台灣電子業財務危機預警模型之研究-以財務與非財務比率建構

A Study of The Financial Crisis Prediction Model for Electronic Industry in Taiwan established by Financial and Nonfinancial Ratios

杜柏毅(Bo-Yi Du)

指導教授 ： 洪進朝

長榮大學/管理學院/經營管理研究所(博)/碩士(2007年)

摘要

過去幾年，我國證券市場蓬勃發展，不僅為公司募集資金，也成為大眾投資的主要管道，因此企業經營狀況與大眾息息相關。但占證券市場交易比重最高的電子業，發生財務危機的事件卻時有所聞，對社會造成嚴重的負面影響。一般投資者常利用與同業相比有異常變動之財務比率，來作為發現危機公司的線索，卻忽略公司發生財務危機，並非一朝一夕，其面臨債務無法償還、應收帳款無法順利回收、獲利無法提升、股權結構變化及公司財務結構不佳等，都有一個時間區間，而這些可能情況，亦會反應於報表趨勢中。
本研究將財務變數變動為一基本模型，加入公司規模、股權結構和市場因子等非財務變數之變動率，帶入模型後探討。以各比率與前一季之歷史數據間關係，所形成反應變化之趨勢，來探討對財務危機預警模型影響。結果發現，單財務變數變動量模型對危機機率在前一季至前二季間有很強的解釋能力，但在前二季至前三季間卻降低很多，表示企業在發生危機前一季至前二季間，財務比率會有異常變動的情形。而在加入非財務之公司規模、股權集中度和市場因子變動率變數後，兩個期間內的解釋能力都大幅提升，表示對模型有非常顯著的影響。因此本研究認為危機公司發生的原因主要為公司舉債過多，造成利息支出大幅增加；另外公司獲利逐季大幅下降，造成現金流入減少，銀行對公司緊縮信用之行為，都讓公司發生資金缺口現象；而股東、經理人持股異常增加，對公司之影響力上升，也加速危機的發生。

關鍵字

財務變動量 ； 非財務變動率 ； LOGIT模型

並列摘要

Taiwanese security market during the recent years has been flourishing in an active step. This development or growth not only helpfully absorbs more and more capital for companies, but becomes the chief channel for mass investment. Therefore, no doubt the success or failure of business management deeply concerns massive investors’ benefits. Financial crises, however, happen to Taiwanese electronic industry so frequently, which has the largest proportion in the security market. These events do have seriously negative influences on the society. In general, the common investors often exploit unusual financial ratios compared with other crafts, as the main clue to discover companies in crises. They, however, neglect a key point: financial crises of these enterprises do not rise overnight. Debt-insolvency, uncollectible accounts receivable without being collected, low profits, and bad concentrative ownership and concentrative financial, should exist or emerge for some time. These possible conditions, too, are reflected from financial reports.
This research sets financial variables as a basic model. with increasing unfinancial variables, notably size of firm, concentrative ownership and factor of market. In order to discuss the influence on Financial Crisis Prediction Model, it is necessary to make a comparison between the data of these unfinancial variables and the debt of the last season. The result is that the model of financial variables simply is so helpful to explain the
crisis-rate in the last first and second seasons, but its availability or effectiveness considerably declines during the last second and third seasons. What it means is that there would be some unusual changes in companies’ financial ratios between the last first and second seasons before falling in crises. Furthermore, after adding the unfinancial elements, including size of firm, ownership concentration, and factor of market, this model becomes
much more useful to analyze both two periods. Clearly, these three financial variables do enhance effectiveness of this model.
This research finally indicates and concludes several key factors for enterprises in crises. First of all, overmuch debt of enterprises causes growing interest expense. The significant decline of company benefits, secondly, leads to the decrease of cash flow and credit freeze by banks. Following both of them is a more serious damage to companies: large shortage of funding. Moreover, the unusual growth of ownership percentage in hands of major shareholdings and mangers would strengthen their domination over enterprises, so as to aggravate these crises.

並列關鍵字

Financial Variables Chamge ； Nonfinancial Variables Chang Rate ； Logit Model

參考文獻

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