CN102968744B - A kind of for calculating the computer system and method that turn debt formula option - Google Patents
A kind of for calculating the computer system and method that turn debt formula option Download PDFInfo
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Abstract
The present invention relates to the internal data process field of computing machine, specifically a kind of for calculating the computer system and method that turn debt formula option, be applied in the computer system with processor and storer, described method comprises: first in described storer, preset a data bank, prestore multiple operation rule; When day of trade n higher than its exercise price one threshold value H of the share price day of trade m of a financial product of input and the closing price of this financial product of concluding the business then being detected, binary tree analog computation is carried out to described day of trade m and day of trade n and goes out customized parameter k; Then the operation rule prestored is called, the result utilizing described binary tree to simulate is to calculate the lower limit H(k of alternative obstacle valency), and the customized parameter k drawn is verified and revises to obtain alternative obstacle valency option, and utilize alternative obstacle valency option to carry out the price calculating and turn debt formula option of fixing a price, for solving in prior art for the rudimentary high in cost of production problem of counting yield turning debt formula option value.
Description
Technical field
The present invention relates to the internal data process field of computing machine, particularly relating to a kind of for calculating the computer system and method that turn debt formula option.
Background technology
Stock option provides possessor to buy or sell the power of its corresponding stock to decide valency at certain hour.To fix a price, the option of buying in stocks is called call option, and the option selling stock to fix a 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 valency of decideing and trades security.Option holder can select not all right power.Such as in share price lower than when decideing valency, call option should not go power.And should not go power in share price higher than put option when decideing valency.Option is divided into European style option, Bermuda option by its row power date again, and American style option.European style option only has power of could going at the date of maturity.Bermuda option is provided with specific several row power date, as monthly No. 5, until the date of expiry.American style option then can front time rows arbitrarily be weighed at the date of maturity.We can have European put option like this, American call etc.
The option of dealing and row power date of term is only had to be commonly referred to as common option.Common option is the basic product of modern finance industry.Their the Bu Laike-Si Keersi Black-Scholes Option Pricing Model Black-Scholes being priced at acquisition Nobel prize in economics.Common European style option price has analytic solution.Common option also can add extra clause as required.Such as, barrier options limits the share price upper limit or lower limit, and when share price reaches price limit, option lost efficacy.The option of these Additional Terms is commonly referred to as exotic option.Though exotic option also obeys Bu Laike-Si Keersi model of popularization, there is no analytic solution, and need by multiway tree, or Monte Carlo method etc. asks numerical solution.The cosxts involved in determining price of exotic option are subject to the precision of its numerical solution, and 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 particular company bond.Turn debt can convert distributing and releasing corporation to circulation stock according to agreement exercise price under certain condition.By economic interests analysis, turn debt possessor and be only converted to stock higher than just considering during exercise price turning debt in share price.This equates possessor with the price lower than current share price, buy in stocks with its bond.But as possessor thinks that share price also has rising space, possessor also can select postpone conversion and wait for higher share price.With the language performance of option, turning debt is the corporate bonds containing distributing and releasing corporation's stock American call.
Contain a call option owing to turning debt, turning debt can issue with lower interest rate, reduces the interest burden of publisher.As distributing and releasing corporation's share price goes up, turn debt possessor and also can select to transfer shares, burden repaid by the capital of deduction and exemption publisher.So relative to distribution straight bond, corporation issues turns debt can rationally reduce debt and finance costs.Relative to investor, buy and turn debt and provide one to abandon a part of inchoate interest for cost and exchange the chance of possible stock return for.The American call that such investor needs arm's length pricing to turn debt to comprise, comes and the interest of possible loss makes balance.
From the monitoring and management angle of securities market, turning debt because it comprises bond and option, is a class complex product.For ensureing the reasonable operation turning debt market, what China now issued turn debt all contains following unusual obstacle condition: turn debt for the petrochemical industry of issuing on February 23rd, 2011, one is had to be if share price is in 30 day of trade of continuous print in its terms of issue, have at least 15 day of trade closing price higher than exercise price 130% time, publisher have the right with capital add current interest redeem turn debt.Therefore, need to calculate turning debt formula option value.
The domestic and international most advanced banking software of current use calculates one and turns debt formula option value and want several tens minutes.General fund can comprise and multiplely turns debt, and being easy to reach once calculate needs several hours.The Financial Management such as market analysis and venture analysis monitoring needs to consider that fund is hundreds of, or more the probable value in kind situation, once calculate the calculated amount that can reach several days.This is not only impracticable, also contains assessing the cost of great number.
Thus, how to provide a kind of high efficiency for calculating the computer system turning debt formula option value fast, 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 of for calculating the computer system and method that turn debt formula option, for solving in prior art for the rudimentary high in cost of production problem of counting yield turning debt formula option value.
For achieving the above object and other relevant objects, the invention provides a kind of for calculating the computer system turning debt formula option, described computer system at least comprises: processor; Storer, comprises storage element and data bank, stores multiple operation rule in described data bank;
Method of substitution computing module, wherein, described method of substitution computing module to be stored in described storage element and to be configured to be performed by described processor, described method of substitution computing module comprises: when day of trade n higher than its exercise price one threshold value H of the share price day of trade m of a financial product of input and the closing price of this financial product of concluding the business being detected, carry out to described day of trade m and day of trade n the first computing unit that binary tree analog computation goes out customized parameter k; Call the operation rule prestored in described data bank, the result utilizing described binary tree to simulate is to calculate the lower limit H(k of alternative obstacle valency) the second computing unit, utilize described Monte Carlo simulation to verify the customized parameter k drawn and revise to obtain the 3rd computing unit of alternative obstacle valency option, and utilizing and substitute obstacle valency option and carry out fixing a price and calculate the 4th computing unit of the price turning debt formula option.
In a kind of embodiment that can realize, described in call the operation rule prestored in described data bank, the result utilizing described binary tree to simulate is to calculate the lower limit H(k of alternative 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 of closing price higher than its exercise 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, the closing price of described this financial product of transaction is 130% exercise price higher than the threshold value H of its exercise price.
In a kind of embodiment that can realize, carrying out to described day of trade m and the day of trade n operation rule that binary tree analog computation goes out customized parameter k is: a selected probable value Q, for different k values simulation when binary tree is issued to lower limit H (k) of alternative obstacle valency day of trade m and day of trade n condition meet probability, select described meet probability closest to Q k value be customized parameter.
The present invention also provides a kind of for calculating the method turning debt formula option, is applied in the computer system with processor and storer, said method comprising the steps of: in described storer, preset a data bank, prestore multiple operation rule; When described processor detects day of trade n higher than its exercise price one threshold value H of the share price day of trade m of a financial product of input and the closing price of this financial product of concluding the business, binary tree analog computation is carried out to described day of trade m and day of trade n and goes out customized parameter k; Described processor calls the operation rule prestored in described data bank, the result that described binary tree is simulated uses further Monte Carlo simulation optimize customized parameter k to obtain the lower limit H(k of alternative obstacle valency option), the price calculating and turn debt formula option and turn debt and the alternative obstacle valency option of utilization carries out fixing a price.
In a kind of embodiment that can realize, described in call the operation rule prestored in described data bank, utilize described binary tree to simulate and the result of Monte Carlo simulation optimization to calculate the lower limit H(k of alternative obstacle valency) be specially:
H(k)=H × exp(k × σ); Wherein, H(k) be lower limit for obstacle valency, H is the threshold value of closing price higher than its exercise 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, the closing price of described this financial product of transaction is 130% exercise price higher than the threshold value H of its exercise price.
As mentioned above, of the present invention for calculating the computer system and method that turn debt formula option, there is following beneficial effect:
Practical, of the present invention for calculating the computer system that turns debt formula option and method can be used for all kinds of price turning debt formula option and interchangeable bond.
Precision is high, of the present invention for calculate turn debt formula option computer system and method in the error of the method for substitution numerical solution that adopts and conventional numeric solution be less than per mille.
Have analytic solution, of the present invention have Bu Laike-Si Keersi analytic solution for the debt formula option that turns after calculating the computer system that turns debt formula option and the conversion of method reasonable employment method of substitution, and analytic solution are the theoretical value turning debt formula option, are better than conventional numeric solution.
Speed is fast, of the present invention for calculate turn debt formula option computer system and method when by method of substitution method analytic solution, computing time lower than one second, when method of substitution method numerical solution asked by needs, computing time is also several seconds, and this is greatly better than the several tens minutes computing time of conventional numeric solution.
Modulability is strong, and of the present invention is a customized parameter for calculating the k turned in the computer system of debt formula option and the method for substitution of method, according to the continuous data to share price, or discrete data hypothesis, standard process can be carried out to k.
Accompanying drawing explanation
Fig. 1 is shown as the present invention for calculating the computer system architecture schematic diagram turning debt formula option.
Fig. 2 is shown as the method for substitution computing module structural representation for calculating in the computer system turning debt formula option.
Fig. 3 is shown as the present invention for calculating the method flow diagram turning debt formula option.
Fig. 4 is that share price is for the contrast trend graph of practical obstacle valency in substitute valence.
Fig. 5 is the trend graph that application share price of the present invention only uses substitute valence.
Embodiment
Below by way of specific instantiation, embodiments of the present invention are described, those skilled in the art the content disclosed by this instructions can understand other advantages of the present invention and effect easily.The present invention can also be implemented or be applied by embodiments different in addition, and the every details in this instructions also can based on different viewpoints and application, carries out various modification or change not deviating under spirit of the present invention.
The domestic debt that turns all contains share price in a continuous print m day of trade, have at least n the day of trade closing price higher than exercise price 130% time, publisher has the right to add current interest with capital and redeems and turn the redemption provision of debt.The actual effect of this clause turns debt possessor can select when share price reaches redemption provision to transfer shares, and namely redemption provision is the upper limit obstacle clause of share price in fact.For convenience of describing, below this kind of clause is called that (m, n) turns debt clause, and handle comprises the debt American style option that turns that (m, n) turn debt clause and is commonly referred to as (m, n) and turns debt formula option.We separately represent 130% exercise price with H, and namely we turn the upper limit obstacle valency of debt formula option.Like this in order to fix a price to turning debt, we need to turn the option valuation of debt formula to (m, n).
Identical with most of exotic option, (m, n) turns debt formula option does not have analytic solution.The numerical method turning the option valuation of debt formula is not applicable to both at home and abroad at present yet.This is because the computing time of numerical method and cost directly depend on the calculating step number of needs.The step number of general barrier options numerical method is tens steps.But (m, n) turns the share price that debt formula option numerical evaluation needs to simulate each stock exchange day.About there is 250 day of trade every year.Turn debt formula option for (m, the n) of 4 terms, we need simulate 1000 day of trade share price, namely need 1000 steps.And this is the calculated amount in a simulation share price path.For obtaining an option premium more accurately, we need to simulate several ten thousand paths.The calculating of such numerical method just needs tens million of step.
For this reason, the invention provides a kind of for calculating the computer system turning debt formula option, refer to Fig. 1 and Fig. 2, Fig. 1 is shown as the present invention for calculating the computer system architecture schematic diagram turning debt formula option, and Fig. 2 is shown as the method for substitution computing module structural representation for calculating in the computer system turning debt formula option.As shown in the figure, described computer system 1 at least comprises: processor 11, storer 12, and to be stored in described storer 12 and to be configured to the method for substitution computing module 13 that performed by described processor 11.
It should be noted that, in the present invention, described processor 11 is such as CPU(central processing unit), described storer 12 comprises storage element 122 and data bank 121, stores multiple operation rule in described data bank 121.Described storer 12 is such as high speed random access memory, and can comprise nonvolatile memory, such as one or more disk storage device, flash memory device or other non-volatile memory devices.Such as CPU can call method of substitution computing module wherein and operation rule to memory access.
Described method of substitution computing module 13 comprises: when day of trade n higher than its exercise price one threshold value H of the share price day of trade m of a financial product of input and the closing price of this financial product of concluding the business being detected, carry out to described day of trade m and day of trade n the first computing unit 131 that binary tree analog computation goes out customized parameter k; Call the operation rule prestored in described data bank, the result utilizing described binary tree to simulate is to calculate the lower limit H(k of alternative obstacle valency) the second computing unit 132, utilize described Monte Carlo simulation to verify the customized parameter k drawn and revise to obtain the 3rd computing unit 133 of alternative obstacle valency option, and utilizing and substitute obstacle valency option and carry out fixing a price and calculate the 4th computing unit 134 of the price turning debt formula option.It should be noted that, in the present invention, first to fourth described unit 131 ~ 134 for being solidificated in the program segment in storer 12, can also can be compatible chipset in described storer 12.
In a kind of embodiment that can realize, described in call the operation rule prestored in described data bank, the result utilizing described binary tree to simulate is to calculate the lower limit H(k of alternative 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 of closing price higher than its exercise 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, the closing price of described this financial product of transaction is 130% exercise price higher than the threshold value H of its exercise price.
Carrying out to described day of trade m and the day of trade n operation rule that binary tree analog computation goes out customized parameter k is: a selected probable value Q, for different k values simulation when binary tree is issued to lower limit H (k) of alternative obstacle valency day of trade m and day of trade n condition meet probability, select described meet probability closest to Q k value be customized parameter.
The present invention also provides a kind of for calculating the method turning debt formula option, be applied to and above-mentionedly have in the computer system of processor and storer, refer to Fig. 3, be shown as the present invention for calculating the method flow diagram turning debt formula option, as shown in the figure, describedly to comprise the following steps for calculating the method turning debt formula option:
First perform step S1, in described storer, preset a data bank, prestore multiple operation rule;
When described processor detects day of trade n higher than its exercise price one threshold value H of the share price day of trade m of a financial product of input and the closing price of this financial product of concluding the business, binary tree analog computation is carried out to described day of trade m and day of trade n and goes out customized parameter k; In the present embodiment, carrying out to described day of trade m and the day of trade n operation rule that binary tree analog computation goes out customized parameter k is: a selected probable value Q, for different k values simulation when binary tree is issued to lower limit H (k) of alternative obstacle valency day of trade m and day of trade n condition meet probability, select described meet probability closest to Q k value be customized parameter.
Such as, 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 such as binary tree simulation hypothesis share price only has two kinds may change every day.Make share price be 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 u value is calculated by σ.Such as, we select S=H, p=0.5, u=exp, then simulate (30,15) clause with the share price sight that binary tree is simulated 30 days.
Then step S2 is performed, described processor calls the operation rule prestored in described data bank, the result that described binary tree is simulated use further Monte Carlo simulation optimize customized parameter k to obtain the lower limit H(k of alternative obstacle valency option), in the present embodiment, describedly call the operation rule prestored in described data bank, utilize described binary tree to simulate and the result of Monte Carlo simulation optimization to calculate the lower limit H(k of alternative obstacle valency) be specially:
H（k）=H×exp（k×σ）；
Wherein, H(k) be lower limit for obstacle valency, H is the threshold value of closing price higher than its exercise 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, the closing price of described this financial product of transaction is 130% exercise price higher than the threshold value H of its exercise price.
Such as, each integer k value is calculated as share price reached H(k in m days), its share price path meets the probability of (m, n) clause.This probability can be calculated by combinatorics and Probability under Two Binomial Tree Model, requires that this probability is not less than 0.8.
In superincumbent (30,15) example, we calculate as k=3, then as share price reached H(3 in 30 days), the probability that its share price path meets (30,15) clause is more than or equal to 0.8262.The corresponding k value of (30,15) clause is 3 like this.
Then perform step S3, use Monte Carlo simulation to optimize customized parameter k to obtain alternative obstacle valency option to the result of binary tree simulation, that is, Monte Carlo simulation checking and correction are carried out to the k value that step S2 obtains.The Two Binomial Tree Model advantage of step S2 directly can carry out theoretical probability calculating, but we often need to carry out Monte Carlo simulation when reality price calculates.Assuming that share price obeys logarithm normal distribution, calculate as H (k), H (k-0.1), H (k+0.1), H (k-0.2), H (k+0.2), wait the alternative obstacle valency option that the k basis that do not coexist produces, and choosing wherein turns the immediate alternative obstacle valency of debt formula option Monte Carlo simulation valency and substitutes obstacle valency as revised practicality with (m, n).Use standard statistical test efficiency index when weighing and substituting option valency, different maturity periods multiple standard options, different interest rates and stability bandwidth, also use different initial share prices, is comprehensive optimum in a wide variety of different scenarios with the positive k value of repairing ensured.
(30,15) turn in debt formula option example, 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 compare with the simulation valency that (30,15) turn debt formula option.In this example, k=3 is best modified value.
Finally perform step S4, described processor utilizes alternative obstacle valency option to carry out the price calculating and turn debt formula option of fixing a price.Because of the value in step S2 and S3 and correction, the method of substitution adopted in this method is applicable to multiway tree numerical method and calculates and Monte Carlo simulation calculating, and method of substitution separately can be used to carry out random partial differential parsing price, and the corresponding debt formula option that turns itself does not have analytic solution.The price turning debt after drawing option valency is easy to calculate.
For highlighting principle of the present invention and effect further, be the rough schematic of our k method below.For convenience of display, we turn debt formula option for example with one (30,15), and select initial share price to be 1, obstacle level is H=1, and daily fluctuation rate is σ=0.01.According to the example in 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
Refer to Fig. 4, for share price is for the contrast trend graph of practical obstacle valency in substitute valence.Because substitute valence is higher than obstacle valency, share price as reach substitute valence then share price must continue higher than practical obstacle valency for some time, this make share price more likely meet (m, n) condition.Wherein, dotted line is expressed as share price, and solid line is expressed as substitute valence, dot-and-dash line is expressed as obstacle valency, and as shown in the figure, whether the share price as directly judged reaches (30,15) obstacle level, then need share price in observation 30 days to have how many days be more than or equal to 1 on earth.Share price has 22 days to be more than or equal to 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 share price of the 6th day reaches method of substitution obstacle value in the diagram, then without the need to considering that share price has on earth how many days more than substitute valence.This provide the way of our a minimizing calculation procedure: we can select within every 5 days, be a step.Refer to Fig. 5, for share price only uses the trend graph of substitute valence.As shown in the figure, now only use substitute valence, but do not use daily stock price, and only have share price weekly.There is weekly 5 day of trade, then only have first day, the 6th day, the share price of the 11 day etc.This cannot directly judge (m, n) condition, but we can be similar to and judge that share price is as satisfied (m, n) condition to use substitute valence.This rough simplification can have been saved our the required share price generated and add up to original 1/5.As shown in Figure 5, wherein, dotted line is expressed as share price, and solid line is expressed as substitute valence.This article share price path is the 1st, 6,11,16,21, and the share price of 26,30 days, has 6 steps.The share price that we can observe the 6th day reaches substitute valence.
The step decreased use method of substitution in above-mentioned example after required for evaluation solution is counted to original (30,15) and is turned 1/5th of the number of steps of debt formula option.
Above-described embodiment is illustrative principle of the present invention and effect thereof only, but not for limiting the present invention.Any person skilled in the art scholar all without prejudice under spirit of the present invention and category, can modify above-described embodiment or changes.Therefore, such as have in art usually know the knowledgeable do not depart from complete under disclosed spirit and technological thought all equivalence modify or change, must be contained by claim of the present invention.
Claims (6)
1. for calculating the computer system turning debt formula option, it is characterized in that, described computer system at least comprises:
Data bank, stores multiple operation rule;
Method of substitution computing module, comprising:
First computing unit, when day of trade n higher than its exercise price one threshold value H of the share price day of trade m of a financial product of input and the closing price of this financial product of concluding the business being detected, binary tree analog computation is carried out to described day of trade m and day of trade n and goes out customized parameter k;
Second computing unit, calls the operation rule prestored in described data bank, and the result utilizing described binary tree to simulate is to calculate lower limit H (k) of alternative obstacle valency;
3rd computing unit, utilizes Monte Carlo simulation to verify the customized parameter k drawn and revises to obtain alternative obstacle valency option; And
4th computing unit, utilizes alternative obstacle valency option to carry out the price calculating and turn debt formula option of fixing a price;
Wherein, carrying out to described day of trade m and the day of trade n operation rule that binary tree analog computation goes out customized parameter k is: a selected probable value Q, for different k values simulation when binary tree is issued to lower limit H (k) of alternative obstacle valency day of trade m and day of trade n condition meet probability, select described meet probability closest to Q k value be customized parameter.
2. according to claim 1 for calculating the computer system turning debt formula option, it is characterized in that: described in call the operation rule prestored in described data bank, the result utilizing described binary tree to simulate is specially to calculate the described operation rule called in the second computing unit of lower limit H (k) of alternative obstacle valency:
H(k)＝H×exp(k×σ)；
Wherein, H (k) is the lower limit substituting obstacle valency, and H is the threshold value of closing price higher than its exercise 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.
3. according to claim 2 for calculating the computer system turning debt formula option, it is characterized in that: the closing price of described this financial product of transaction is 130% exercise price higher than the threshold value H of its exercise price.
4., for calculating the method turning debt formula option, being applied in the computer system with processor and storer, it is characterized in that, said method comprising the steps of:
In described storer, preset a data bank, prestore multiple operation rule;
When described processor detects day of trade n higher than its exercise price one threshold value H of the share price day of trade m of a financial product of input and the closing price of this financial product of concluding the business, binary tree analog computation is carried out to described day of trade m and day of trade n and goes out customized parameter k;
Described processor calls the operation rule prestored in described data bank, the result that described binary tree is simulated use further Monte Carlo simulation optimize customized parameter k to obtain lower limit H (k) of alternative obstacle valency option, the price calculating and turn debt formula option and turn debt and the alternative obstacle valency option of utilization carries out fixing a price;
Wherein, carrying out to described day of trade m and the day of trade n operation rule that binary tree analog computation goes out customized parameter k is: a selected probable value Q, for different k values simulation when binary tree is issued to lower limit H (k) of alternative obstacle valency day of trade m and day of trade n condition meet probability, select described meet probability closest to Q k value be customized parameter.
5. according to claim 4 for calculating the method turning debt formula option, it is characterized in that: described in call the operation rule prestored in described data bank, utilize described binary tree to simulate and the result of Monte Carlo simulation optimization is specially to lower limit H (k) calculating alternative obstacle valency:
H (k)=H × exp (k × σ); Wherein, H (k) is the lower limit substituting obstacle valency, and H is the threshold value of closing price higher than its exercise 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.
6. according to claim 5 for calculating the method turning debt formula option, it is characterized in that: the closing price of described this financial product of transaction is 130% exercise price higher than the threshold value H of its exercise price.
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| 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 |
| CN113312024B (en) * | 2021-06-17 | 2022-05-24 | 中国人民解放军国防科技大学 | Option pricing calculation hardware accelerator, accelerator card and computer equipment |
Citations (2)
| 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 |
| CN101310298A (en) * | 2005-04-01 | 2008-11-19 | 利菲行政管理公司 | Trading and settling enhancements to electronic futures exchange |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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
- 2012-11-23 CN CN201210480236.0A patent/CN102968744B/en not_active Expired - Fee Related
Patent Citations (2)
| 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 |
| 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 |
|---|
| 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;李莉等;《第四届（2009）中国管理学年会——金融分会场论文集》;20091114;第308-317页 * |
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