發(fā)布時間：2018-10-09 11:02

【摘要】：自2007年次貸危機(jī)爆發(fā)以后,迫使各國開始重視風(fēng)險管理的研究。經(jīng)過“金融風(fēng)暴”的爆發(fā),財務(wù)風(fēng)險無處不在,企業(yè)必須時刻注意識別和防范風(fēng)險。本文嘗試著對目前發(fā)展的財務(wù)風(fēng)險管理系統(tǒng)提出適合企業(yè)的財務(wù)風(fēng)險預(yù)警系統(tǒng)。目前我國房地產(chǎn)行業(yè)發(fā)展迅猛,社會及政府部門對其發(fā)展態(tài)勢給予了高度關(guān)注。在經(jīng)濟(jì)形勢嚴(yán)峻的情況下,防范房地產(chǎn)上市公司內(nèi)部財務(wù)風(fēng)險就顯得尤為重要。 本文針對新形勢的發(fā)展?fàn)顟B(tài)下,提出了預(yù)測房地產(chǎn)上市公司財務(wù)風(fēng)險的方法。本文針對房地產(chǎn)行業(yè)龍頭公司—M房地產(chǎn)上市公司進(jìn)行了研究分析,進(jìn)而通過M房地產(chǎn)上市公司的研究方法,推廣到所有房地產(chǎn)上市公司的研究中,并分析了共36家房地產(chǎn)上市公司的財務(wù)風(fēng)險值。本文選取了五大類財務(wù)指標(biāo),包括：每股指標(biāo)、盈利能力、成長能力、營運能力、償債及資本結(jié)構(gòu)共22個財務(wù)指標(biāo)進(jìn)行研究,選取時間為2002年3月31日至2013年3月31日期間的季度財務(wù)數(shù)據(jù)共45個季度數(shù)據(jù)。本文利用熵權(quán)法來進(jìn)行測算權(quán)重,從而算出了綜合測評財務(wù)指標(biāo)序列,再對該序列進(jìn)行時間序列分析的相關(guān)檢驗,主要檢驗包括：單位根檢驗、自相關(guān)性檢驗、ARCH-LM檢驗等。綜合測評財務(wù)指標(biāo)序列通過了單位根檢驗,但存在著3階的自相關(guān)性,同時還檢驗出其存在著高階ARCH效應(yīng),因此對其建立GARCH模型,模型檢驗后發(fā)現(xiàn)消除了之前存在的ARCH效應(yīng),結(jié)論是模型通過檢驗,可以利用GARCH模型來分析。本文通過GARCH模型來計算風(fēng)險VaR值,從而得到綜合測評財務(wù)指標(biāo)值計算出相應(yīng)的財務(wù)風(fēng)險值。為了分析財務(wù)風(fēng)險值,采用自回歸模型(VAR模型)來預(yù)測下一期的風(fēng)險值,預(yù)測階數(shù)為5階,預(yù)測模型的擬合優(yōu)度達(dá)到71.4%,效果較好。另一方面,本文通過建立房地產(chǎn)上市公司財務(wù)風(fēng)險轉(zhuǎn)移概率矩陣進(jìn)一步度量所有房地產(chǎn)上市公司的風(fēng)險轉(zhuǎn)移概率,從而能夠更加有效地控制風(fēng)險。 本文通過建立的預(yù)測模型,能夠合理的分析出下一期的財務(wù)風(fēng)險值,從而可以達(dá)到防范風(fēng)險,預(yù)測風(fēng)險的目的,能夠提前為房地產(chǎn)上市公司的風(fēng)險防范采取適當(dāng)措施,從而能夠為房地產(chǎn)行業(yè)提供更加有效的規(guī)避方法。本文已建立起適合企業(yè)自身發(fā)展的財務(wù)風(fēng)險管理體系,但同時也要不斷完善財務(wù)風(fēng)險管理的系統(tǒng),使預(yù)測效果達(dá)到更佳。
[Abstract]:Since the subprime mortgage crisis broke out in 2007, countries began to attach importance to risk management research. After the outbreak of "financial storm", financial risks are everywhere, enterprises must always pay attention to identify and guard against risks. This paper attempts to put forward a financial risk early warning system suitable for enterprises to develop the current financial risk management system. At present, the real estate industry is developing rapidly in our country, and the society and government departments pay close attention to it. In the severe economic situation, it is particularly important to guard against the internal financial risks of listed real estate companies. In view of the development of the new situation, this paper puts forward a method to predict the financial risk of real estate listed companies. This article has carried on the research analysis to the real estate industry leading company -M real estate listed company, then through the M real estate listed company's research method, popularized to all the real estate listed company's research, And analyzed a total of 36 real estate listed companies financial risk value. This paper selects five kinds of financial indicators, including: per share index, profitability, growth capacity, operating capacity, debt service and capital structure of a total of 22 financial indicators to study. A total of 45 quarterly financial data were selected from March 31, 2002 to March 31, 2013. In this paper, entropy weight method is used to calculate the financial index sequence of comprehensive evaluation, and then the correlation test of time series analysis of this series is carried out. The main tests include unit root test, autocorrelation test and ARCH-LM test. The financial index sequence of comprehensive evaluation has passed the unit root test, but there is a third order autocorrelation, and at the same time, the existence of high order ARCH effect is also tested. Therefore, the GARCH model is established, and the former ARCH effect is eliminated after the model test. The conclusion is that GARCH model can be used to analyze the model. In this paper, the risk VaR value is calculated by GARCH model, and the corresponding financial risk value is calculated by synthetically evaluating the financial index value. In order to analyze the financial risk value, the autoregressive model (VAR model) is used to predict the risk value in the next period. The prediction order is 5 order, and the goodness of fit of the prediction model is 71.4. The effect is good. On the other hand, this paper further measures the risk transfer probability of all listed real estate companies by establishing the financial risk transfer probability matrix of real estate listed companies, so as to control the risk more effectively. Through the prediction model, this paper can reasonably analyze the value of financial risk in the next period, so as to achieve the purpose of risk prevention, forecast risk, and take appropriate measures for the risk prevention of listed real estate companies in advance. Thus, the real estate industry can provide a more effective way to circumvent. This paper has established a financial risk management system suitable for the enterprise's own development, but at the same time, it is necessary to continuously improve the financial risk management system so as to achieve a better forecast effect.
【學(xué)位授予單位】：內(nèi)蒙古工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F299.233.42

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 王蕾;淺析企業(yè)融資風(fēng)險的成因及防范[J];商業(yè)研究;2005年13期

2 李詠梅;楊洋;;財務(wù)風(fēng)險管理研究探析[J];財會通訊;2009年08期

3 潘愛玲,吳有紅;企業(yè)集團(tuán)內(nèi)部控制框架的構(gòu)建及其應(yīng)用[J];中國工業(yè)經(jīng)濟(jì);2005年08期

4 劉斯蓮;;關(guān)于房地產(chǎn)行業(yè)財務(wù)風(fēng)險和防范的研究[J];經(jīng)營管理者;2012年18期

5 王蕾;;淺談房地產(chǎn)行業(yè)財務(wù)風(fēng)險的控制[J];財務(wù)與會計;2012年07期

6 陶萍;蘇里;;房地產(chǎn)公司財務(wù)風(fēng)險控制模式研究[J];建筑管理現(xiàn)代化;2009年05期

7 陳守東,俞世典;基于GARCH模型的VaR方法對中國股市的分析[J];吉林大學(xué)社會科學(xué)學(xué)報;2002年04期

8 邢毅;侯建華;;運用事后監(jiān)督資源 建立央行綜合監(jiān)督系統(tǒng)[J];金融會計;2007年09期

9 譚晉;范曉霞;;增強(qiáng)事后監(jiān)督效能促進(jìn)基層央行大監(jiān)督體系建設(shè)[J];華北金融;2011年01期

10 王昆,宋海洲;三種客觀權(quán)重賦權(quán)法的比較分析[J];技術(shù)經(jīng)濟(jì)與管理研究;2003年06期

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本文編號：2259094