Constructing the Regression Model of the Financial Crises : The Impact of the Subprime Mortgage Crisis in U.S.

過去三、四十年來世界各地發生金融危機的頻率較從前高出許多，探究原因後可以發現，與各國陸續開放金融自由化以及國際金融市場快速成長有極大的關係。除此之外，在各國中，金融危機的發生通常具備一些共同特徵，諸如危機發生時會導致資金外流、匯率大幅貶值、股市重挫、產出減少、進出口減少…等影響。因此，面對這一波次級房貸風暴，本研究也即將檢視美國在總體經濟數據上各方面的表現，希望能利用1970年以來已開發國家和開發中國家歷年來所發生的貨幣、銀行危機下所代表的各種總體經濟數據，經過轉化整理後，透過Logistic迴歸模型建立一個迴歸方程式，以了解金融危機的發生與實質匯率、進出口…等其他解釋變數之間的關聯，並利用此模型探測現階段次級房貸風暴對美國可能引發金融危機的機率值，以探討其合理性。We find that the frequencies of the financial crises are higher for the past forty years in the world. It is due to the financial liberalization and international financial markets which grow rapidly. Besides, financial crises usually company with some common characteristics such as capital outflow, the depreciation of the foreign exchange, the shock of the stock market, the decreasing of the production and so on. Therefore, in order to understand this financial crisis of the subprime mortgage, this thesis surveys the economic data of developed countries and developing countries from 1970s and figures out the performances of these countries under balance-of -payments crises or banking crisis. We use the logistic regression model and transform the data to construct a regression model. After understanding the relationship between the explaining variables, we use this model to predict the probability of possible financial crisis in U.S. under the subprime mortgage crisis and then discuss the rationality of those predicted values