Abstract
The chapter covers a study on forecasting stock prices, which can be a challenging task due to the amount of information and variability involved. The test approach, research, and results cover 50 companies on the US stock market over a 6-year period. Company quarterly and annual financial reports, along with daily stock prices, form the data set analyzed. The financial ratios were tested as independent variables against stock price as the dependent variable. Also, ratio type comparisons and timing scenarios for leading or lagging indicators were covered. Correlation and multiple-regression tests were used to eliminate some ratios, and to find a combination of 12 ratios that successfully account for 35% of the variability in stock prices. The results point to leading indicators, statistically significant ratios, and a predictive model for forecasting stock price.
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