CN102968744A - Computer system and method for calculating convertible-bond share option - Google Patents
Computer system and method for calculating convertible-bond share option Download PDFInfo
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- CN102968744A CN102968744A CN2012104802360A CN201210480236A CN102968744A CN 102968744 A CN102968744 A CN 102968744A CN 2012104802360 A CN2012104802360 A CN 2012104802360A CN 201210480236 A CN201210480236 A CN 201210480236A CN 102968744 A CN102968744 A CN 102968744A
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Abstract
The invention relates to the field of internal data processing in computers, and in particular relates to a computer system and method for calculating convertible-bond share options, which are applied to a computer system with a processor and a memory. The method comprises the following steps of: firstly, presetting a data bank in the memory, and pre-storing a plurality of calculation rules; when a share price trading day m of an input financial product, and a trading day n when a closing price for trading the financial product is higher than a conversion price threshold H are detected, carrying out binary tree simulation calculation on the trading day m and the trading day n so as to figure out an adjustable parameter k; calling the pre-stored calculation rule, calculating a lower limit H(k) of an alternative barrier price by virtue of the binary tree simulation result, verifying and correcting the obtained adjustable parameter k so as to obtain the alternative barrier price share option, and carrying out pricing calculation by virtue of the alternative barrier price share option so as to obtain the fixed price of the convertible-bond share option. The computer system and the method are used for solving the problems of low calculation efficiency, high calculation cost and the like of the convertible-bond share option in the prior art.
Description
Technical field
The present invention relates to the internal data process field of computing machine, particularly relate to a kind of computer system and method that turns debt formula option for calculating.
Background technology
Stock option provides the possessor to buy or sell the power of its corresponding stock to decide valency at certain hour.The option of buying in stocks with price is called call option, and the option of selling stock with price is called put option.Share price is higher, and the value of call option is higher.Share price is lower, and the value of put option is higher.Option row power refers to decide valency and trades security.The option holder can select not all right power.For example be lower than when decideing valency in share price, call option should not gone power.Should not go power and be higher than when decideing valency put option in share price.Option is divided into European style option, Bermuda option, and American style option by its row power date again.European style option only has the power of could going at the date of maturity.Bermuda option is provided with specific several row power date, such as No. 5 per month, until the date of expiry.American style option then can be at the date of maturity before random time row power.We can have European put option, American call etc. like this.
Only have the option of dealing and row power date of term to be commonly referred to as common option.Common option is the basic product of modern finance industry.Their Bu Laike that is priced at the acquisition Nobel prize in economics-Si Keersi Black-Scholes Option Pricing Model Black-Scholes.Common European style option price has analytic solution.Also can add as required extra clause on the common option.For example, barrier options limits the share price upper limit or lower limit, and option lost efficacy when share price reaches price limit.The option of these Additional Terms is commonly referred to as exotic option.Though exotic option is also obeyed the Bu Laike that promotes-Si Keersi model, do not have analytic solution, and need by multiway tree, or Monte Carlo method etc. is asked numerical solution.The cosxts involved in determining price of exotic option are subjected to the precision of its numerical solution, and the computing velocity impact.Under equal accuracy, the cosxts involved in determining price of the algorithm that computing velocity is faster are lower.
Interchangeable bond, common name turns debt, is the particular company bond.Turn the circulation stock that debt can convert according to the agreement exercise price distributing and releasing corporation under certain condition.By the economic interests analysis, turn the debt possessor and only when share price is higher than exercise price, just can consider to be converted to stock turning debt.This equates the possessor to be lower than the price of current share price, buy in stocks with its bond.But think that such as the possessor share price also has rising space, the possessor also can select to postpone changing and wait for higher share price.With the language performance of option, turning debt is the corporate bonds that comprised distributing and releasing corporation's stock American call.
Because turning debt has comprised a call option, turn debt and can with lower interest rate distribution, reduce publisher's interest burden.Go up such as distributing and releasing corporation's share price, turn the debt possessor and also can select to transfer shares, deduction and exemption publisher's capital is repaid burden.So with respect to the distribution straight bond, company's distribution turns debt and can rationally reduce debt and finance costs.With respect to the investor, purchase turns debt provides one to abandon the chance of a part of inchoate interest possible stock return as cost exchanges for.The investor needs arm's length pricing to turn the American call that debt comprises like this, comes to make balance with the interest of possible loss.
In the monitoring and management view of securities market, turn debt and comprised bond and option because of it, be a class complex product.For guaranteeing to turn the reasonable operation of debt market, the debt that turns that China now issues has all comprised following unusual obstacle condition: turn debt as example take the petrochemical industry in distribution on February 23rd, 2011, have in its terms of issue one be such as share price in the 30 continuous day of trade, have at least 15 day of trade closing price be higher than exercise price 130% the time, the publisher has the right to add current interest with capital and redeems and turn debt.Therefore, need to calculate turning debt formula option value.
Use at present one of domestic and international most advanced banking software calculating to turn debt formula option value and want tens of minutes.General fund can comprise a plurality of debts that turn, and being easy to reach once calculate needs several hours.The Financial Management such as market analysis and venture analysis monitoring needs to consider fund hundreds of, or the probable value in more kinds of situation, once calculates to reach several days calculated amount.This is not only impracticable, has also comprised assessing the cost of great number.
Thereby, how to provide a kind of high efficiency for calculating fast the computer system that turns debt formula option value, real is the art personnel problem demanding prompt solutions.
Summary of the invention
The shortcoming of prior art in view of the above the object of the present invention is to provide a kind ofly to turn computer system and the method for debt formula option for calculating, is used for solving prior art for the rudimentary high in cost of production problem of counting yield that turns debt formula option value.
Reach for achieving the above object other relevant purposes, the invention provides and a kind ofly turn the computer system of debt formula option for calculating, described computer system comprises at least: processor; Storer comprises storage element and data bank, stores a plurality of operation rules in the described data bank;
The method of substitution computing module, wherein, described method of substitution computing module is stored in the described storage element and is configured to and carried out by described processor, described method of substitution computing module comprises: when the closing price that detects the share price day of trade m of a financial product of input and this financial product of concluding the business is higher than the day of trade n of its exercise price one threshold value H, described day of trade m and day of trade n are carried out the first computing unit that the binary tree analog computation goes out customized parameter k; Call the operation rule that prestores in the described data bank, utilize the result of described binary tree simulation to calculate the lower limit H(k that substitutes the obstacle valency) the second computing unit, utilize described Monte Carlo simulation the customized parameter k that draws to be verified and revise to obtain to substitute the 3rd computing unit of obstacle valency option, and utilize and substitute obstacle valency option and fix a price and calculate the 4th computing unit of the price that turns debt formula option.
In a kind of embodiment that can realize, the described operation rule that prestores in the described data bank that calls utilizes the result of described binary tree simulation to calculate the lower limit H(k that substitutes the obstacle valency) the second computing unit in the described operation rule that calls be specially:
H(k)=H * exp(k * σ); Wherein, H(k) for substituting the lower limit of obstacle valency, H is the threshold value that the closing price of this financial product of transaction is higher than its exercise price, and k is customized parameter, and σ is the daily fluctuation rate of this financial product share price.Particularly, to be higher than the threshold value H of its exercise price be 130% exercise price to the closing price of described this financial product of transaction.
In a kind of embodiment that can realize, described day of trade m and day of trade n are carried out the operation rule that the binary tree analog computation goes out customized parameter k is: selected probable value Q, for the probability that satisfies of the condition of the simulation of different k value day of trade m and day of trade n when binary tree is issued to the lower limit H (k) that substitutes the obstacle valency, selects that described to satisfy probability be customized parameter close to the k value of Q.
The present invention also provides a kind of and turns the method for debt formula option for calculating, is applied to have in the computer system of processor and storer, said method comprising the steps of: a default data bank in described storer, and a plurality of operation rules prestore; When the closing price that described processor detects the share price day of trade m of a financial product of input and this financial product of concluding the business is higher than the day of trade n of its exercise price one threshold value H, described day of trade m and day of trade n is carried out the binary tree analog computation go out customized parameter k; Described processor calls the operation rule that prestores in the described data bank, on the result of described binary tree simulation, further use Monte Carlo simulation to optimize customized parameter k to obtain to substitute the lower limit H(k of obstacle valency option), and utilize and substitute obstacle valency option and fix a price and calculate the price that turns debt formula option and turn debt.
In a kind of embodiment that can realize, the described operation rule that prestores in the described data bank that calls utilizes the result of described binary tree simulation and Monte Carlo simulation optimization to calculate the lower limit H(k that substitutes the obstacle valency) be specially:
H(k)=H * exp(k * σ); Wherein, H(k) be lower limit for the obstacle valency, H is higher than the threshold value of its exercise price for the closing price of this financial product of transaction, and k is customized parameter, and σ is the daily fluctuation rate of this financial product share price.Particularly, to be higher than the threshold value H of its exercise price be 130% exercise price to the closing price of described this financial product of transaction.
As mentioned above, of the present inventionly turn computer system and the method for debt formula option for calculating, have following beneficial effect:
Practical, computer system and the method that turns debt formula option for calculating of the present invention can be used for all kinds of prices that turn debt formula option and interchangeable bond.
Precision is high, of the present inventionly turns the error of the computer system of debt formula option and method of substitution numerical solution that method adopts and traditional numerical solution less than per mille for calculating.
Analytic solution are arranged, of the present inventionly turn the computer system of debt formula option and method for calculating and rationally use the debt formula option that turns after the method for substitution conversion that Bu Laike-Si Keersi analytic solution are arranged, analytic solution are the theoretical value that turns debt formula option, are better than traditional numerical solution.
Speed is fast, of the present inventionly turn the computer system of debt formula option and method with method of substitution method analytic solution the time for calculating, be lower than one second computing time, when needs are asked method of substitution method numerical solution, also be several seconds computing time, and this greatly is better than tens of minutes computing times of traditional numerical solution.
Modulability is strong, and the k that turns the method for substitution of the computer system of debt formula option and method for calculating of the present invention is a customized parameter, according to the continuous data to share price, or the discrete data hypothesis, can carry out standard to k and process.
Description of drawings
Fig. 1 is shown as the present invention and is used for calculating the computer system architecture synoptic diagram that turns debt formula option.
Fig. 2 is shown as the method for substitution computing module structural representation that turns the computer system of debt formula option for calculating.
Fig. 3 is shown as the present invention and is used for calculating the method flow diagram that turns debt formula option.
Fig. 4 is that share price is for the contrast trend graph of practical obstacle valency in substitute valence.
Fig. 5 only uses the trend graph of substitute valence for using share price of the present invention.
Embodiment
Below by specific instantiation explanation embodiments of the present invention, those skilled in the art can understand other advantages of the present invention and effect easily by the disclosed content of this instructions.The present invention can also be implemented or be used by other different embodiment, and the every details in this instructions also can be based on different viewpoints and application, carries out various modifications or change under the spirit of the present invention not deviating from.
The domestic debt that turns has all comprised share price at continuous m in the day of trade, have at least n the day of trade closing price be higher than exercise price 130% the time, the publisher has the right to add current interest with capital and redeems the redemption provision that turns debt.The actual effect of this clause is to turn the debt possessor can select to transfer shares when share price reaches redemption provision, and namely redemption provision is the upper limit obstacle clause of share price in fact.Be convenient and describe that the below calls (m, n) to this class clause and turns the debt clause, and the debt American style option that turns that comprises (m, n) and turn the debt clause is commonly referred to as (m, n) and turns debt formula option.We represent 130% exercise price with H in addition, and namely we turn the upper limit obstacle valency of debt formula option.Turn the debt price in order to give like this, we turn the option valuation of debt formula need to for (m, n).
Identical with most of exotic option, (m, n) turns debt formula option does not have analytic solution.Be not fit to turn at present the numerical method of debt formula option valuation both at home and abroad yet.This is because the computing time of numerical method and the calculating step number that cost directly depends on needs.The step number of general barrier options numerical method was tens steps.But turning debt formula option numerical evaluation, (m, n) need to simulate the share price of each stock exchange day.250 day of trade is arranged every year approximately.(m, n) take 4 terms turns debt formula option as example, and we need simulate 1000 day of trade share price, namely needs for 1000 steps.And this just simulates the calculated amount in a share price path.For obtaining a more accurately option premium, we need to simulate several ten thousand paths.The calculating of such numerical method just needs tens million of steps.
For this reason, the invention provides a kind of computer system that turns debt formula option for calculating, see also Fig. 1 and Fig. 2, Fig. 1 is shown as the present invention and is used for calculating the computer system architecture synoptic diagram that turns debt formula option, and Fig. 2 is shown as the method for substitution computing module structural representation that turns the computer system of debt formula option for calculating.As shown in the figure, described computer system 1 comprises at least: processor 11, storer 12, and the method for substitution computing module 13 that is stored in the described storer 12 and is configured to be carried out by described processor 11.
Of particular note, in the present invention, described processor 11 for example is the CPU(central processing unit), described storer 12 comprises storage element 122 and data bank 121, stores a plurality of operation rules in the described data bank 121.Described storer 12 for example is the high speed random access memory, and can comprise nonvolatile memory, for example one or more disk storage devices, flash memory device or other non-volatile memory devices.Can call wherein method of substitution computing module and operation rule to memory access such as CPU.
Described method of substitution computing module 13 comprises: when the closing price that detects the share price day of trade m of a financial product of input and this financial product of concluding the business is higher than the day of trade n of its exercise price one threshold value H, described day of trade m and day of trade n are carried out the first computing unit 131 that the binary tree analog computation goes out customized parameter k; Call the operation rule that prestores in the described data bank, utilize the result of described binary tree simulation to calculate the lower limit H(k that substitutes the obstacle valency) the second computing unit 132, utilize described Monte Carlo simulation the customized parameter k that draws to be verified and revise to obtain to substitute the 3rd computing unit 133 of obstacle valency option, and utilize and substitute obstacle valency option and fix a price and calculate the 4th computing unit 134 of the price that turns debt formula option.Of particular note, in the present invention, described first to fourth unit 131 ~ 134 can for being solidificated in the program segment in the storer 12, also can be compatible chipset in described storer 12.
In a kind of embodiment that can realize, the described operation rule that prestores in the described data bank that calls utilizes the result of described binary tree simulation to calculate the lower limit H(k that substitutes the obstacle valency) the second computing unit in the described operation rule that calls be specially:
H（k）=H×exp（k×σ）；
Wherein, H(k) for substituting the lower limit of obstacle valency, H is the threshold value that the closing price of this financial product of transaction is higher than its exercise price, and k is customized parameter, and σ is the daily fluctuation rate of this financial product share price.Particularly, to be higher than the threshold value H of its exercise price be 130% exercise price to the closing price of described this financial product of transaction.
Described day of trade m and day of trade n are carried out the operation rule that the binary tree analog computation goes out customized parameter k is: selected probable value Q, for the probability that satisfies of the condition of the simulation of different k value day of trade m and day of trade n when binary tree is issued to the lower limit H (k) that substitutes the obstacle valency, selects that described to satisfy probability be customized parameter close to the k value of Q.
The present invention also provides a kind of method that turns debt formula option for calculating, be applied in the above-mentioned computer system with processor and storer, see also Fig. 3, be shown as the present invention and be used for calculating the method flow diagram that turns debt formula option, as shown in the figure, the described method that turns debt formula option for calculating may further comprise the steps:
At first execution in step S1 presets a data bank in described storer, and a plurality of operation rules prestore;
When the closing price that described processor detects the share price day of trade m of a financial product of input and this financial product of concluding the business is higher than the day of trade n of its exercise price one threshold value H, described day of trade m and day of trade n is carried out the binary tree analog computation go out customized parameter k; In the present embodiment, described day of trade m and day of trade n are carried out the operation rule that the binary tree analog computation goes out customized parameter k is: selected probable value Q, for the probability that satisfies of the condition of the simulation of different k value day of trade m and day of trade n when binary tree is issued to the lower limit H (k) that substitutes the obstacle valency, selects that described to satisfy probability be customized parameter close to the k value of Q.
For example, setting this financial product share price is S, and the share price of this financial product after one day rises to uS with the probability of p, drops to S/u with the probability of (1-p), u is the expected yield of this financial product, and for example binary tree simulation hypothesis share price only has two kinds may change every day.Make that share price is S, then the share price after a day rises to uS with the probability of p, drops to S/u with the probability of (1-p).Here the u value is calculated by σ.For example, we select S=H, p=0.5, and then u=exp simulates (30,15) clause with 30 days share price sight of binary tree simulation.
Follow execution in step S2, described processor calls the operation rule that prestores in the described data bank, on the result of described binary tree simulation, further use Monte Carlo simulation to optimize customized parameter k to obtain to substitute the lower limit H(k of obstacle valency option), in the present embodiment, the described operation rule that prestores in the described data bank that calls utilizes the result of described binary tree simulation and Monte Carlo simulation optimization to calculate the lower limit H(k that substitutes the obstacle valency) be specially:
H（k）=H×exp（k×σ）；
Wherein, H(k) be lower limit for the obstacle valency, H is higher than the threshold value of its exercise price for the closing price of this financial product of transaction, and k is customized parameter, and σ is the daily fluctuation rate of this financial product share price.Particularly, to be higher than the threshold value H of its exercise price be 130% exercise price to the closing price of described this financial product of transaction.
For example, each integer k value calculating was reached H(k such as share price in m days), the probability of (m, n) clause is satisfied in its share price path.This probability can calculate by combinatorics and Probability under Two Binomial Tree Model, requires this probability to be not less than 0.8.
In superincumbent (30,15) example, we calculate such as k=3, then reach H(3 such as share price in 30 days), the probability of (30,15) clause is satisfied more than or equal to 0.8262 in its share price path.The corresponding k value of (30,15) clause is 3 like this.
Then execution in step S3 uses Monte Carlo simulation to optimize customized parameter k to obtain to substitute obstacle valency option to the result of binary tree simulation,, the k value that step S2 obtains is carried out Monte Carlo simulation checking and correction that is.The Two Binomial Tree Model advantage of step S2 is can directly carry out theoretical probability to calculate, but we often need to carry out Monte Carlo simulation when the reality price is calculated.Suppose the share price obeys logarithm normal distribution, calculate such as H (k), H (k-0.1), H (k+0.1), H (k-0.2), H (k+0.2) waits the alternative obstacle valency option that produces on the k basis that do not coexist, and choosing wherein turns the immediate alternative obstacle valency of debt formula option Monte Carlo simulation valency as the alternative obstacle valency of revised practicality with (m, n).Application standard statistical test efficiency index when weigh substituting the option valency, different maturity periods a plurality of standard options, different interest rates and stability bandwidth also use different initial share prices, take the correction k value that guarantees as the comprehensive optimum under multiple different situations.
Turn in the debt formula option example in (30,15), calculate with H (3), H (2.9), H (3.1), H (2.8), H (3.2) etc. is the American barrier option valency of obstacle valency, and the simulation valency that turns debt formula option with (30,15) relatively.K=3 is best modified value in this example.
Last execution in step S4, the alternative obstacle valency option of described processor utilization is fixed a price and is calculated the price that turns debt formula option.Because of value and the correction in step S2 and S3, the method of substitution that adopts in this method is applicable to the calculating of multiway tree numerical method and Monte Carlo simulation is calculated, and can use in addition method of substitution to carry out at random partial differential parsing price, and the corresponding debt formula option that turns itself does not have analytic solution.The price that turns debt after drawing the option valency is easy to calculate.
For further highlighting principle of the present invention and effect, the below is the rough schematic of our k method.Show that for convenient we turn debt formula option with one (30,15) is example, selecting initial share price is 1, and the obstacle level is H=1, and the daily fluctuation rate is σ=0.01.According to the example among the above-mentioned steps S3, we have substitution coefficient k=3.We can calculate alternative obstacle share price
H（3）=1×exp（3×0.01）=1.03
See also Fig. 4, for share price for the contrast trend graph of practical obstacle valency in substitute valence.Because substitute valence is higher than the obstacle valency, share price as reach substitute valence then share price must continue for some time to be higher than the practical obstacle valency, this is so that share price more likely satisfies (m, n) condition.Wherein, the point-like dotted line is expressed as share price, and solid line is expressed as substitute valence, and dot-and-dash line is expressed as the obstacle valency, as shown in the figure, whether reaches (30,15) obstacle level such as the share price of direct judgement, and then needing to observe in 30 days share price has on earth how many days more than or equal to 1.Share price has 22 days greater than equaling the obstacle valency in this example.This is reflected in the share price line most of the time more than barrier line, and the substitute valence that the solid line of Fig. 4 represents is our method of substitution obstacle value.The 6th day share price has reached method of substitution obstacle value in Fig. 4, need not then to consider that share price has on earth how many days more than substitute valence.This provides us a way that reduces calculation procedure: we can select per 5 days is a step.See also Fig. 5, only use the trend graph of substitute valence for share price.As shown in the figure, now only use substitute valence, but do not use daily stock price, and only have weekly share price.5 day of trade was arranged weekly, then only have first day, the 6th day, the 11 day etc. share price.This can't directly judge (m, n) condition, and we can be similar to the judgement share price for satisfying (m, n) condition but use substitute valence.The share price that this rough simplification can have been saved our required generation adds up to original 1/5.As shown in Figure 5, wherein, the point-like dotted line is expressed as share price, and solid line is expressed as substitute valence.This share price path is the 1st, 6,11,16, and 21,26,30 days share price had for 6 steps.We can observe the 6th day share price and reach substitute valence.
In above-mentioned example, use reduced behind the method for substitution the needed step of evaluation solution count to original (30,15) turn debt formula option number of steps 1/5th.
Above-described embodiment is illustrative principle of the present invention and effect thereof only, but not is used for restriction the present invention.Any person skilled in the art scholar all can be under spirit of the present invention and category, and above-described embodiment is modified or changed.Therefore, have in the technical field under such as and know that usually the knowledgeable modifies or changes not breaking away from all equivalences of finishing under disclosed spirit and the technological thought, must be contained by claim of the present invention.
Claims (7)
1. one kind is used for calculating the computer system that turns debt formula option, it is characterized in that described computer system comprises at least:
Processor;
Storer comprises storage element and data bank, stores a plurality of operation rules in the described data bank;
The method of substitution computing module, wherein, described method of substitution computing module is stored in the described storage element and is configured to and carried out by described processor, and described method of substitution computing module comprises:
When the closing price that detects the share price day of trade m of a financial product of input and this financial product of concluding the business is higher than the day of trade n of its exercise price one threshold value H, described day of trade m and day of trade n are carried out the first computing unit that the binary tree analog computation goes out customized parameter k;
Call the operation rule that prestores in the described data bank, utilize the result of described binary tree simulation to calculate the lower limit H(k that substitutes the obstacle valency) the second computing unit, utilize described Monte Carlo simulation the customized parameter k that draws to be verified and revise to obtain to substitute the 3rd computing unit of obstacle valency option, and utilize and substitute obstacle valency option and fix a price and calculate the 4th computing unit of the price that turns debt formula option.
2. the computer system that turns debt formula option for calculating according to claim 1, it is characterized in that: the described operation rule that prestores in the described data bank that calls, utilize the result of described binary tree simulation to calculate the lower limit H(k that substitutes the obstacle valency) the second computing unit in the described operation rule that calls be specially:
H（k）=H×exp（k×σ）；
Wherein, H(k) for substituting the lower limit of obstacle valency, H is the threshold value that the closing price of this financial product of transaction is higher than its exercise price, and k is customized parameter, and σ is the daily fluctuation rate of this financial product share price.
3. according to claim 2ly turn the computer system of debt formula option for calculating, it is characterized in that: the threshold value H that the closing price of described this financial product of transaction is higher than its exercise price is 130% exercise price.
4. according to claim 1ly turn the computer system of debt formula option for calculating, it is characterized in that: described day of trade m and day of trade n are carried out the operation rule that the binary tree analog computation goes out customized parameter k is:
Selected probable value Q for the probability that satisfies of the condition of different k value simulations day of trade m and day of trade n when binary tree is issued to the lower limit H (k) that substitutes the obstacle valency, selects that described to satisfy probability be customized parameter close to the k value of Q.
5. one kind is used for calculating the method that turns debt formula option, is applied to have in the computer system of processor and storer, it is characterized in that, said method comprising the steps of:
A default data bank in described storer, a plurality of operation rules prestore;
When the closing price that described processor detects the share price day of trade m of a financial product of input and this financial product of concluding the business is higher than the day of trade n of its exercise price one threshold value H, described day of trade m and day of trade n is carried out the binary tree analog computation go out customized parameter k;
Described processor calls the operation rule that prestores in the described data bank, on the result of described binary tree simulation, further use Monte Carlo simulation to optimize customized parameter k to obtain to substitute the lower limit H(k of obstacle valency option), and utilize and substitute obstacle valency option and fix a price and calculate the price that turns debt formula option and turn debt.
6. the method that turns debt formula option for calculating according to claim 5, it is characterized in that: the described operation rule that prestores in the described data bank that calls, utilize the result of described binary tree simulation and Monte Carlo simulation optimization to calculate the lower limit H(k that substitutes the obstacle valency) be specially:
H(k)=H * exp(k * σ); Wherein, H(k) be lower limit for the obstacle valency, H is higher than the threshold value of its exercise price for the closing price of this financial product of transaction, and k is customized parameter, and σ is the daily fluctuation rate of this financial product share price.
7. according to claim 6ly turn the method for debt formula option for calculating, it is characterized in that: the threshold value H that the closing price of described this financial product of transaction is higher than its exercise price is 130% exercise price.
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| CN111311094A (en) * | 2020-02-14 | 2020-06-19 | 上海东普信息科技有限公司 | Supply chain project analysis method, device, equipment and storage medium |
| CN111507837A (en) * | 2020-04-10 | 2020-08-07 | 浙江万里学院 | Option value calculation system based on time fractional order option pricing model |
| CN111507838A (en) * | 2020-04-10 | 2020-08-07 | 浙江万里学院 | Value evaluation system and method capable of converting bonds |
| CN113312024A (en) * | 2021-06-17 | 2021-08-27 | 中国人民解放军国防科技大学 | Option pricing calculation hardware accelerator, accelerator card and computer equipment |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6493681B1 (en) * | 1999-08-11 | 2002-12-10 | Proxytrader, Inc. | Method and system for visual analysis of investment strategies |
| US20060224491A1 (en) * | 2005-04-01 | 2006-10-05 | De Novo Markets Limited | Trading and settling enhancements to the standard electronic futures exchange market model leading to novel derivatives including on exchange ISDA type credit derivatives and entirely new recovery products including novel options on these |
| US20090055306A1 (en) * | 2004-09-29 | 2009-02-26 | Hirani Sunil G | Systems and Methods for Limit Order Volume Clearing in Online Trading of Credit Derivatives |
-
2012
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6493681B1 (en) * | 1999-08-11 | 2002-12-10 | Proxytrader, Inc. | Method and system for visual analysis of investment strategies |
| US20090055306A1 (en) * | 2004-09-29 | 2009-02-26 | Hirani Sunil G | Systems and Methods for Limit Order Volume Clearing in Online Trading of Credit Derivatives |
| US20060224491A1 (en) * | 2005-04-01 | 2006-10-05 | De Novo Markets Limited | Trading and settling enhancements to the standard electronic futures exchange market model leading to novel derivatives including on exchange ISDA type credit derivatives and entirely new recovery products including novel options on these |
| CN101310298A (en) * | 2005-04-01 | 2008-11-19 | 利菲行政管理公司 | Trading and settling enhancements to electronic futures exchange |
Non-Patent Citations (1)
| Title |
|---|
| 李莉等: "中国上市可转债双因素定价模型研究——基于二叉树和蒙特卡罗模拟方法", 《第四届（2009）中国管理学年会——金融分会场论文集》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111311094A (en) * | 2020-02-14 | 2020-06-19 | 上海东普信息科技有限公司 | Supply chain project analysis method, device, equipment and storage medium |
| CN111507837A (en) * | 2020-04-10 | 2020-08-07 | 浙江万里学院 | Option value calculation system based on time fractional order option pricing model |
| CN111507838A (en) * | 2020-04-10 | 2020-08-07 | 浙江万里学院 | Value evaluation system and method capable of converting bonds |
| CN113312024A (en) * | 2021-06-17 | 2021-08-27 | 中国人民解放军国防科技大学 | Option pricing calculation hardware accelerator, accelerator card and computer equipment |
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