CN108985822A - A kind of used equipment marketing price index generation method - Google Patents

A kind of used equipment marketing price index generation method Download PDF

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Publication number
CN108985822A
CN108985822A CN201810662472.1A CN201810662472A CN108985822A CN 108985822 A CN108985822 A CN 108985822A CN 201810662472 A CN201810662472 A CN 201810662472A CN 108985822 A CN108985822 A CN 108985822A
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index
days
value
sample
used equipment
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CN201810662472.1A
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张庆华
汤吉惠
孙洪全
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Shanghai To Show Internet Technology Co Ltd
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Shanghai To Show Internet Technology Co Ltd
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Priority to CN201810662472.1A priority Critical patent/CN108985822A/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G06Q30/0206—Price or cost determination based on market factors

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  • Business, Economics & Management (AREA)
  • Strategic Management (AREA)
  • Engineering & Computer Science (AREA)
  • Accounting & Taxation (AREA)
  • Development Economics (AREA)
  • Finance (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Game Theory and Decision Science (AREA)
  • Data Mining & Analysis (AREA)
  • Economics (AREA)
  • Marketing (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

A kind of used equipment marketing price index generation method obtains the big data sample B of used equipment comprising steps of defining according to the base period within the period in base perioddWith true sale data sample Sd, utilize big data sample BdValuation model is optimized, and utilizes true sale data sample SdSystematic error correction is done to Optimized model, obtains the value attenuation model for possessing the used equipment of the base period market characteristics；Within the preceding N days periods including statistics day M, effective sale sample S is acquiredp, using the value attenuation model of optimization, calculate every SpThe corresponding value aggregate value of sample, value aggregate value and every SpThe relative error of actual selling price aggregate value in sample is defined as N days M days average index Kn.According to KnAlgorithm, calculate N days M days average index C in the base periodn, KnWith CnDifference be defined as chain base index Kc.By establishing second-hand equipment market price index, society's generally foundation of approval and the information resources and macro economic decision-making that can share is become.

Description

A kind of used equipment marketing price index generation method
Technical field
The present invention is the market price exponentiation algorithm of economics and statistics education field, is related to a kind of Chinese used equipment The internet published method of marketing price index generation method and the index.
Background technique
Currently, Chinese used equipment Market clearing quantity amplifies year by year, price index there is no.Since every new equipment has altogether Same quality standard, and every used equipment quality is all different.So used equipment can not be calculated with usual price index algorithm Price index.Application scenarios of the present invention: 1) the new product market access maturity period, possess between similar different brands product it is good can It is alternative；2) possess the business big data traded under relevant internet environment to secondhand goods.3) can find stablize, be true, by The used equipment true sale data that license-master wants administrative region to be distributed.Currently, there is used car, second-hand in the market for having above-mentioned scene Engineering machinery, second-hand mobile phone, second-hand household electrical appliances etc..
By taking engineering mechanical device market as an example, trillion yuan in annual transaction size, there are two big market circulation channels: newly setting Standby Sales Channel, each manufacturer are a with " equipment+service+old for new service " for pricing model according to administrative region point sales policy processed Other product " old for new service " ratio is up to the 60% of new machine sales volume.This mix and match pricing method, leads to device sales valence Lattice are unintelligible；Second-hand equipment Sales Channel, number of transaction was quickly amplifying in recent years, some used equipment number of transaction are significantly larger than New equipment number of transaction, main market players generally participate in, and market environment is not limited by manufacturer's policy with administrative region, and price is freely competing It strives, equipment and service individually valuation.
Based on the above market analysis, fleamarket can preferably react relation between market supply and demand, become research pair of the invention As.
Summary of the invention
Problem solved by the invention: establishing Chinese used equipment marketing price index, and becoming can share The foundation of market information resource and macro economic decision-making.To solve the above-mentioned problems, the present invention is theoretical base with " law of value " Plinth, Statistics Application principle propose a kind of used equipment marketing price index generation method, use following technology hand Section:
It is defined according to the base period, big data acquisition is carried out to the transaction of used equipment within the period in base period and obtains big data sample Bd, and the true sale of used equipment is acquired and obtains true sale data sample Sd, utilize big data sample BdTo appraisal mould Type optimizes, and utilizes true sale data sample SdSystematic error correction is done to Optimized model, obtains possessing base period market The value attenuation model of the used equipment of feature；
Within the preceding N days periods including statistics day M, effective sale sample S is acquiredp, declined using the value of optimization Subtract model, calculates every SpThe corresponding value aggregate value of sample, the value aggregate value and every SpEffective sale in sample The relative error of price aggregate value is defined as N days M days average index Kn。
According to KnAlgorithm, calculate N days M days average index C in the base periodn, KnWith CnDifference be defined as chain base index Kc。
In a kind of embodiment, whole year previous year in definition statistics year is the base period.
In a kind of embodiment, further include the steps that being filtered average index and chain base index.
In a kind of embodiment, further include the steps that externally issuing average index and chain base index.
The present invention devises the Index Definition for meeting used equipment market practical application scene.Index calculates public according to the present invention Formula can converse the index value of standard price Index Definition.
According to the used equipment marketing price index generation method of above-described embodiment, by establishing the used equipment market price Index becomes society's generally foundation of approval and the information resources and macro economic decision-making that can share.
Detailed description of the invention
Fig. 1 is average index algorithm flow chart；
Fig. 2 is excavator average index curve in 2018；
Fig. 3 is exponent data filtering principle figure.
Specific embodiment
Below by specific embodiment combination attached drawing, invention is further described in detail.
Index date of issue and data acquisition time period define: before when counting day 19, issuing the price index on the same day.Statistics Day Trading sample collection period section be (when the day before yesterday 17, when the same day 17].
Base period definition: annual for the period in base period with a upper year for index publication year.Within the period in base period, adopt Collect the big data set B of used equipment marketing transactiondWith real sales data set Sd, and with data acquisition system BdAnd data set Close SdOptimize used equipment valuation model parameter.Become the model with the base period market characteristics, reacts in used equipment Life Cycle It is worth the canonical algorithm of attenuation law.
Average index definition: within the preceding N days periods including statistics day M, effective sale sample set is acquired. In the sample set, missing between the aggregate value of the selling price of every sample and the aggregate value of every sample base period value relatively Poor (formula -1) is known as N days M days average indexs.The market significance of average index is that reflecting transaction value deviates base period value Ratio.
Chain base index definition: in the case where other statistical conditions are constant, the N days average price indexes and base year of day are counted The difference (formula -2) of N days average price indexes on the same day is known as N days chain base indexs.The market significance of chain base index is to reflect statistics The deviation amplitude of day N days average indexs N days average indexs on the same day than the prior year.
Chain base index=(N days on the i-thth average indexs)-(N days on the i-thth base period average index) formula -2.
By above-mentioned definition, this example realizes comprising the concrete steps that for used equipment marketing price index generation method:
1) it is defined according to the base period, big data acquisition is carried out to the transaction of used equipment within the period in base period and obtains big data sample This Bd, and the true sale of used equipment is acquired and obtains true sale data sample Sd, utilize big data sample BdTo appraisal Model optimizes, and utilizes true sale data sample SdSystematic error correction is done to Optimized model, obtains possessing base period city The value attenuation model of the used equipment of field feature；
2) within the preceding N days periods including statistics day M, effective sale sample S is acquiredp, utilize the value of optimization Attenuation model calculates every SpThe corresponding value aggregate value of sample, the value aggregate value and every SpPractical pin in sample The relative error of price lattice aggregate value is defined as N days M days average index Kn。
3) according to KnAlgorithm, calculate N days M days average index C in the base periodn, KnWith CnDifference be defined as ring ratio and refer to Number Kc；
4) average index and chain base index are filtered；
5) by after filtering processing average index and chain base index externally issue.
Using second-hand hydraulic excavator market price index algorithm in 2018 as example, illustrate the side of exponentiation algorithm and index publication Formula, flow chart as shown in Figure 1, detailed process is as follows description.
The optimization process of apparatus value attenuation model is as follows:
1) base data acquires.
Defining 2017 is the base period.Within the base period, big data sample B is acquireddSet, as second-hand excavator dealing are invited With process of exchange Game of Price digital information；Acquire real trade data sample SdSet, as second-hand excavator exchange intermediary True second-hand excavator transaction data in service enterprise's ERP system.
2) optimize apparatus value attenuation model.
Utilize BdThe second-hand excavator of sample optimization is worth attenuation model parameter, obtains the function representation of primary Optimized model Formula:
Po=F (X) formula -3；
Wherein: X is second-hand excavator life cycle characteristic variable and parameter sets.
3) systematic error is rectified a deviation.
By SdX parameter in sample brings " formula -3 " into and calculates the corresponding apparatus value P of sampleo, " public according to formula Formula -4 " calculates PoWith SdActual selling price P in sampletBetween ratio:
E=∑ Pt/∑PoFormula -4；
Wherein: ∑ refers to SdWhole sample parameter summations.
Systematic error E is substituted into " formula 5 ", in the second-hand excavator life cycle that you can get it is adapted with base period market Value attenuation standard model:
Pe=E*F (X) formula -5.
The calculating process of average index is as follows:
The setting of average index type: according to second-hand hydraulic excavator market periodic characteristics, three average indexs is set: being referred within 30 days Number (N=30), 90 days indexes (N=90), 182 days indexes (N=182), as shown in Figure 2.
The calculating process of N days average indexs is: setting M as index and calculates day, on the section date [M-N+1, M], collects real Border transaction data sample set Sp.By SpSample brings " formula -5 " into and calculates corresponding Pe, M days N are calculated according still further to " formula -6 " It average index Kn:
Kn=(∑ Pt/∑Pe) -1 formula -6；
Wherein: ∑ is in SpSummation in set.
The process that chain base index calculates is as follows:
The setting of chain base index type, according to second-hand hydraulic excavator market periodic characteristics, sets three chain base indexs: referring within 30th Number (N=30), index (N=90) on the 90th, 182 days indexes (N=182).
The calculating of N days chain base indexs, calculates K firstn.Under the conditions of common base period, calculated according to " formula -6 " N days M days price index C of one yearn, chain base index K is calculated according to " formula -7 "c。
Kc=Kn-CnFormula -7.
Exponent data filtering processing: in order to prevent trading volume periodicity low ebb and special deal price fluctuation to the shadow of index It rings, after index calculating, try again low-pass filtering, and Filtering Formula is as follows.
Yn=α * Xn+ (1- α) * Yn-1 formula -8；
Wherein: α is filter factor.
As shown in figure 3, average index KnWith chain base index KcAfter filter process, output valve Kny, Kcy is respectively to filter Average index and chain base index after wave, and as the index finally issued.
The publication of index on the internet: as shown in Figure 1, index is externally issued by internet web page, user passes through three Kind approach uses exponent data: 1) internet computer terminal；2) internet cellphone terminals；3) index information is provided for particular customer Exclusive network interface.
Use above specific case is illustrated the present invention, is merely used to help understand the present invention, not to limit The system present invention.For those skilled in the art, according to the thought of the present invention, can also make several simple It deduces, deform or replaces.

Claims (4)

1. a kind of used equipment marketing price index generation method, which is characterized in that comprising steps of
It is defined according to the base period, the big data sample B of used equipment is obtained within the period in base perioddWith true sale data sample Sd, benefit With big data sample BdValuation model is optimized, and utilizes true sale data sample SdSystematic error is done to Optimized model Correction, obtains the value attenuation model for possessing the used equipment of the base period market characteristics；
Within the preceding N days periods including statistics day M, effective sale sample S is acquiredp, utilize the value decay mode of optimization Type calculates every SpThe corresponding value aggregate value of sample, the value aggregate value and every SpActual selling price in sample The relative error of aggregate value is defined as N days M days average index Kn；
According to KnAlgorithm, calculate N days M days average index C in the base periodn, KnWith CnDifference be defined as chain base index Kc。
2. used equipment marketing price index generation method as described in claim 1, which is characterized in that definition statistics year Whole year previous year be the base period.
3. second-hand equipment price index generation method as described in claim 1, which is characterized in that further include to the average finger The step of several and chain base index is filtered.
4. second-hand equipment price index generation method as claimed in claim 3, which is characterized in that further include by the average finger The step of several and chain base index is externally issued.
CN201810662472.1A 2018-06-25 2018-06-25 A kind of used equipment marketing price index generation method Pending CN108985822A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112418913A (en) * 2020-11-05 2021-02-26 中国科学院城市环境研究所 Price index calculation method for newly-built house, terminal equipment and storage medium
CN115423506A (en) * 2022-08-23 2022-12-02 浪潮卓数大数据产业发展有限公司 Statistical calculation method and system for price index of on-line living necessities

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112418913A (en) * 2020-11-05 2021-02-26 中国科学院城市环境研究所 Price index calculation method for newly-built house, terminal equipment and storage medium
CN115423506A (en) * 2022-08-23 2022-12-02 浪潮卓数大数据产业发展有限公司 Statistical calculation method and system for price index of on-line living necessities

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Application publication date: 20181211