Quantitative analysis of large stock market crashes
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Document from the year 2011 in the subject Business economics - Investment and Finance, grade: A, California State University, East Bay, language: English, abstract: The objective of this study is to structure a dependable model to forecast the timing of entry and exit from the stock markets by using multivariate linear regression analysis. The study uses major macroeconomic indicators such CPI, PPI, GDP, MEI as independent variables and the S&P 500 index value as the dependent variable. The sample consists of 30 years of monthly data. This study includes four different loss scenarios in the S...
Document from the year 2011 in the subject Business economics - Investment and Finance, grade: A, California State University, East Bay, language: English, abstract: The objective of this study is to structure a dependable model to forecast the timing of entry and exit from the stock markets by using multivariate linear regression analysis. The study uses major macroeconomic indicators such CPI, PPI, GDP, MEI as independent variables and the S&P 500 index value as the dependent variable. The sample consists of 30 years of monthly data. This study includes four different loss scenarios in the S&P 500 index value and analyzes the data to see if the losses can be absorbed or if further losses will occur. This report discusses the practical implications of using regression analysis and how it is used to predict the market movements. This paper concludes that our regression model can help an investor to anticipate market movements and thus make appropriate buy and sell decisions.
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