本文關(guān)鍵詞：P2P網(wǎng)絡(luò)借貸市場的非線性動力學(xué)特征研究　出處：《東華大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： P2P網(wǎng)絡(luò)借貸市場 BDS檢驗(yàn) 非線性依賴性 R/S分析 非線性動力學(xué)特征

【摘要】：P2P網(wǎng)絡(luò)借貸是一種近年來逐漸興起的個人對個人直接信貸模式。網(wǎng)貸公司通過線上平臺撮合借貸雙方達(dá)成交易。平臺本身扮演信息中介的角色,提供信息披露、信用評級、資金結(jié)算、逾期催收等服務(wù),平臺利潤主要來源于客戶繳納的手續(xù)費(fèi)。P2P網(wǎng)絡(luò)借貸在中國發(fā)展十分迅速,它的出現(xiàn)填補(bǔ)了小額借貸市場的空白。據(jù)網(wǎng)貸之家統(tǒng)計(jì),截至2015年10月底,我國P2P網(wǎng)絡(luò)借貸平臺3598家,歷史累計(jì)成交量終于突破萬億元大關(guān),達(dá)到10983.49億元。2015年10月P2P網(wǎng)絡(luò)借貸行業(yè)綜合收益率為12.38%,10月P2P網(wǎng)絡(luò)借貸行業(yè)平均借款期限為6.78個月,預(yù)計(jì)整個2015年P(guān)2P網(wǎng)絡(luò)借貸行業(yè)平均借款期限都將在7個月左右徘徊。然而,同樣在過去幾年,P2P問題平臺數(shù)量急劇上升,截至2015年10月總量已累計(jì)達(dá)1078家,跑路、停業(yè)、提現(xiàn)困難成為主要問題來源�？梢�,現(xiàn)實(shí)的P2P網(wǎng)絡(luò)借貸市場不是簡單、有秩序的,它既混亂又復(fù)雜。P2P網(wǎng)絡(luò)借貸風(fēng)險(xiǎn)發(fā)生的強(qiáng)度與頻率也遠(yuǎn)比我們理論想象中的要大,風(fēng)險(xiǎn)的復(fù)雜性遠(yuǎn)不是純粹的隨機(jī)游走所能解釋的。P2P網(wǎng)絡(luò)借貸市場參與要素多、變量關(guān)系多、內(nèi)部因果關(guān)系多樣性、強(qiáng)藕合性等特性決定了系統(tǒng)往往是以非線性方式對外界作用產(chǎn)生反應(yīng)。在這種背景下,深入探析P2P網(wǎng)絡(luò)借貸市場的非線性動力學(xué)特征將為研究P2P網(wǎng)絡(luò)借貸市場本質(zhì)特征與實(shí)踐管理提供一個全新的視角。因此,本文采集四列主要反映全國P2P網(wǎng)絡(luò)借貸行業(yè)全貌的日交易指數(shù)時(shí)間序列,初步探索P2P網(wǎng)絡(luò)借貸市場的非線性動力學(xué)特征。運(yùn)用ROR方法對中國P2P網(wǎng)絡(luò)借貸指數(shù)時(shí)間序列進(jìn)行平穩(wěn)化處理,得到適合進(jìn)行深入研究的時(shí)間序列;運(yùn)用BDS非線性檢驗(yàn)方法,實(shí)證分析中國P2P網(wǎng)絡(luò)借貸市場的非線性依賴性特征,結(jié)果表明存在顯著的非線性依賴結(jié)構(gòu),并且其非線性結(jié)構(gòu)可能來源于低維混沌過程;進(jìn)一步地,運(yùn)用經(jīng)典R/S分析方法和修正R/S分析方法,實(shí)證分析中國P2P網(wǎng)絡(luò)借貸時(shí)間序列中是否存在長記憶性特征,結(jié)果表明中國P2P網(wǎng)絡(luò)借貸時(shí)間序列的產(chǎn)生過程均不是獨(dú)立隨機(jī)的,存在大量非線性,但并未顯示出長記憶性特征。綜合判斷,P2P網(wǎng)絡(luò)借貸市場目前的發(fā)展歷史和演化程度尚淺,正處在從簡單線性系統(tǒng)發(fā)展到復(fù)雜巨系統(tǒng)的過渡階段。最后結(jié)合理論和實(shí)證分析,給出相關(guān)建議。
[Abstract]:P2P network lending is a kind of personal to individual direct credit model which is emerging gradually in recent years. The online loan companies make transactions through online platform. The platform itself plays the role of information intermediary. To provide information disclosure, credit rating, fund settlement, overdue collection and other services, the platform profit mainly from customer fees. P2P network lending in China is developing very rapidly. It fills the gap in the small loan market. According to the statistics of Internet loan House, as of the end of October 2015, there are 3 598 P2P network lending platforms in China. In October 2015, the comprehensive yield of P2P network lending industry was 12.38%. In October, the average loan maturity of the P2P network lending industry was 6.78 months, and the average borrowing period of the P2P network lending industry is expected to be around seven months for the whole 2015. In the past few years, the number of P2P problem platforms has risen sharply. By October 2015, the total number of P2P problem platforms had reached 1078, running the road, closing down, making cash difficulties become the main source of problems. The real P2P network lending market is not simple, orderly, it is chaotic and complex. P2P network lending risk occurrence intensity and frequency is much larger than our theoretical imagination. The complexity of risk is far from pure random walk can explain. P2P network lending market participation factors, variables, internal causality diversity. Strong coupling and other characteristics determine that the system often responds to the external action in a nonlinear manner. In this context. Deeply analyzing the nonlinear dynamic characteristics of P2P network lending market will provide a new perspective for the study of the essential characteristics and practical management of P2P network lending market. This paper collects four series of daily transaction index time series which mainly reflect the whole picture of P2P network lending industry in China. The nonlinear dynamic characteristics of P2P network lending market are preliminarily explored. The time series of Chinese P2P network lending index are treated stably by using ROR method, and the time series suitable for further study are obtained. Using the BDS nonlinear test method, this paper empirically analyzes the nonlinear dependence characteristics of Chinese P2P network lending market. The results show that there is a significant nonlinear dependence structure. And its nonlinear structure may be derived from the low dimensional chaotic process. Furthermore, using the classical R / S analysis method and the modified R / S analysis method, the paper empirically analyzes whether there are long memory characteristics in the Chinese P2P network lending time series. The results show that the time series of P2P network lending in China are not independent and random, there are a lot of nonlinear, but do not show the characteristics of long memory. The development history and evolution of P2P network lending market is still shallow, and it is in the transition stage from simple linear system to complex giant system. Finally, combined with theoretical and empirical analysis, the relevant suggestions are given.
【學(xué)位授予單位】：東華大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F724.6;F832.4

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