Model for Predicting Financial Performance of Development and Construction Corporations

Abstract

Performance forecasting is central to aligning an organization’s operations with its strategic direction. Despite the panoply of approaches to performance predictions, relatively few published studies address model development of financial performance predictions for the construction industry. By analyzing the preceding relationship between financial and economic variables and financial performance, this paper proposes an innovative approach to predicting firm financial performance. First, hypothesis tests using data for 42 development and construction corporations listed in the construction sector of the Taiwan Stock Exchange between 1997 Q1 and 2006 Q4 uncover useful relationships between financial performance and financial and economic variables. Second, based on these relationships, a three-stage mathematical modeling procedure is used for cross-sectional model estimation, which is subsequently refined to create firm-specific financial performance-forecasting models for four sample firms. The out-of-sample forecasting accuracy is evaluated using mean absolute percentage error (MAPE). The results show that the cross-sectional model explains 78.9% of the variation in the cross-sectional performance data, and the MAPE values in the forecasting models range from 9.54 to 19.69%.