本文選題：財務風險 + OLAP　； 參考：《華北電力大學(北京)》2017年碩士論文

【摘要】：近年來,隨著政府對新能源產(chǎn)業(yè)扶持力度的不斷加大,我國光伏企業(yè)取得了高速發(fā)展。但是,由于我國光伏產(chǎn)業(yè)起步較晚,核心技術(shù)尚不成熟,給企業(yè)的生產(chǎn)經(jīng)營帶來了許多不利影響,容易引發(fā)企業(yè)的財務風險。為了減少光伏企業(yè)財務風險帶來的損失,財務風險分析與預警體系的建立迫在眉睫。然而,面對與日俱增的財務數(shù)據(jù)量,傳統(tǒng)的財務分析方法已經(jīng)不能滿足風險分析的需要。因此,借助商務智能工具OLAP(Online Analytical Processing,即聯(lián)機分析處理),從海量的財務數(shù)據(jù)中挖掘出有用信息,對財務狀況進行多維分析與風險預警,對于企業(yè)的健康發(fā)展尤為必要。本文利用商務智能工具OLAP,針對我國光伏企業(yè)的財務風險分析與預警進行了相關(guān)研究,實現(xiàn)了研究方法的創(chuàng)新。首先,概述了我國光伏企業(yè)的發(fā)展現(xiàn)狀,明確了財務風險和含義及分析方法,綜述了財務預警的內(nèi)涵及模型,闡述了OLAP的相關(guān)理論,為下文研究奠定了理論基礎(chǔ)。其次,按照一定的原則選取25家光伏上市企業(yè)作為樣本,構(gòu)建財務數(shù)據(jù)倉庫,將OLAP技術(shù)應用于財務分析中,利用切片、切塊、旋轉(zhuǎn)、鉆取等方法,從償債風險、營運風險、盈利風險、支付風險等四個方面深入分析了企業(yè)的財務狀況,為財務風險預警模型的指標選取提供了依據(jù)。再次,在多維分析的基礎(chǔ)上,建立了風險預警的星型指標體系,結(jié)合熵權(quán)法確定各個預警指標的權(quán)重,構(gòu)建了財務風險預警模型,并利用判別分析法驗證了預警模型的有效性。最后,以O(shè)LAP立方體作為數(shù)據(jù)源,針對企業(yè)面臨的不同方面的財務風險,采用因子——聚類法將25家樣本企業(yè)劃分為不同的類別,并且有針對性地提出了各自應對財務風險的預警策略。本文所做的研究對企業(yè)管理層、投資者、債權(quán)人等相關(guān)利益決策者都有比較重要的幫助意義。
[Abstract]:In recent years, with the increasing of government support to the new energy industry, photovoltaic enterprises in China have made rapid development. However, due to the late start of photovoltaic industry in China and the immature core technology, it has brought many adverse effects to the production and management of enterprises, which can easily lead to the financial risks of enterprises. In order to reduce the loss caused by the financial risk of photovoltaic enterprises, the establishment of financial risk analysis and early warning system is urgent. However, in the face of increasing financial data, the traditional financial analysis method can not meet the needs of risk analysis. Therefore, with the help of business intelligence tool OLAP(Online Analytical processing, that is, on-line analytical processing, mining useful information from massive financial data and carrying out multidimensional analysis and risk early warning of financial situation, it is particularly necessary for the healthy development of enterprises. Based on the business intelligence tool OLAP, this paper studies the financial risk analysis and early warning of photovoltaic enterprises in China, and realizes the innovation of research methods. Firstly, this paper summarizes the development of photovoltaic enterprises in China, clarifies the financial risk, meaning and analysis methods, summarizes the connotation and model of financial early warning, expounds the relevant theories of OLAP, and lays a theoretical foundation for the following research. Secondly, 25 photovoltaic listed enterprises are selected as samples according to certain principles, and the financial data warehouse is constructed. The OLAP technology is applied to financial analysis, using slice, rotation, drilling and other methods, from debt repayment risk, operating risk, etc. This paper analyzes the financial situation of the enterprise from four aspects: profit risk and payment risk, which provides the basis for selecting the index of financial risk warning model. Thirdly, on the basis of multidimensional analysis, the star index system of risk early warning is established, combined with entropy weight method to determine the weight of each early warning index, the financial risk early warning model is constructed, and the validity of the early warning model is verified by discriminant analysis. Finally, taking the OLAP cube as the data source and aiming at the different financial risks faced by enterprises, 25 sample enterprises are divided into different categories by factor-clustering method. And has pointed out to deal with the financial risk each early warning strategy. The research in this paper is of great help to managers, investors, creditors and other relevant interest decision makers.
【學位授予單位】：華北電力大學(北京)
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F406.7;F426.61

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