
D D T T D；
F) by optimizing short-term storage to semantic network syntactic information and semantic information uniform enconding, and make
Long term memory maximizes；
G) under parallel environment, optimize short-term storage so that long term memory maximization becomes optimization difference and knows
Communication and storage between knowledge source (process)；
H) in simulations using defined and undefined help to separate class of assets.
Section 2: the method for first item further includes rewriting rule using to the associated phrase structure of node in semantic network
Fortune then is configured for the test of rewriting rule and passes through.
Section 3: the method for Section 2 realize grammer can be carried out polynary syntax parsing from top to bottom, from lower and
On syntax analyzer.
Section 4: the method for Section 3 uses the data of system clock, runing time stack and heap, processor and rewriting rule
The database in library, the database of semantic network and syntactic and semantic information.
Section 5: the system for executing quaternary logic to optimize short-term storage and maximize long term memory, it should
System includes:
A) machine readable instructions in non-volatile computer-readable medium, central processing unit, runing time stack are stored in
With heap, semantic network, from top to bottom/syntax analyzer, system clock, database with history economics information from bottom to top；
B) system indicates to be mapped in two vector dynamic arrays using the Boolean type coding including (F, T, U, D)
"false", "true", the value of " undefined " and " defined "；These values are also mapped into the index in the two vectors dynamic array simultaneously
And it is associated with the node in semantic network；
C) { F, T, U, D } is limited to sets theory, such as, { } be " undefined ", { T } be "true", { F } be "false", T,
F } it is " defined ", these values are interpreted that attribute { P } is "true",For "false", { } is " undefined ", P,Be
" defined ", these attributes are the attributes for condition test and variable quantization in predicate calculus.
D) system using following binary system conjunction (logical AND (Λ), it is non-Logic or (∨) conjunction) with negative
Form defines logic, and the binary system conjunction is used for the completeness of proof logic as follows:
It is T
It is F
It is D
It is U；
E) it is directed to conjunctionΛ
ΛF T U D
F F F F F
T F T U D
U F U U F
D F D F D；
F) it is directed to conjunction ∨
∨F T U D
F F T U D
T T T T T
U U T U T
D D T T D；
G) system optimizes short-term storage by the way that information to be linearly encoded to semantic network, and makes long term memory
It maximizes；
H) under parallel environment, system integration memory is to optimize the communication between different knowledge sources (process) and deposit
Storage.
Section 6: the system of Section 5 further includes rewriting rule using to the associated phrase structure of node in semantic network
Fortune then is configured for the test of rewriting rule and passes through, and the size of the word of system is strong to condition test in theoretical time O (C)
Add chunking factor.
Section 7: the system of Section 5 further includes database (each array and each semantic node pass of vector array
Connection), the data of semantic network and grammatical phrases the structure database and logical connective database implemented.
Section 8: the system of Section 7 realize grammer can be carried out polynary syntax parsing from top to bottom, from bottom to top
Syntax analyzer, with provide for the complexity in order matching engine for various financial types buy in and sell order into
The grammatical pattern matching capacity of row modeling.
Section 9: the system of Section 7 realizes risk management system, for between different participants in the market
Interaction when financial instrument the risk that liquidates in both usage history data and real time data Monte-Carlo Simulation is moved
State modeling.
Section 10: the system of Section 7 realizes risk management system, for between different participants in the market
Interaction when insurance system the risk that liquidates in both usage history data and real time data come to Monte-Carlo Simulation model
Carry out dynamic modeling.
Section 11: the system of Section 10 further includes the real-time input from financial market, to provide market to dealer
In financial asset running accurate update, and allow the efficient communication between participant in the market.
Section 12: the system of Section 11 further includes from compiling computerization monitoring system, to be used for COMPLEX MIXED people
Machine monetary device designs and implements.
Claims (12)
1. a kind of method that the machine for executing quaternary logic to model to financial instrument is realized, which comprises
A) "false", "true", " undefined " that are mapped to two vector dynamic arrays are indicated using the symbol including F, T, U and D
The value of " defined ", wherein F indicates the value for being mapped to the "false" of two vector dynamic arrays, and T expression is mapped to two vectors
The value of the "true" of dynamic array, U indicate the value for being mapped to " undefined " of two vector dynamic arrays, and D expression is mapped to two
The value of " defined " of vector dynamic array；It index that described value is also mapped into the two vectors dynamic array and is stored
For the node in semantic network；
B) F, T, U and D are limited with sets theory, wherein { } is " undefined ", and { T } is "true", and { F } is "false", and { T, F } is
" defined ", described value is interpreted: attribute { P } is "true", attributeFor "false", attribute { } is " undefined ", attributeFor " defined ", the attribute is become for being directed to continuous recursion step test condition and quantization in predicate calculus
The attribute of amount；
C) ignore dull demonstration, logic is defined with negative form using following binary system conjunction, the binary system connection
Word is logical AND Λ, logic NOTLogic or ∨ conjunction, the binary system conjunction are used for the complete of proof logic as follows
Property:
It is T
It is F
It is D
It is U；
D) it is directed to conjunction Λ
ΛF T U D
F F F F F
T F T U D
U F U U F
D F D F D,
Wherein, the value of the first row and the value of first row are the value before carrying out logic and operation, i-th of value and first of the first row
J-th of value of column carries out logic and operation and obtains the value of the i-th row jth column, wherein 2≤i≤5,2≤j≤5；
E) it is directed to conjunction ∨
∨F T U D
F F T U D
T T T T T
U U T U T
D D T T D,
Wherein, the value of the first row and the value of first row are the value before carrying out logic or operation, i-th of value and first of the first row
J-th of value of column carries out logic or operation obtains the value of the i-th row jth column, wherein 2≤i≤5,2≤j≤5；
F) by optimizing short-term storage to semantic network syntactic information and semantic information uniform enconding, and make long-term
Memory maximizes；
G) under parallel environment, optimize short-term storage so that long term memory, which is maximumlly handled, becomes making different knowledge
Communication and optimal storage between source, wherein knowledge source is process；
H) it helps to separate class of assets using " defined " and " undefined " in simulations.
2. the method as described in claim 1, the method also includes: using to the associated phrase of node in semantic network
The fortune of structure rewriting rule is configured for the test of rewriting rule and passes through.
3. method according to claim 2, the method realize grammer can be carried out polynary syntax parsing from top to bottom,
Syntax analyzer from bottom to top.
4. method as claimed in claim 3, wherein the method using system clock, runing time stack and heap, processor and
The database of the database of rewriting rule, the database of semantic network and syntactic and semantic information.
5. a kind of system for executing quaternary logic to optimize short-term storage and maximize long term memory, the system packet
It includes:
A) be stored in machine readable instructions, central processing unit, runing time stack and heap in non-volatile computer-readable medium,
Semantic network, from top to bottom/syntax analyzer, system clock and database with history economics information from bottom to top；
B) system using including F, T, U and D Boolean type coding come indicate the "false" being mapped in two vector dynamic arrays,
The value of "true", " undefined " and " defined ", wherein F indicates the value for the "false" being mapped in two vector dynamic arrays, T table
Show the value for the "true" being mapped in two vector dynamic arrays, U indicates " undefined " being mapped in two vector dynamic arrays
Value, D indicates the value of " defined " being mapped in two vector dynamic arrays；It is dynamic that described value is also mapped into two vector
Indexing and being associated with the node in semantic network in state array；
C) F, T, U and D are limited with sets theory, wherein { } is " undefined ", and { T } is "true", and { F } is "false", and { T, F } is
" defined ", described value is interpreted: attribute { P } is "true", attributeFor "false", attribute { } is " undefined ", attributeFor " defined ", the attribute is the attribute for condition test and variable quantization in predicate calculus；
D) system defines logic using following binary system conjunction with negative form, and the binary system conjunction is logical AND
Λ, logic NOTLogic or ∨ conjunction, the binary system conjunction are used for the completeness of proof logic as follows:
It is T
It is F
It is D
It is U；
E) it is directed to conjunction Λ
ΛF T U D
F F F F F
T F T U D
U F U U F
D F D F D,
Wherein, the value of the first row and the value of first row are the value before carrying out logic and operation, i-th of value and first of the first row
J-th of value of column carries out logic and operation and obtains the value of the i-th row jth column, wherein 2≤i≤5,2≤j≤5；
F) it is directed to conjunction ∨
∨F T U D
F F T U D
T T T T T
U U T U T
D D T T D,
Wherein, the value of the first row and the value of first row are the value before carrying out logic or operation, i-th of value and first of the first row
J-th of value of column carries out logic or operation obtains the value of the i-th row jth column, wherein 2≤i≤5,2≤j≤5；
G) system optimizes short-term storage by the way that information to be linearly encoded to semantic network, and keeps long term memory maximum
Change；
H) under parallel environment, system integration memory is so that communication and optimal storage between different knowledge source, wherein knows
Knowledge source is process.
6. system as claimed in claim 5, wherein the system also includes use to associated with the node in semantic network
The fortune of phrase structure rewriting rule is configured for the test of rewriting rule and passes through, and the size of the word of system is at theoretical time O (C)
In to condition test force chunking factor.
7. system as claimed in claim 5, wherein the system also includes the databases of vector array, the number of semantic network
The database and logical connective database implemented according to library and grammatical phrases structure, wherein each vector array and each language
Adopted node association.
8. system as claimed in claim 7, wherein the system realize grammer can be carried out polynary syntax parsing from upper
Under and, from bottom to top syntax analyzer, to provide for being bought in order matching engine for the complexity of various financial types
Enter and sell the grammatical pattern matching capacity that order is modeled.
9. system as claimed in claim 7, wherein the system realizes risk management system, for in difference
Both usage history data and real time data are special to covering in the risk that liquidates of financial instrument when interaction between participant in the market
Caro emulation carries out dynamic modeling.
10. system as claimed in claim 7, wherein the system realizes risk management system, for in difference
Both usage history data and real time data are special to covering in the risk that liquidates of insurance system when interaction between participant in the market
Caro simulation model carries out dynamic modeling.
11. system as claimed in claim 10, wherein the system also includes the real-time input from financial market, with to
Dealer provides the accurate update of the running of the financial asset in market, and allows the efficient communication between participant in the market.
12. system as claimed in claim 11, wherein the system also includes from compiling computerization monitor system, with
In designing and implementing for the complex situations analogy for mixing man-machine monetary device.
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US14/051,722 US9576319B2 (en) | 2013-09-03 | 2013-10-11 | Methods and systems of four-valued Monte Carlo simulation for financial modeling |
| US14/051,722 | 2013-10-11 | ||
| PCT/US2014/056152 WO2015053912A1 (en) | 2013-10-11 | 2014-09-17 | Methods and systems of four-valued monte carlo simulation for financial modeling |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105814598A CN105814598A (en) | 2016-07-27 |
| CN105814598B true CN105814598B (en) | 2019-06-18 |
Family
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| CN201480067323.0A Active CN105814598B (en) | 2013-10-11 | 2014-09-17 | The method and system of the four value Monte-Carlo Simulations for finance modeling |
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|---|---|
| EP (1) | EP3055825A4 (en) |
| CN (1) | CN105814598B (en) |
| AU (1) | AU2014332409A1 (en) |
| CA (1) | CA2966564A1 (en) |
| WO (1) | WO2015053912A1 (en) |
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| EP3619700A4 (en) * | 2017-05-05 | 2020-10-14 | Midmore, Roger | Interactive story system using four-valued logic |
| US11257155B2 (en) * | 2018-08-27 | 2022-02-22 | Chicago Mercantile Exchange Inc. | Apparatuses, methods and systems for a computationally efficient volatility index platform |
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- 2014-09-17 CA CA2966564A patent/CA2966564A1/en not_active Abandoned
- 2014-09-17 EP EP14851877.2A patent/EP3055825A4/en not_active Withdrawn
- 2014-09-17 AU AU2014332409A patent/AU2014332409A1/en not_active Abandoned
- 2014-09-17 CN CN201480067323.0A patent/CN105814598B/en active Active
- 2014-09-17 WO PCT/US2014/056152 patent/WO2015053912A1/en active Application Filing
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| WO2007092795A2 (en) * | 2006-02-02 | 2007-08-16 | Neuric Technologies, Llc | Method for movie animation |
| US8219512B2 (en) * | 2006-12-22 | 2012-07-10 | Avaya Inc. | Higher order logic applied to expert systems for alarm analysis, filtering, correlation and root causes which converts a specification proof into a program language |
| CN101976374A (en) * | 2010-10-28 | 2011-02-16 | 西北工业大学 | Inconsistent ontology inference method by using minimum inconsistent sets and dispellable correlation |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2015053912A1 (en) | 2015-04-16 |
| CN105814598A (en) | 2016-07-27 |
| EP3055825A4 (en) | 2017-03-22 |
| CA2966564A1 (en) | 2015-04-16 |
| EP3055825A1 (en) | 2016-08-17 |
| AU2014332409A1 (en) | 2016-06-02 |
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