縣級中國農(nóng)業(yè)發(fā)展銀行貸款需求預測模型的研究和分析
發(fā)布時間:2018-09-14 19:51
【摘要】:本研究主要研究分析縣級區(qū)域的農(nóng)業(yè)經(jīng)濟發(fā)展形勢和貸款資金規(guī)模的關(guān)系。以江西宜黃縣為樣本,搜集與縣級農(nóng)業(yè)發(fā)展銀行貸款資金需求規(guī)模相關(guān)的一些指標數(shù)據(jù),并采用Person相關(guān)性的分析方法,找出與其相關(guān)指標。然后,,利用灰色預測模型GM(1,1)對各個指標的后期變化趨勢進行合理地預測,并嘗試利用多元線性回歸模型對縣級農(nóng)業(yè)發(fā)展銀行的貸款資金需求規(guī)模進行預測,并給出宜黃縣的數(shù)值仿真結(jié)果。主要得到如下結(jié)論: (1)宜黃縣農(nóng)業(yè)經(jīng)濟發(fā)展的各項數(shù)據(jù)指標之間與該縣農(nóng)業(yè)發(fā)展銀行的貸款資金規(guī)模之間存在顯著的正相關(guān)關(guān)系。其中,對縣級農(nóng)業(yè)發(fā)展銀行貸款規(guī)模有影響的主要經(jīng)濟指標有:GDP、財政收入、農(nóng)民人均純收入、社會消費品零售總額、糧食產(chǎn)量等。 (2)以宜黃縣農(nóng)業(yè)發(fā)展銀行貸款資金需求規(guī)模問題為例,展開的數(shù)值仿真結(jié)果顯示:本研究中提出多重GM(1,1)回歸預測模型基本達到預期目的,是從灰色理論出發(fā)進行的一次較為有益的嘗試。 (3)在2014年—2018年之間,宜黃縣農(nóng)業(yè)發(fā)展銀行的貸款需求規(guī)模大體上會呈現(xiàn)逐步上升的趨勢,但是,需要注意的是上升的速度與2011年相比會顯著放緩。
[Abstract]:This study mainly analyzes the relationship between the agricultural economic development situation and the scale of loan funds in county-level regions. Taking Yihuang County of Jiangxi Province as a sample, this paper collects some index data related to the scale of loan fund demand of agricultural development bank at county level, and uses the method of Person correlation analysis to find out the relevant indexes. Then, the grey prediction model GM (1 / 1) is used to predict the late change trend of each index reasonably, and the multivariate linear regression model is used to predict the loan capital demand scale of the county agricultural development bank. The numerical simulation results of Yihuang County are given. The main conclusions are as follows: (1) there is a significant positive correlation between the data of agricultural economic development in Yihuang County and the loan capital scale of the Agricultural Development Bank of Yihuang County. Among them, the main economic indicators that have an impact on the loan size of the county-level agricultural development bank are: GDP, fiscal income, per capita net income of farmers, total retail sales of social consumer goods, (2) taking the scale of loan fund demand of Yihuang Agricultural Development Bank as an example, the numerical simulation results show that: in this study, the multiple GM (1 ~ 1) regression prediction model has basically achieved the expected purpose. It is a useful attempt based on grey theory. (3) between 2014 and 2018, the loan demand of Yihuang County Agricultural Development Bank will increase gradually, but, It is important to note that the rate of increase will be significantly slower than in 2011.
【學位授予單位】:南昌大學
【學位級別】:碩士
【學位授予年份】:2014
【分類號】:F832.4
本文編號:2243707
[Abstract]:This study mainly analyzes the relationship between the agricultural economic development situation and the scale of loan funds in county-level regions. Taking Yihuang County of Jiangxi Province as a sample, this paper collects some index data related to the scale of loan fund demand of agricultural development bank at county level, and uses the method of Person correlation analysis to find out the relevant indexes. Then, the grey prediction model GM (1 / 1) is used to predict the late change trend of each index reasonably, and the multivariate linear regression model is used to predict the loan capital demand scale of the county agricultural development bank. The numerical simulation results of Yihuang County are given. The main conclusions are as follows: (1) there is a significant positive correlation between the data of agricultural economic development in Yihuang County and the loan capital scale of the Agricultural Development Bank of Yihuang County. Among them, the main economic indicators that have an impact on the loan size of the county-level agricultural development bank are: GDP, fiscal income, per capita net income of farmers, total retail sales of social consumer goods, (2) taking the scale of loan fund demand of Yihuang Agricultural Development Bank as an example, the numerical simulation results show that: in this study, the multiple GM (1 ~ 1) regression prediction model has basically achieved the expected purpose. It is a useful attempt based on grey theory. (3) between 2014 and 2018, the loan demand of Yihuang County Agricultural Development Bank will increase gradually, but, It is important to note that the rate of increase will be significantly slower than in 2011.
【學位授予單位】:南昌大學
【學位級別】:碩士
【學位授予年份】:2014
【分類號】:F832.4
【參考文獻】
相關(guān)期刊論文 前10條
1 徐進軍;王海成;白中潔;;灰色預測模型若干改進方法[J];測繪信息與工程;2011年04期
2 費羅曼;胡譽滿;;IS-LM模型預測貸款需求量的Fuzzy系統(tǒng)分析[J];江西電力職業(yè)技術(shù)學院學報;2006年04期
3 麥強盛;;基于BP神經(jīng)網(wǎng)絡的我國金融機構(gòu)信貸規(guī)模預測[J];廣西輕工業(yè);2010年01期
4 陳麗珍;顧偉;;中小企業(yè)獲取銀行信貸:嵌入性視角下的研究[J];商業(yè)研究;2013年02期
5 孫志娟;;基于灰色自校正理論的我國商業(yè)銀行信貸風險預警機制研究[J];湖南社會科學;2013年02期
6 李麗;楊桂元;;基于IOWGA的匯價預測風險程度的組合預測[J];科技和產(chǎn)業(yè);2014年03期
7 王健;;灰導數(shù)優(yōu)化的一類灰色預測直接建模[J];遼寧工程技術(shù)大學學報(自然科學版);2014年04期
8 丁世錄;雷友;張娟;;重慶市新型城鎮(zhèn)化建設金融服務需求預測[J];重慶理工大學學報(社會科學);2014年08期
9 陳耀豐;;甘蔗產(chǎn)業(yè)對銀行貸款需求分析[J];廣東農(nóng)業(yè)科學;2010年08期
10 羅鄂湘;錢省三;李銳;;可變參數(shù)動態(tài)灰色預測模型的建立與實證研究[J];上海理工大學學報;2006年05期
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