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The Timescale Effects of Corporate Governance Measure on Predicting Financial Distress

Hsin-Hung Chen

Open publisher page 37 citations

Abstract

This study aims to investigate the timescale effects of the corporate governance measure on predicting financial distress of corporations. A new corporate governance measure is adopted in the logistic regression model. Historical data of the companies listed on the Taiwan Stock Exchange Corporation (TSEC) were used in the empirical analysis. The analysis was based on three different prediction horizons comprising one-, two- and three-year horizons. The results confirmed that the accuracy of the logistic regression model for predicting corporate financial distress can be improved by incorporating the corporate governance measure. Moreover, the improvements of the correct rate for classification by incorporating the corporate governance measure increased as the prediction horizon was raised. The improvements of the correct rate for classification by incorporating the corporate governance measure are 2.9%, 4.4% and 5.8% for "Year 1", "Year 2" and "Year 3" models respectively.

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What this paper is about

This study aims to investigate the timescale effects of the corporate governance measure on predicting financial distress of corporations. A new corporate governance measure is adopted in the logistic regression model. Historical data of the companies listed on the Taiwan Stock Exchange Corporation (TSEC) were used in the empirical analysis. The analysis was based on three different prediction horizons comprising one-, two- and three-year horizons. The results confirmed that the accuracy of the logistic regression model for predicting corporate financial distress can be improved by incorporating the corporate governance measure. Moreover, the improvements of the correct rate for classification by incorporating the corporate governance measure increased as the prediction horizon was raised. The improvements of the correct rate for classification by incorporating the corporate governance measure are 2.9%, 4.4% and 5.8% for "Year 1", "Year 2" and "Year 3" models respectively.

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Available abstract

This study aims to investigate the timescale effects of the corporate governance measure on predicting financial distress of corporations. A new corporate governance measure is adopted in the logistic regression model. Historical data of the companies listed on the Taiwan Stock Exchange Corporation (TSEC) were used in the empirical analysis. The analysis was based on three different prediction horizons comprising one-, two- and three-year horizons. The results confirmed that the accuracy of the logistic regression model for predicting corporate financial distress can be improved by incorporating the corporate governance measure. Moreover, the improvements of the correct rate for classification by incorporating the corporate governance measure increased as the prediction horizon was raised. The improvements of the correct rate for classification by incorporating the corporate governance measure are 2.9%, 4.4% and 5.8% for "Year 1", "Year 2" and "Year 3" models respectively.

Key concepts: Corporate governance, Logistic regression, Measure (data warehouse), Corporation, Stock exchange, Business, Financial distress, Actuarial science

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