The Empirical Research of Price Fluctuation Rules and Influence Factors with Fresh Produce Sequential Auction Limei Cui

Transcription

1 6h Inernaonal Conference on Sensor Nework and Compuer Engneerng (ICSNCE 016) The Emprcal Research of Prce Flucuaon Rules and Influence Facors wh Fresh Produce Sequenal Aucon Lme Cu Qujng Normal Unversy, Qujng Keywords: Sequenal aucon; Fresh agrculural produc; Prce; Flucuaon rends Absrac. Research he law of prce flucuaons under he fresh agrculural sequenal aucon based on he aucon heory; use Kunmng Inernaonal Flower Aucon Cenre (KIFA) as an example for emprcal analyss. Afer appon he sudy objec whch s he rose of 80 cm lengh for he B level (nework) named Corolla and he sudy perod, he prce rends. Esablsh some reasonable assumpons facors, and hen use he mulple lnear regressons for analyss hese varables. Evenually fnd ha he prevous aucon prce, aucon duraon, he buyer ype (sze) and he seller ypes (sze) and oher facors have a ceran degree of nfluence on he aucon prce flucuaons. Inroducon Sequenal aucon belongs o mul-objec aucons ha are mul objecs beng raded n sequence wh an open prce aucon mechansm whch have a rapd radng speed and a lower radng cos. Along wh he developng of aucon pracce and aucon heory, he marke of wesern counres frs found ha sequenal aucon s very su for radng fresh produce. By mporng sequenal aucon can solve a lo of problems such as lower markeng effcency, hgher markeng cos and so on. I has many benefs for agrculural ndusralzaon. However, because of he characer ha las ransacon prce wll affec curren ransacon n sequenal aucon; he ransacon prce wll generae a grea flucuae wh oher facors over me. Obvously, hs ransacon prce flucuae s dsadvanageous for he aucon parcpan. How o analyss he facors of nfluencng prce formaon and prce flucuae usng he rule of prce flucuae o adop reasonable measures conrol he prce flucuae or made end o smooh and seady s he manly problem o be solved n hs paper. The Flucuaon Rules of Fresh Produce Prce n Sequenal Aucon The flucuaon rules of fresh produce prce n sequenal aucon n hs arcle are based on he long erm aucon pracce of Kunmng Inernaonal Flower Aucon Marke whch s shor for KIFA. The KIFA was se up and pu no operaon a 00; s a large professonal flower radng marke and engage n fresh flowers aucon. Nowadays, he KIFA s become he bgges flower aucon and radng marke n Chna even n Asa. In hs secon, we wll analyze he aucon prce flucuaon phenomenal n he KIFA. All he aucon daa are come from he ransacon hsory daabase of KIFA, 5,61,604 ransacon daa from Dec 1s 007 o Feb nd 010. Accordng o he prelmnary analyss of hese almos sx mllon daa, we fnd here s a superfne rose named Carola n KIFA has he bgges ransacon frequency and bes radng volume and larges ransacon amoun whle he radng class of Carola s class B and he lengh s 80cm. So hs arcle chose he Carola wh 80cm lengh and B class as he manly research objec. And we choose he whole year daa of 008 and 009 of KIFA for a deeply analyze n order o fnd ou he rules and he nfluence of prce flucuaon The auhors - Publshed by Alans Press 601

2 Average prce of 008 Fgure 1. The average prce flucuaon conras of Carola wh 80cm lengh and B class beween 008 and 009 The Fg. 1 drecly shows ha n every year, from May o Augus, he prce flucuaon became sable. Analyze he daa furher; we calculae he mean value and sandard devaon of Carola wh 80cm lengh and B class ransacon prce durng every moh n he year of 008 and 009. Table 1 The average prce and sandard devaon of Carola wh 80cm lengh and B class n each monh of 008 Jan. Feb. Mar. Apr. May. June. July. Aug. Sep. Oc. Nov. Dec. Avg. Prce SD Table The average prce and sandard devaon of Carola wh 80cm lengh and B class n each monh of 009 Jan. Feb. Mar. Apr. May. June. July. Aug. Sep. Oc. Nov. Dec. Avg. Prce SD Table 3 and Table 4 show he classfcaon of daly ransacon prce flucuaon rends of Carola wh 80cm lengh and B class n May 008 and May 009. Among hem, he daa of May 1s 008, May 1s and May 8h 009 are mssng. Table 3 Trends Dae Up Down The classfcaon of daly prce flucuaon rends of Carola wh 80cm lengh and B class n each day of May 008 May 5h, May 9h, May 13h, May 17h, May 18h, May 0h, May 1s, May nd, May 8h, May 30h May nd, May 3rd, May 6h, May 8h, May 10h, May 11h, May 1h, May 15h, May 16h, May 4h, May 5h, May 6h, May 7h Mx May 4h, May 7h, May 14h, May 19h, May 3rd, May 9h, May 31s 7 Toal days

3 Table 4 The classfcaon of daly prce flucuaon rends of Carola wh 80cm lengh and B class n each day of May 009 Trends Dae Toal days Up May 6 h, May 7 h, May 15 h, May 16 h, May 19 h, May 0 h, May 1 s, May 5 h, May 30 h 9 Down May nd, May 3 rd, May 8 h, May 10 h, May 11 h, May 1 h, May 13 h, May 14 h, May 3 rd, May 6 h, May 7 h h, May 9 1 Mx May 4 h, May 5 h, May 9 h, May 17 h, May 18 h, May nd, May 4 h, May 30 h 8 Accordng o analyze hese daa, we found ha prce downrend of he daly ransacon daa of Carola wh 80cm lengh and B class s n he majory, he downrend day oaled 5 n May 008 and May 008, ake up 4.3% of all he samples. In conras, he uprend day oaled 19, ake up 3.% of all he samples, mx rend oaled 15, ake up 5.5% of all he samples. These daa analyss gve us an mporan concluson ha n conras wh abroad, here s a hgher flucuaon level of he fresh produce sequenal aucon prce beween ransacon days n Chna. However, here s a ceran rule of hs flucuaon whch s he runcaon prce downrend as me passed. The Facor and Influence Analyss of Prce Formaon and Flucuaon Base on he case summarze above, hs arcle analyss he daly ransacon prce downrend of Carola wh 80cm lengh and B class n May 009, choose he ransacon daa of May 3rd, May 8h, May 10h and May 3rd o analyze he relevance of fresh produce ransacon prce wh same produc, same class and same qualfcaon n order o fnd ou he basc process of aucon prce formaon. Across o se up an ARIMA formulaon o make a me seres analyss, we ge he resul as shown n Table 5. Table 5 The ARIMA analyss of Carola wh 80cm lengh and B class Dae Formula value p es of May 3 rd 009 prce 0.775prce May 8 h 009 prce prce May 10 h 009 prce prce May 3 rd 009 prce 0.578prce Accordng o Table 5, n he process of daly aucon wh he produce of same produc, same class and same qualfcaon, we found ha he las me ransacon prce has a promnen posve nfluence on curren ransacon prce. Ths resul reveals he marngale heory n sequenal aucon also. Tha s he las me aucon ransacon prce nfluence he curren one. However, based on he nfluence of mul research varable on prce flucuaon, how promnen wll he las me aucon ransacon prce nfluence he curren one, reman o furher analyss, so we buld he followng hypohess: H1: In sequenal aucon, he las me aucon ransacon prce has a promnen posve nfluence on he curren ransacon prce. In he aucon process of KIFA, daly aucon sar a 1:00 pm every ngh, he whole aucon process las hree or four hours. The lengh of aucon me s closely relaed o he supply amoun, every ransacon only need several seconds. The ense aucon process s a bg challenge of aenon and reacon capacy o he aucon parcpans. So we buld he followng hypohess: H: The duraon of daly aucon process has a negave nfluence on ransacon prce. 603

4 For all he bdders and supplers who parcpae he aucon as buyer and seller, mos domesc and abroad reference research her valuaon or bd based on he hypohess of rsk neural aude. Because he rsk aude of parcpae s random. Ths arcle wll no make deep research also. Bu we can fnd he consue scale of buyer and seller from her hsory radng volume, hs wll reac her rsk aude ndrecly. Ths arcle consders he hsory radng volume has ceran nfluence on he prce flucuaon durng aucon process, so we bul he followng hypohess: H3: The buyer scale has a posve nfluence on ransacon prce. H4: The seller scale has a posve nfluence on ransacon prce. Wh he aucon process connue he amoun of aucon goods become smaller. On he conrary of common relaon beween demand and supply, he supply amoun reduce wll lead o a weak bddng end of bdder n sequenal aucon. Tha s he smaller scale parcpae bd more carefully, hs wll lead o a prce flucuaon also. So hs arcle bul anoher hypohess: H5: The amoun of reman goods has a posve nfluence on ransacon prce. The above fve hypoheszes conan he manly facors whch may be nfluence he prce flucuaon of KIFA daly aucon ransacon prce of goods wh same class, same sandard and same produc. We wll make an emprcal research n he nex chaper usng mulple regresson analyss. The Emprcal Research on he Facors of Prce Flucuaon Accordng o he fve hypoheszes of las chaper and he characers of he daa hs arcle research, we choose he ransacon prce of every aucon as he dependen varable of hs research. Ths s he manly research objec also. Wh he fve ndependen varables of rnpr ce means he 1 ransacon prce of each aucon; rn Prce means he ransacon prce of las aucon; durtme means he duraon from he frs aucon of he curren produc; remansup means he remanng supply amoun wh he aucon gong on; buyersum means he hsory oal buy ransacon amoun of Carola wh 80cm lengh and B class.c means he hsory oal sell ransacon amoun of Carola wh 80cm lengh and B class; LnRS means he logarhm of reman supply; buyertype and sellertype are consruced by buyersum and we buld he regresson model as formula 5.1 shows. rnprce rnprce sellersum 4 max sellersum 1.Kn durtme buyersum.accordng o he chosen varables, buyersum 3 max buyersum 1.K n 5 ln( remansup ) Smplfy he formula 5.1 accordng o he consruced varable; we ge he new regresson model as formula 5. shows. rnprce 1 0 1rn Prce durtme sellertype LnRS 4 5 buyertype () To research he nfluence of every varable on ransacon prce from dfferen sde deeply. We break up he formula 5. no formula A and formula B as shown n formula 5.3 and 5.4. We wll research he wo sub formula separaely. 3 (1) 604

5 Formula A: 1 rnce Pr 01 rnce Pr durtme buyertypesellertype 3 4 (3) rn Pr ce rn Pr ce 1 LnRS buyertype sellertype F o r m u l a B : 3 4 ( 4 ) Wh he emprcal research of regresson analyss, we can ge he varable parameer of every formula and he esng summary able as shown n able 5.1. Ths able summarzes and compare analyzes he formula A made up by he daa of May 8h and May 3rd 009 and formula B made up by he daa of May 3rd and May 10h 009. I conans he consan erms and ndependen varables, he R value ndcae he goodness of f of he formula, he F value ndcaes he sgnfcance level of he formula and he P value ndcaes he esng resul of F value of every formula. Table 5.1: The summary shee of each formula parameer and her esng resul Formula & Parameer Varable & Index Formula A Formula A Formula B Formula B Descrbe Indcae R value F value P value of F esng VIF mean value Sample sze The concree formula made by he wo absrac formulas and he daa of four specfc daes above s shown n he Table 6. Table 6 Formula name The analyss dae The summary shee of each formula Formula Formula A May 8 h 009 rn Prce rn Prce 0.03sellerType durTme 0.05buyerType May 3 rd 009 rn Prce durTme 0.434rn Prce 0.06buyerType 0.077sellerType 1 Formula B May 3 rd 009 rn Prce rn Prce 0.061sellerType LnRS 0.033buyerType 605

6 May 10 h 009 rn Prce rn Prce 0.04sellerType LnRS 0.06buyerType In he chaper 4 of hs arcle, accordng o he sequenal heory and he acual analyss on KIFA aucon marke we made fve hypoheses. Combne wh he relaed ndependen varable n hs chaper and he regresson analyss resul of four ransacon daes and wo formulas; we deal he resuls of he fve hypoheses esng as follow. H1: In sequenal aucon, he las me aucon ransacon prce has a promnen posve nfluence on he curren ransacon prce. 1 From able 4. we can fnd ha he values of rn Prce varable ndcae las prce are 0.35, 0.434, and Ths resul s conssen wh he marngale heory of classcs sequenal aucon heory we have menoned above. H: The duraon of daly aucon process has a negave nfluence on ransacon prce. As he able 4. shown, he values of durtme varable whch ndcae he duraon of daly aucon process are -0.03, only n formula A. Ths means ha he duraon of daly aucon process has a negave sgnfcan mpac on ransacon prce. The longer he duraon of daly aucon process s, he cheaper he ransacon prce s. I s because afer long me enson aucon process, no only he aenon of rader wll be decrease bu due o he relaon beween supply and demand, he prce wll presen a downrend also. So combne wh he heory research and emprcal research, we accep hypohess H. H3: The buyer scale has a posve nfluence on ransacon prce. H4: The seller scale has a posve nfluence on ransacon prce. Ths arcle made a quanave analyss on he ndrec facor whch wll be nfluence he rsk aude usng buyer scale and seller scale. We explan he parcpan ype coeffcen accordng o he ransacon amoun of Carola wh 80cm lengh and B class. From able 4. we can fnd ha n he formula A, he regresson coeffcens of buyertype ndcae he buyer ype are 0.05, 0.06; he regresson coeffcens of sellertype ndcae he seller ype are 0.03, Overall, he buyer ype and he seller ype have a posve sgnfcan mpac. Tha s he larger he buyer and seller scale are, he hgher he ransacon prce s. So we accep he hypohess of H3 and H4. H5: The amoun of reman goods has a posve nfluence on ransacon prce. Because he duraon of daly aucon process and he ndependen varable LnRS ndcae he logarhm of reman goods are collnear. We only research he nfluence of LnRS on ransacon prce n formula B. As shown n able 4., he regresson coeffcens of LnRS are 0.014, I means ha along wh he process of aucon, he remanng aucon goods have a posve sgnfcan mpac on ransacon prce. Ths s he manly resul of ransacon prce declne rend along wh he remanng aucon goods amoun declne. Concluson Ths arcle researches he prce flucuaon rules and nfluence facors wh fresh produce sequenal aucon accordng o heory and pracce, and use he KIFA as sample makng emprcal research. Afer choose he research objec, research perod and he prce rend, we make an ARIMA me seres auo regresson analyss on he process of prce formng and confrm ha here s a self-relevance beween sngle day ransacon prce sequences. Base on he above, we buld fve hypoheses whch may be nfluence he prce flucuaon, and buld varables accordng o he hypoheses, analyss hem usng mulple lnear regresson, and fnally es and verfy hese hypoheses. However, because of he lmaon of daa selecon n hs arcle, here has more 606

7 heorecal sgnfcance and praccal sgnfcance o research he prce flucuaon rules usng more oher aucon markes wh new ransacon daa n he fuure. References [1] X You-Mn, Lu Xao-Jun. Pung Aucon Theory o Work: Chna Machne Press.000 [] Mlgrom, P. Du L, Hu Yng-Q. Pung Aucon Theory o Work: Tsnghua Unversy Press, 006 [3] Dou L-Me. The leraure revew abou aucon prce heory research: Journal of Shangha busness school, 009, (10):45-51 [4] Chen Jan, Chen X-Long, Song X-Png, The buyer's sraegy whle group-buyng aucon, Chnese Journal of Managemen Scence,00,(10):1-7 [5] Zhang L, The hree deas abou flower aucon, Chna Flowers & Horculure, 004, ():11-1 [6] L Xan-Guo, Zhang Qan, The operaon research of CC onlne aucon based on he webse self-dae, Chna Sof Scence,009(1),11-11 [7] Wllam Vckrey, Couner speculaon, Aucons, and Compeve Sealed Tenders, Journal of Fnance.16(March l961), 8-37 [8] Paul R. Mlgrom; Rober J. Weber, A Theory of Aucons and Compeve Bddng, Economerca, 198, 50(5), [9] Gerand J, Jan C, Menno P. Declnng Prces n he Sequenal Duch Flower Aucon of Roses, 1999,6,11 [10] Chen Yu, Wang Jang, Yang Bao-Jan. Elecronc Aucon Sysem Based on Inerne:A Case Sudy of Kunmng Flower Elecronc Marke. Proceedng of he 4h Inernaonal Conference on Innovaon and Managemen