CN102750651A - Curve fitting-based device and method for processing data - Google Patents

Abstract

The invention discloses a curve fitting-based device for processing data. The device comprises a data storage device, a data preprocessing device, a time series device, a data fitting device and a data output device, wherein the data storage device is used for storing parameters used by a system and calculation results of subsequent devices; the data preprocessing device is used for receiving data of an external data source, reading a timeliness screening rule and storing the preprocessed data in the data storage device; the time series device is used for receiving a notice sent by the data preprocessing device, reading relevant parameters and the preprocessed data, calculating account dates and due dates of all products and constructing a time series according to a cash flow date sequence; the data fitting device is used for calculating a cash flow date parity interest rate and conducting loop iteration on fitting data through the parity interest rate and a discount factor; and the data output device is used for reading the parity interest rate of a required term structure after receiving a notice of the data fitting device, so that the data processing efficiency and the data processing computational accuracy are improved.

Description

A kind of data processing equipment and method based on curve fitting

Technical field

The present invention relates to data processing field, particularly a kind of data processing equipment and method based on curve fitting.

Background technology

Computing machine need obtain the par interest rate and the stability bandwidth information of many term structure quotation products of all categories when prediction markets income and risk fluctuation situation.At present, the technology that adopts in the quotation treatment system is the market quotes data message that directly obtains the main time limit through the market external data base, requires to carry out linear interpolation processing based on many term structures and calculates.Adopt this kind processing mode to mainly contain following defective: the one, the market quotes data message that directly reads the quotation main time limit of product from external data source receives the influence of outside computer system; Possible owing to network failure, origin system failure and other reasons cause obtaining the situation of desired data information, and then cause disposal system to break down; The 2nd, carry out the processing computing method of linear interpolation for the requirement of many term structures and need carry out complicated computing, data-handling efficiency is low, even problems such as the data computation precision is not high can occur.

Summary of the invention

Adopt the linear interpolation processing computing technique need go complicated computing in order to have overcome existing quotation disposal system; Exist data-handling efficiency low; Even the not high defective of the precision of data computation, the invention provides a kind of data processing equipment and method based on curve fitting.

The data processing equipment based on curve fitting that the present invention proposes comprises data storage device, is used for the parameter of storage system use and the result of calculation of follow up device; The data pretreatment unit; Be used to receive the data of external data source, and read ageing screening rule, reject the abnormal data that does not meet rule from said data storage device; To pass through pretreated data and be stored in the said data storage device, and send notice to the time series device; The time series device; Be used to receive the notice that said data pretreatment unit sends; Read correlation parameter and the pretreated data of process in the said data storage device, name day, the date of expiry of calculating each product, and according to cash flow day ordering structure time series; The data fitting device is used to calculate cash flow day par interest rate, through par interest rate, discount factor, the conversion of progressively guiding method of spot interest rate, loop iteration fitting data; Data output device is used for after the notice that receives said data fitting device, from said data storage device, reads the par interest rate of required term structure and offers the user.

The data processing method based on curve fitting that the present invention proposes comprises the steps: step 1, the checksum filter step of effectively offering, and the data pretreatment unit receives data and carries out pre-service; Quotation product unit and system's static parameter are inquired about and read to step 2 from data storage device; Step 3, time series device calculation and quotation curve each the quotation product name day with and the date of expiry; Step 4, the time series device calculates each cash flow day that curve construction relates to, and arranges the time series that makes up curve in order; Step 5, data fitting device are carried out cubic spline interpolation through what the cubic spline method released and can't read quotation for curve cash flow day, read its corresponding par interest rate; Step 6, the data fitting device is a discount factor with the par interest rate swap of each cash flow day, and is stored in the data storage device; Step 7, the data fitting device converts the discount factor of each cash flow day into spot interest rate, and is stored in the data storage device; Step 8, data fitting device be the difference between the circulation of the spot interest rate circulation The Fitting Calculation of each cash flow day, and be stored in the data storage device; Step 9, data output device read the par interest rate of corresponding requirements term structure from data storage device, and data are offered the user.

The par interest rate of predicting many term structures as compared with the past based on the data processing equipment and the method for curve fitting of the present invention or the method for stability bandwidth have realized the raising of data-handling efficiency and data processing computational accuracy.

Description of drawings

Fig. 1 shows the structured flowchart of the data processing equipment that the present invention is based on curve fitting;

Fig. 2 shows the structured flowchart of the time series device in the data processing equipment that the present invention is based on curve fitting;

Fig. 3 shows the structured flowchart of the data fitting device in the data processing equipment that the present invention is based on curve fitting;

Fig. 4 shows the process flow diagram of the data processing method that the present invention is based on curve fitting.

Embodiment

For making the object of the invention, technical scheme and advantage clearer, below in conjunction with specific embodiment, and with reference to accompanying drawing, to further explain of the present invention.

The term that the present invention relates to and the explanation as follows:

Cash flow day: on the date that cash flow changes, include but not limited to date of expiry, the pay date of bond interest.

Change Business Day Convention (" BDC ") working day: convert nonworkdays (for example: weekend, public holiday) into workaday method, as postpone, adjusting type is postponed.

Name day convention settlement convention: the fate on working day between valuation day and name day (just 0 day is t+0, and 1 day is t+1, and 2 days is t+2).

Conversion expires the end of month: the conversion that expires the end of month is the universal method of sign date of expiry at the end of month.

Par interest rate Par rate: make the equipollent Coupon interest rate of bond price and par interest rate.

Spot interest rate Spot rate:N spot interest rate refers to the interest rate of behind n, recouping capital outlay.All interests and capital are realized at n the year end.So according to this definition, the spot interest rate zero breath interest rate that is otherwise known as.Wherein, N and n are natural number.

Day count conventions Day Count Convention (" DCC "): during each cash flow, need the utilization rules specific to calculate fate and the fate in a year between beginning day and the closing day.A lot of different market rules are arranged when calculating these fates, and these different rules also are called day count conventions.DCC is expressed as usually: and the fate in the date fate in computing interval/calculating place year (for example: 30/360, ACTUAL/360, ACTUAL/ACTUAL).

Time series: to the date sequence of cash flow day series arrangement formation.

Standard point: the data interpolating unit will read its par interest rate ri automatically from data storage device cash flow day.Wherein, r and i are natural number.

On schedule nonstandard: for the cash flow day that calculates that does not have corresponding quotation on the market.

Fig. 1 shows the structured flowchart of the data processing equipment that the present invention is based on curve fitting.As shown in Figure 1, this device comprises: data storage device 1, data pretreatment unit 2, time series device 3, data fitting device 4, data output device 5.

Data storage device 1 is used for the parameter that storage system need use and the result of calculation of follow up device.The parameter that system need use comprises system-level parameters, quotation product sound attitude parameter, marketing data image parameter and term structure request.

System-level parameters comprises that curve makes up the correlation parameters such as the ageing requirement of quotation, data precision scope and circulation threshold values of regulation.

Quotation product static parameter comprises changes the expire calendar correlation parameters such as (for example tabulating festivals or holidays) in conversion and affiliated market of BDC, name day convention settlement convention, day count conventions, the end of month working day of the product of offer.

Quotation product dynamic parameter comprises the quotation product date of expiry that may be read into, issue date, correlation parameter such as interest date first.

The static parameter in the market under the main finger receiving of the marketing data image parameter valency product.Specific targets are with above-mentioned quotation product static parameter.As can't read quotation product static parameter, then system will read its affiliated market static parameter automatically.

Data pretreatment unit 2; Be used to receive the data (the for example efficient market of Reuter quotation) of external data source; And from data storage device 1, read screening rule, and reject the abnormal data that does not meet rule, avoid the final target data accuracy of calculating of this type of data influence.As through ageing screening rule, reject the expired data that surpass date range, improve the accurately fixed of follow-up data.To pass through pretreated data and be stored in the data storage device 1, and send notice to time series device 3.

Time series device 3; Receive the notice that data pretreatment unit 2 sends; Correlation parameter of reading of data memory storage 1 (for example name day convention, conversion on working day and date of expiry etc.) and the pretreated data of process; Calculate name day, the date of expiry of each product, and make up time series according to the ordering of cash flow day.Cash flow day is in chronological sequence sorted, and calculate last date of expiry of outputting standard point.

Data fitting device 4; Be used for calculating cash flow day par interest rate through the cubic spline optimization algorithm; Progressively guide method (bootstrapping) to realize three's organic transformation through par interest rate, discount factor, spot interest rate, the loop iteration fitting data reduces the error of calculation.

Data output device 5 is used for after the notice that receives data fitting device 4, from data storage device 1, reads the par interest rate (ResultParRatei) of required term structure and offers the user.

Fig. 2 shows the structured flowchart of the time series device in the data processing equipment that the present invention is based on curve fitting.As shown in Figure 2, time series device 3 comprise Data Date unit 301, name day unit 302, date of expiry unit 303 and cash flow day unit 304.

Data Date unit 301 is used for the term structure request of reading of data memory storage 1, will send to name day unit 302 through the correlation parameter (for example expiring conversion, date of expiry etc. at name day convention " settlement convention ", conversion on working day, time limit, the end of month) after the 2 screening processing of data pretreatment unit.

Name day unit 302 is used for the parameters such as 301 receiving quotation product name day conventions " settlement convention ", conversion on working day, date of expiry from the Data Date unit, calculates name day t according to following steps _Spot, and with the name day t of parameter and each quotation product _SpotSend to date of expiry unit 303.

1) when the quotation product name day convention " settlement convention "=0:t _Spot=t ₀

2) when the quotation product name day convention " settlement convention "=1:t _Spot=t ₀+ 1 (conversion on+working day)

3) when the quotation product name day convention " settlement convention "=2:t _Spot=[t ₀+ 1 (conversion on+working day)]+1 (conversion on+working day)

4) when the quotation product name day convention " settlement convention "=3:t _Spot={ [t ₀+ 1 (conversion on+working day)]+1 (conversion on+working day) }+1 (conversion on+working day)

Wherein, t ₀Be Data Date, i.e. on the date that quotation receives, t is a natural number; (change+working day) expression has been carried out a nonworkdays (for example weekend, public holiday) and has been converted workaday calculating into.

Date of expiry unit 303 is used for from the name day unit 302 receiving quotation product conversions on working day, the end of month data such as conversion, date of expiry that expire, and calculates the date of expiry of the product of offering, and the corresponding date of expiry is sent to cash flow day unit 304.The calculating of date of expiry has following two types:

1) directly from name day unit 302, reads date of expiry t _n

2) as can't directly reading, then can be through name day t with name day unit 302 _SpotWith the date of expiry addition, again according to working day convention adjust nonworkdays and calculate, computing method are following:

t _n=t _Spot+ time expiry (conversion expires the+the end of month) (conversion on+working day)

Wherein, t ₀Be Data Date, i.e. on the date that quotation receives, t is a natural number; (change+working day) expression has been carried out a nonworkdays (for example weekend, public holiday) and has been converted workaday calculating into; The conversion that expires a end of month has been carried out in (conversion expires the+the end of month) expression.

Cash flow day, unit 304 was used for the date of expiry t of the 303 receiving quotation products from the date of expiry unit ₀, to date of expiry t _nTwo kinds of approach that read, the each payment of interest produces the date t of cash flow _iAlso have two kinds of different computing method, concrete grammar is following:

1) for the date of expiry t that calculates _n, cash flow day unit 304 calculate cash flow day through read the similar after the match quotation product in city the longest date of expiry under same payment of interest frequency from date of expiry unit 303.I cash flow day t _iEqual name day t _SpotAdd apart from the fate of this cash flow day again according to convention adjustment on working day, wherein, equal i apart from the fate of this cash flow day and multiply by time limit period:

t _i=t _Spot+ iperiod (conversion expires the+the end of month) (conversion on+working day) i=1 ..., n-1

Wherein, n-1 is the sequence number of cash flow day, and does not comprise date of expiry t _n, wherein n, t are natural number.Time limit equals 12 months divided by payment frequency.

2) for the date of expiry t that directly reads _n, cash flow day unit 304 read correlation parameter from date of expiry unit 303, calculate each quotation product cash flow day according to following steps are independent respectively: i cash flow day t _iEqualing the date of expiry deducts the fate apart from this cash flow day, again according to convention adjustment on working day, wherein equals the time limit apart from the fate of this cash flow day and multiply by n and subtract the poor of i.

t _i=t _n-(n-i) * period (conversion expires the+the end of month) (conversion on+working day) fori=1...n-1

Wherein, n-1 is the sequence number of cash flow day, and does not comprise date of expiry t _n, wherein n, t are natural number.Time limit equals 12 months divided by payment frequency.

Cash flow day unit 304 calculated curves cash flow day t _iAfter the completion, to cash flow day t _iSort and time series is kept in the data storage device 1, and send notice to data fitting device 4.

Fig. 3 shows the structured flowchart of the data fitting device in the data processing equipment that the present invention is based on curve fitting.As shown in Figure 3, data fitting device 4 comprises data interpolating unit 401, Date Conversion Unit 1, Date Conversion Unit 2 403, loop iteration unit 404 and Date Conversion Unit 3 405, Date Conversion Unit 4 406.

Data interpolating unit 401 is used for reading from data storage device 1 time series of the cash flow day of curve.For the cash flow day that has corresponding quotation on the quotation market, data interpolating unit 401 will read its par interest rate r automatically from data storage device 1 _i, with date of this type of cash flow day as standard point.For the cash flow day that does not have corresponding quotation on the market, data interpolating unit 401 will pass through the cubic spline method for this cash flow day t automatically _iIts par interest rate of interpolation calculation r _i, and with date of this type of cash flow day as on schedule nonstandard.

The cubic spline method is with S _i(x)=a _i+ b _i(t-t _i)+c _i(t-t _i) ²+ d _i(t-t _i) ³Formal representation.For one group of known standard point cash flow day t _iAnd corresponding par interest rate r _iArray { (t ₁, r ₁), (t ₂, r ₂) ..., (t _n, r _n), make it satisfy S through the structure cubic spline function _i(t _i)=r _i=S _I-1(t _i), S _i' (t _i)=S _I-1' (t _i), S _i" (t _i)=S _I-1(t _i) and S ₀" (t ₀)=S _n" (t _n)=0, thus one group of n-1 batten obtained.Wherein, a, b, c, d, i, n, t, r, x are natural number.Obtain t through cubic spline _iCorresponding nonstandard par interest rate r on schedule _iBe stored in the data storage device 1.

Calculate through data interpolating unit 401, with each cash flow day t _iCorresponding par interest rate r _iBe stored in the data storage device 1, and notification data converting unit 1 begins to carry out the conversion process flow process of par interest rate to discount factor.

Date Conversion Unit 1 is used for reading par interest rate r from data storage device 1 _iCalculate discount factor DiscountFactor _kConversion from the par interest rate to discount factor can realize through progressively guiding method (bootstrapping), is that once be example half a year with the curve payment frequency, and its calculation procedure is following:

At first, for cash flow day t _iPar interest rate ParRate smaller or equal to six months _k, convert it into the discount factor in corresponding time limit.Because payment frequency be half a year once, so cash flow day t _iOnly can represent a cash flow smaller or equal to six months par interest rates---the principal and interest of repaying at the date of maturity, calculate cash flow day t according to following steps _iEach discount factor DiscountFactor smaller or equal to six months _k:

${\mathrm{DiscountFactor}}_k=\frac{1}{{(1+\frac{{\mathrm{ParRate}}_k}{\mathrm{CompoundFrequency}})}^{{\mathrm{CompoundingFrequency}\×\mathrm{DayCountFactor}}_{\mathrm{StartDate},\mathrm{EndDate}}}}$

Here, DayCountFactor _{StartDate, EndDate}Expression cash flow day t _iThe time interval;

ParRate _kExpression is with the cash flow day t in year _iCorresponding par interest rate r _i

The interest-bearing frequency of Compounding Frequency corresponding product (for instance, bond) is (if payment in a year once then is 1, if semi-annual payment once then is that payment in 2, months once then is 12, by that analogy);

StartDate representes the name day t of this point on the curve _Spot

EndDate representes the cash flow day t of this point on the curve _i

Secondly, for cash flow day t _iPar interest rate ParRate greater than six months _k, discount factor must be calculated according to the sequencing of cash flow, and when calculating n discount factor, front n-1 must all be calculated.Calculate cash flow day t according to following steps _iEach discount factor DiscountFactor greater than six months _k:

${\mathrm{DiscountFactor}}_n=\frac{1-\frac{{\mathrm{ParRate}}_n}{\mathrm{CompoundingFrequency}}\×\underset{i=1}{\overset{n-1}{\mathrm{\Σ}}}{\mathrm{DiscountFactor}}_i}{1+\frac{{\mathrm{ParRate}}_n}{\mathrm{CompoundingFrequency}}}$

Here; 1 expression equals the 1st cash flow pairing discount factor under day the time limit in

; N representes n cash flow pairing discount factor under day; Wherein, n is a natural number.

ParRate _kBe meant cash flow day t with year _iCorresponding par interest rate r _i

The interest-bearing frequency of Compounding Frequency corresponding product (for instance, bond) is (if payment in a year once then is 1, if semi-annual payment once then is that payment in 2, months once then is 12, by that analogy).

Calculate through Date Conversion Unit 1, with each cash flow day t _iCorresponding discount factor DiscountFactor _kBe stored in the data storage device 1, notifications Date Conversion Unit 2 403 begins to carry out the conversion process flow process.

Date Conversion Unit 2 403 is used for from each cash flow day t that data storage device 1 reading of data converting unit 1 calculates _iCorresponding discount factor DiscountFactor _kBe transformed into spot interest rate ZeroCouponRate _iWith the curve payment frequency is that once be example half a year, and its calculation procedure is following:

${\mathrm{ZeroCouponRate}}_i=\mathrm{CompoundingFrequency}*({(1/{\mathrm{DiscountFactor}}_i)}^{\frac{1}{\mathrm{compoundingFrequency}*{\mathrm{DayCountFactor}}_{\mathrm{StartDate},\mathrm{EndDate}}}}-1)$

Here, ZeroCouponRate _iIn 1 expression equal the 1st cash flow pairing spot interest rate under day the time limit, n representes n cash flow pairing spot interest rate under day, wherein, n is a natural number;

DayCountFactor _{StartDate, EndDate}Expression cash flow day t _iThe time interval;

StartDate representes the name day t of this point on the curve _Spot

EndDate representes the cash flow day t of this point on the curve _i

The interest-bearing frequency of Compounding Frequency corresponding product (for instance, bond) is (if payment in a year once then is 1, if semi-annual payment once then is that payment in 2, months once then is 12, by that analogy).

Calculate through Date Conversion Unit 2 403, with cash flow day t _iCorresponding spot interest rate ZeroCouponRate _iBe stored in the data storage device 1, notice loop iteration unit 404 begins to carry out the treatment scheme that circulation reduces error.

Loop iteration unit 404 is used for circular treatment from cash flow day t that data storage device 1 reads _iCorresponding spot interest rate ZeroCouponRate _iCarry out conversion Calculation, reduce error, make data reach the threshold values requirement of system's regulation.1), from data storage device 1, reads earlier the spot interest rate ZeroCouponRate of " standard point " for the nonstandard day of cash flow on schedule _iAs basic array, cubic spline interpolation calculates the spot interest rate NewZeroCouponRate of " on schedule nonstandard " cash flow day _{Spot, ti}After spot interest rate calculated and accomplishes, the loop iteration unit sent notice and gives Date Conversion Unit 3 405, according to the discount factor Newdiscountfactor after the following method computation cycles _{Spot, ti}, and the NewZeroCouponRate that " on schedule nonstandard " cash flow day is corresponding _{Spot, ti}, Newdiscountfactor _{Spot, ti}Be saved in the data storage device 1.

${\mathrm{Newdiscountfactor}}_{\mathrm{sport},\mathrm{ti}}=\frac{1}{{(1+\frac{{\mathrm{NewZeroCouponRate}}_{\mathrm{spot},\mathrm{ti}}}{\mathrm{CompoundingFrequency}})}^{{\mathrm{CompoundingFrequency}*\mathrm{DayCountFactor}}_{\mathrm{Start\; Date},\mathrm{End\; Date}}}}$

Here, DayCountFactor _{StartDate, EndDate}Express time at interval.

The interest-bearing frequency of Compounding Frequency corresponding product (for instance, bond) is (if payment in a year once then is 1, if semi-annual payment once then is that payment in 2, months once then is 12, by that analogy).2), from data storage device 1, read the par interest rate of standard point, notification data converting unit 1 and Date Conversion Unit 2 403, the discount factor Newdiscountfactor after the circulation of calculating " standard point " for the cash flow day of standard point _{Spot, ti}, and spot interest rate NewZeroCouponRate _{Spot, ti}, and be stored in the data storage device 1.

With cash flow day t _iThe spot interest rate NewZeroCouponRate that calculates after the circulation _{Spot, ti}With a preceding spot interest rate ZeroCouponRate who preserves in the data storage device 1 _iRelatively, if both differences reach system's predetermined data accuracy requirement of data storage device 1, then stop the NewZeroCouponRate that circulates _{Spot, ti}, otherwise continue the threshold values requirement of the difference compliance with system until between twice circulation that circulates, and the final spot interest rate ResultZeroCouponRate in back that will circulate _{Spot, ti}Be saved in the data storage device 1.

Date Conversion Unit 3 405 is used for the final spot interest rate ResultZeroCouponRate in data memory storage 1 circulation back _{Spot, ti}Carry out the discount factor conversion, convert Resultdiscountfactor into _{Spot, ti}, and be stored in the data storage device 1.

Date Conversion Unit 4 406 is used for circular treatment final discount factor Resultdiscountfactor after the corresponding circulation of all that data storage device 1 reads cash flow days _{Spot, ti}, according to the par interest rate (Resu/tParRate of the following method calculating term structure of asking _i), be stored in the data storage device 1 notification data output unit 5 after calculating is accomplished.

For cash flow day t _iThe discount factor that is less than or equal to six months cash flow days, calculate according to following method:

$\mathrm{ResultPar}{\mathrm{Rate}}_i=\mathrm{CompoundingFrequency}*({(1/{\mathrm{DiscountFactor}}_{\mathrm{spt},\mathrm{ti}})}^{\frac{1}{\mathrm{compoundingFrequency}*{\mathrm{DayCountFactor}}_{\mathrm{StartDate},\mathrm{EndDate}}}}-1)$

Here, DayCountFactor _{StartDate, EndDate}Express time at interval.

The interest-bearing frequency of Compounding Frequency corresponding product (for instance, bond) is (if payment in a year once then is 1, if semi-annual payment once then is that payment in 2, months once then is 12, by that analogy).

For cash flow day t _iDiscount factor greater than six months cash flow days:

${\mathrm{ResultParRate}}_i=\frac{\mathrm{CompoundingFrequency}*\left({1-\mathrm{Resultdiscountfactor}}_n\right)}{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}\mathrm{Resultdiscountfactorspot},\mathrm{ti}}$

Here; 1 expression time limit equaled the discount factor of 6 months cash flow day in ; N representes the discount factor of n 6 months cash flow day; Wherein, n is a natural number.

The interest-bearing frequency of Compounding Frequency corresponding product (for instance, bond) is (if payment in a year once then is 1, if semi-annual payment once then is that payment in 2, months once then is 12, by that analogy).

Fig. 4 shows the process flow diagram of a kind of data processing method based on curve fitting provided by the invention.

Step 101: the checksum filter step of effectively offering.Data pretreatment unit 2 receives data and carries out pre-service.If system can receive and filter out active data through pre-service, then forward step 102 to, otherwise finish the native system flow process, use the proxima luce (prox. luc) data, and data output device 5 prompting users.

Data pretreatment unit 2 receives the data (the for example efficient market of Reuter quotation) of external data source; And from data storage device 1, read screening rules such as ageing; Rejecting does not meet the abnormal data of rule, avoids the final target data accuracy of calculating of this type of data influence.To pass through pretreated data is stored in the data storage device 1.Step 102: from data storage device 1, inquire about and read quotation product unit and system's static parameter.

Data storage device 1 is used for the parameter that storage system need use and the result of calculation of follow up device.The parameter that system need use comprises system-level parameters, quotation product sound attitude parameter, marketing data image parameter and term structure request.

Step 103: time series device 3 calculation and quotation curves each the quotation product name day with and the date of expiry.

Step 104: time series device 3 calculates each cash flow day that curve construction relates to, and arranges the time series that makes up curve in order.

Step 105: data fitting device 4 releases and can't read cash flow day of quotation through the cubic spline method for curve, carry out cubic spline interpolation and calculate its corresponding par interest rate.

Data interpolating unit 401 in the data fitting device 4 is used for reading from data storage device 1 time series of the cash flow day of curve.For the cash flow day that has corresponding quotation on the quotation market, data interpolating unit 401 will read its par interest rate r automatically from data storage device 1 _i, with date of this type of cash flow day as standard point.For the cash flow day that does not have corresponding quotation on the market, data interpolating unit 401 will pass through the cubic spline method for this cash flow day t automatically _iIts par interest rate of interpolation calculation r _i, and with date of this type of cash flow day as on schedule nonstandard.

Step 106: data fitting device 4 is a discount factor with the par interest rate swap of each cash flow day, and is stored in the data storage device 1.

Date Conversion Unit 402 in the data fitting device 4 is used for reading par interest rate r from data storage device 1 _i, calculate discount factor DiscountFactor _k, the conversion from the par interest rate to discount factor can realize through progressively guiding method (bootstrapping).

Step 107: data fitting device 4 converts the discount factor of each cash flow day into spot interest rate, and is stored in the data storage device 1.

Step 108: data fitting device 4 is the difference between the circulation of the spot interest rate circulation The Fitting Calculation of each cash flow day, the accuracy requirement of Control Circulation match, and be stored in the data storage device 1.If difference compliance with system requirement; Then read final round-robin spot interest rate, and reverse calculation procedure 108, step 107; To be converted into discount factor earlier according to the reverse formula spot interest rate of step 108; Obtain the par interest rate according to the reverse formula of step 107 again, and the result is stored in the data storage device 1, otherwise just continue circulation step 108.

Step 109: data output device 5 reads the par interest rate of corresponding requirements term structure from data storage device 1, data offer the user.

Above-described specific embodiment; The object of the invention, technical scheme and beneficial effect have been carried out further explain, and institute it should be understood that the above is merely specific embodiment of the present invention; Be not limited to the present invention; All within spirit of the present invention and principle, any modification of being made, be equal to replacement, improvement etc., all should be included within protection scope of the present invention.

Claims (16)

1. data processing equipment based on curve fitting comprises:

Data storage device is used for the parameter of storage system use and the result of calculation of follow up device;

The data pretreatment unit; Be used to receive the data of external data source, and read ageing screening rule, reject the abnormal data that does not meet rule from said data storage device; To pass through pretreated data and be stored in the said data storage device, and send notice to the time series device;

The time series device is used to receive the notice that said data pretreatment unit sends, and reads correlation parameter and the pretreated data of process in the said data storage device, and makes up time series according to the ordering of cash flow day;

The data fitting device is used to calculate cash flow day par interest rate, through par interest rate, discount factor, the conversion of progressively guiding method of spot interest rate, loop iteration fitting data;

Data output device is used for after the notice that receives said data fitting device, from said data storage device, reads the par interest rate of required term structure and offers the user.

2. device according to claim 1, wherein, said time series device comprises:

The Data Date unit, the term structure request that is used to read said data storage device will send to the name day unit through the parameter after the said data pretreatment unit screening processing;

The name day unit is used for the reception correlation parameter from the Data Date unit, and calculates the name day parameter, and other correlation parameters of calculation of parameter result and the reception from the Data Date unit are sent to the date of expiry unit;

The date of expiry unit is used for receiving correlation parameter from the name day unit, calculates the date of expiry of quotation product, and the corresponding date of expiry is sent to cash flow day unit;

Cash flow day the unit, be used for from the Expiration Date of Expiration Date unit receiving quotation product, and the cash flow day of calculated curve, to sorting cash flow day and time series being kept in the data storage device, send simultaneously and be notified to the data fitting device.

3. device according to claim 1 and 2, wherein, said data fitting device comprises:

The data interpolating unit; Be used for reading the time series of the cash flow day of curve from data storage device; And the par interest rate that each is corresponding cash flow day is stored in the data storage device, and the notification data converting unit is carried out the conversion process flow process of par interest rate to discount factor at the beginning simultaneously;

Date Conversion Unit one is used for reading the par interest rate from data storage device, calculates discount factor, and the discount factor that each cash flow day is corresponding is stored in the data storage device, and notifications Date Conversion Unit two begins to carry out the conversion process flow process;

Date Conversion Unit two; Be used for from the corresponding discount factor of each cash flow day that data storage device reading of data converting unit one calculates; Be transformed into spot interest rate; Simultaneously that cash flow day is corresponding spot interest rate is stored in the data storage device, and notice loop iteration unit begins to carry out the treatment scheme that circulation reduces error;

The loop iteration unit is used for circular treatment from the corresponding spot interest rate of cash flow day that data storage device reads, and carries out conversion Calculation;

Date Conversion Unit three is used for that the final spot interest rate in data memory storage circulation back is carried out discount factor and changes and be stored in the data storage device;

Date Conversion Unit four is used for circular treatment final discount factor after the corresponding circulation of all that data storage device reads cash flow days, is stored in the data storage device, calculate accomplish after the notification data output unit.

4. device according to claim 3 is characterized in that, for the cash flow day that has corresponding quotation on the quotation market, the data interpolating unit will read its par interest rate r automatically from data storage device _i, with date of this type of cash flow day as standard point, for the cash flow day that does not have corresponding quotation on the market, the data interpolating unit will be automatically through the cubic spline method for this cash flow day t _iIts par interest rate of interpolation calculation r _i, and with date of this type of cash flow day as on schedule nonstandard.

5. device according to claim 4 is characterized in that the cubic spline method is with S _i(x)=a _i+ b _i(t-t _i)+c _i(t-t _i) ²+ d _i(t-t _i) ³Formal representation.For one group of known standard point cash flow day t _iAnd corresponding par interest rate r _iArray { (t ₁, r ₁), (t ₂, r ₂) ..., (t _n, r _n), make it satisfy S through the structure cubic spline function _i(t _i)=r _i=S _I-1(t _i), S _i' (t _i)=S _I-1' (t _i), S _i" (t _i)=S _I-1" (t _i) and S ₀" (t ₀)=S _n" (t _n)=0, thus one group of n-1 batten obtained.Wherein, a, b, c, d, i, n, t, r, x are natural number, obtain t through cubic spline _iCorresponding nonstandard par interest rate r on schedule _iBe stored in the data storage device 1, calculate through the data interpolating unit, each cash flow day t _iCorresponding par interest rate r _iBe stored in the data storage device, and the notification data converting unit is carried out the conversion process flow process of par interest rate to discount factor at the beginning.

6. device according to claim 5 is characterized in that, the loop iteration unit is used for circular treatment from cash flow day t that data storage device reads _iCorresponding spot interest rate ZeroCouponRate _i, make data reach the threshold values requirement of system's regulation, for the nonstandard day of cash flow on schedule, from data storage device, read earlier the spot interest rate ZeroCouponRate of " standard point " _iAs basic array, cubic spline interpolation calculates the spot interest rate NewZeroCouponRate of " on schedule nonstandard " cash flow day _{Spot, ti}

7. device according to claim 6; It is characterized in that; For the cash flow day of standard point; The loop iteration unit reads the par interest rate of standard point from data storage device, send notification data converting unit one and Date Conversion Unit two, the discount factor Newdiscountfactor after the circulation of calculating " standard point " _{Spot, ti}, and spot interest rate NewZeroCouponRate _{Spot, ti}, and be stored in the data storage device.

8. device according to claim 7 is characterized in that, the loop iteration unit is with cash flow day t _iThe spot interest rate NewZeroCouponRate that calculates after the circulation _{Spot, ti}With a preceding spot interest rate ZeroCouponRate who preserves in the data storage device _iRelatively, if both differences reach system's predetermined data accuracy requirement of data storage device, then stop the NewZeroCouponRate that circulates _{Spot, ti}, otherwise continue the threshold values requirement of the difference compliance with system until between twice circulation that circulates, and preserve the final spot interest rate ResultZeroCouponRate in circulation back _{Spot, ti}In data storage device.

9. the data processing method based on curve fitting comprises the steps:

Step 1; The data pretreatment unit receives the data of external data source, and reads ageing screening rule from said data storage device, rejects the abnormal data that does not meet rule; To pass through pretreated data and be stored in the said data storage device, and send notice to the time series device;

Step 2, time series device receive the notice that said data pretreatment unit sends, and read the correlation parameter in the said data storage device and make up time series through pretreated data and according to the ordering of cash flow day;

Step 3, the data fitting device calculates cash flow day par interest rate, through par interest rate, discount factor, the conversion of progressively guiding method of spot interest rate, loop iteration fitting data;

Step 4, data output device read the par interest rate of required term structure and offer the user after the notice that receives said data fitting device from said data storage device.

Wherein the parameter of system's use and the result of calculation of follow up device are stored in the data storage device.

10. method according to claim 9, wherein, said data fitting device further comprises:

The data interpolating unit; Be used for reading the time series of the cash flow day of curve from data storage device; And the par interest rate that each is corresponding cash flow day is stored in the data storage device, and the notification data converting unit is carried out the conversion process flow process of par interest rate to discount factor at the beginning simultaneously;

Date Conversion Unit one is used for reading the par interest rate from data storage device, calculates discount factor, and the discount factor that each cash flow day is corresponding is stored in the data storage device, and notifications Date Conversion Unit two begins to carry out the conversion process flow process;

Date Conversion Unit two; Be used for from the corresponding discount factor of each cash flow day that data storage device reading of data converting unit one calculates; Be transformed into spot interest rate; Simultaneously that cash flow day is corresponding spot interest rate is stored in the data storage device, and notice loop iteration unit begins to carry out the treatment scheme that circulation reduces error;

The loop iteration unit is used for circular treatment from the corresponding spot interest rate of cash flow day that data storage device reads, and carries out conversion Calculation;

Date Conversion Unit three is used for that the final spot interest rate in data memory storage circulation back is carried out discount factor and changes and be stored in the data storage device;

Date Conversion Unit four is used for circular treatment final discount factor after the corresponding circulation of all that data storage device reads cash flow days, is stored in the data storage device, calculate accomplish after the notification data output unit.

11. method according to claim 10, wherein, said time series device further comprises:

The Data Date unit, the term structure request that is used to read said data storage device will send to the name day unit through the parameter after the said data pretreatment unit screening processing;

The name day unit is used for the reception correlation parameter from the Data Date unit, and calculates the name day parameter, and other correlation parameters of calculation of parameter result and the reception from the Data Date unit are sent to the date of expiry unit;

The date of expiry unit is used for receiving correlation parameter from the name day unit, calculates the date of expiry of quotation product, and the corresponding date of expiry is sent to cash flow day unit;

Cash flow day the unit, be used for from the Expiration Date of Expiration Date unit receiving quotation product, and the cash flow day of calculated curve, to sorting cash flow day and time series being kept in the data storage device, send simultaneously and be notified to the data fitting device.

12. method according to claim 11 is characterized in that, for the cash flow day that has corresponding quotation on the quotation market, the data interpolating unit will read its par interest rate r automatically from data storage device _i, with date of this type of cash flow day as standard point, for the cash flow day that does not have corresponding quotation on the market, the data interpolating unit will be automatically through the cubic spline method for this cash flow day t _iIts par interest rate of interpolation calculation r _i, and with date of this type of cash flow day as on schedule nonstandard.

13. method according to claim 12 is characterized in that, the cubic spline method is with S _i(x)=a _i+ b _i(t-t _i)+c _i(t-t _i) ²+ d _i(t-t _i) ³Formal representation.For one group of known standard point cash flow day t _iAnd corresponding par interest rate r _iArray { (t ₁, r ₁), (t ₂, r ₂) ..., (t _n, r _n), make it satisfy S through the structure cubic spline function _i(t _i)=r _i=S _I-1(t _i), S _i' (t _i)=S _I-1' (t _i), S _i" (t _i)=S _I-1" (t _i) and S ₀" (t ₀)=S _n" (t _n)=0, thus one group of n-1 batten obtained.Wherein, a, b, c, d, i, n, t, r, x are natural number, obtain t through cubic spline _iCorresponding nonstandard par interest rate r on schedule _iBe stored in the data storage device 1, calculate through the data interpolating unit, each cash flow day t _iCorresponding par interest rate r _iBe stored in the data storage device 1, and notification data converting unit 1 begins to carry out the conversion process flow process of par interest rate to discount factor.

14. method according to claim 13 is characterized in that, the loop iteration unit is used for circular treatment from cash flow day t that data storage device reads _iCorresponding spot interest rate ZeroCouponRate _i, carry out conversion Calculation, reduce error, make data reach the threshold values requirement of system's regulation, for the nonstandard day of cash flow on schedule, from data storage device, read earlier the spot interest rate ZeroCouponRate of " standard point " _iAs basic array, cubic spline interpolation calculates the spot interest rate NewZeroCouponRate of " on schedule nonstandard " cash flow day _{Spot, ti}

15. method according to claim 14; It is characterized in that; For the cash flow day of standard point; The loop iteration unit reads the par interest rate of standard point from data storage device, send notification data converting unit one and Date Conversion Unit two, the discount factor Newdiscountfactor after the circulation of calculating " standard point " _{Spot, ti}, and spot interest rate NewZeroCouponRate _{Spot, ti}, and be stored in the data storage device.

16. method according to claim 15 is characterized in that, the spot interest rate NewZeroCouponRate that the loop iteration unit calculates after cash flow day ti is circulated _{Spot, ti}With a preceding spot interest rate ZeroCouponRate who preserves in the data storage device _iRelatively, if both differences reach system's predetermined data accuracy requirement of data storage device, then stop the NewZeroCouponRate that circulates _{Spot, ti}, otherwise continue the threshold values requirement of the difference compliance with system until between twice circulation that circulates, and preserve the final spot interest rate ResultZeroCouponRate in circulation back _{Spot, ti}In data storage device.

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