ECOM5005 Business Analytics and Data Visualisation Presentation

When a company cannot generate enough revenue to cover its financial obligations, especially loan payments to creditors, it is in a state of financial distress. This situation can ultimately lead to bankruptcy if it is severe and prolonged.

As a market analyst, you are curious about the elements that can lead to a company’s financial difficulties. To conduct the investigation, you obtain the following data for the financial year 2022 from Capital IQ database for US companies in the S&P500 Index.

• Altman Z-score: This score, developed by Professor Edward Altman¹in 1968, measures a company's level of financial distress. It takes into account factors such as profitability, leverage, liquidity, and insolvency.
• Quickratio: The quick ratio is an indicator of a company’s short- term liquidity position and measures a company’s ability to meet its short-term obligations with its most liquid assets.
• Total Liabilities/ Total Assets %: the ratio of total liabilities to total assets (i,e.debt ratio). This ratio indicates the proportion of a company’s assets which is financed through debt.
• NetIncome: This figure represents a company's profitability by calculating its total revenue minus all expenses, including cost of goods sold, operating expenses, taxes, and
• ROA: Return on Assets (ROA) is a measure of a company's profitability relativeto its total It is calculated as net income divided by total assets.

Use the above data, you are required to perform a regression analysis to predict which factors can impact the level of firm financial distress (i.e. Altman Z-score) by answering the following questions

1. When it comes to forecasting a company’s financial distress, which variable(s) has (have) significant impact(s)?
2. Arethe errors of the regression independent?
3. Isthe regression model useful?