Unstable economic conditions have an adverse impact on the financial performance of firms, leading to financial distress, which is an unfavourable situation for investors as it may affect their investment returns. Thus, this study attempted to predict financial distress and to examine the effect of financial distress on stock returns by using firms listed on Bursa Malaysia from 1990 to 2020. This study used the logit model to find the probability of bankruptcy and also as a proxy for financial distress risk in the asset pricing model. From this study, financial distress risk was found to be insignificant in pricing stock returns in all tested models. This finding demonstrates that financial distress risk does not affect stock returns since this risk may be eliminated through diversification.

Research on financial distress has attracted growing attention in the recent past. Enormous corporate failures in history have pointed to the need for deepened research on financial distress. This study attempts to predict the financial distress of listed firms in the Malaysian Stock Market by using firms’ financial ratios. Using Logit Regression Analysis, this study analysed a sample from Malaysian public listed firms from the year 2000 to 2018 to predict the probability of financial distress events. It showed that financial distress such as total assets turnover, earnings before interest and tax to sales, debt ratio, and shareholder’s fund to total debt were found to be significant in predicting financial distress. Based on the confusion matrix approach the developed model showed high accuracy in predicting financial distress since it could predict most of the cases within the sample correctly.

The increasing numbers of financially distressed firms in the Malaysian market demonstrate the importance of predicting financial distress among firms in Malaysia. Using firm financial ratios, this study focuses on predicting financial distress using the hazard model and logistic regression (logit model) based on the Malaysian market. This study used listed firms on the Malaysian stock market from 2000 to 2018 to create two sets of data comprising the main sample and holdout sample in order to compare the predictability between hazard and logit models. The results clearly show that the hazard model is better compared to the logit model in predicting financial distress for the Malaysian market since more variables were found to be significant in addition to the model being more consistent in terms of accuracy.

The Covid-19 pandemic has brought about major changes to the Malaysian economic landscape in terms of productivity level, investment, and household spending. Nonetheless, the unprecedented presence of Covid-19 has caused an unexpected level of disruption to firms from a liquidity and leverage perspective that impacts financial performance. This study focused on financially distressed firms classified under PN17 and GN3 by Bursa Malaysia. Hence, the aim of this study is to examine the impact of liquidity, leverage, and the Covid-19 pandemic period on the financial performance of financially distressed firms in Malaysia which are classified as PN17 and GN3 firms. By using liquidity ratios, financial leverage ratios, and a dummy variable of Covid-19, the result showed that the current ratio, net working capital, and debt ratio were found significant to affect the financial performance. Meanwhile, there is no significant evidence to support that the Covid-19 pandemic has an impact on the performance of financially distressed firms. The finding indicates that the financially distressed firm’s financial performance was purely due to bad management practices, and not contributed by the Covid-19 pandemic.