This paper develops a financial distress model using the statistical methodology of time-series Cumulative Sums (CUSUM). The model has the ability to distinguish between changes in the financial variables of a firm that are the result of serial correlation and changes that are the result of...

This paper develops a financial distress model using the statistical methodology of time-series Cumulative Sums (CUSUM). The model has the ability to distinguish between changes in the financial variables of a firm that are the result of serial correlation and changes that are the result of...

The ability to predict corporate financial distress can be strengthened using models that account for serial correlation in the data, incorporate information from more than one period and include stationary explanatory variables. This paper develops a stationary financial distress model for AMEX...

Outlines previous research on business failure prediction models and investigates the impact of serial correlation and non‐stationarity in financial variables on models based on linear discriminant analysis, logit and cumulative sums using 1974‐1991 data from a sample of failed and...

This paper investigates the behavior of exchange rate volatility during appreciations and depreciations. Six US dollar exchange rates are investigated. In all instances the response of volatility to exchange rate changes is asymmetric. For dollar exchange rates with respect to EMS currencies,...