The effect of quality measures in testing stocks' irrational exuberance in traumas

Abstract

The Global financial markets have witnessed great traumas due to several events such as the 2000 US stock market crash, the attack of September I Ph 2001, the Afghani war December 2001, and recently the Iraqi war February 2003, the repercussions of which are being felt till today. These events caused immense turbulence in the stability of the stock market and a collapse of investor confidence. One product of accounting evolution is the use of ratios for analyzing financial statements. Originally developed as short-term credit analysis devices, ratios can be traced as far back as the late 19th century. Since then, analysts have developed many financial ratios that are widely used by practitioners and academicians in stock markets (Pottier 1998). Ever since the beginning of the stock market, investors, both professional and casual, have been trying to find secret methods that could lead them towards more wealth. Fundamental analysis is one essential method where traders can rely on it for good forecasting means and generating excess trading profits rather than making rational investment decision and a flip of a coin game that could spoil the company intrinsic value where temporarily high prices are sustained mostly by investor enthusiasm rather than estimation of real value. The purpose of this study is to examine the predictive ability of the quality measures in determining which stock prices would be adversely affected in a crash period. The study will focus on studying the NASDAQ stock market using a sample of 200 listed companies (100 for the analysis sample and another 100 for the holdout). Logistic regression model is used to test the correlation between quality measures and the stock movement. These stocks are subdivided into two groups, which are 1- stocks that are adversely affected during the crash period and 2- stocks that are less affected. The study aims to develop a benchmark that could be used to determine those stocks that would better perform during crash periods.