# Analysis of Corporate Leverage in Four Countries

For the project your group will conduct analysis of the leverage ratios of companies from the following four countries: Australia, China, Japan and the U.K.

Relevant financial data will be available on Moodle in one excel file. You will have to download the data, upload to your Jupyter notebook and then conduct your analysis using Pandas. Your group will have to submit the Jupyter notebook you used to do the analysis for this project.

You will have to write up your analysis in a report of up to 3,000 words. Your report should also include tables and graphs from your analysis. These tables and graphs have to be produced using Python and you will have submit all the relevant codes in a Jupyter notebook.

The project should be completed in teams of 3 or 4 students.

The objectives of your analysis are as follows:

• Document and discuss the distribution and trends in leverage ratios over time in each country o Use multiple measures of leverage (e.g., total leverage, short-term and long-term leverage and coverage ratio) and discuss if you get similar or different results from different measures.
• You will look at statistics such as mean, median, 25 percentile and 75 percentile to compare leverage across countries.
• You will conduct the analysis for Australia, China, Japan and the U.K. and you will discuss how the leverage ratios of the different countries compare with each other and if they show similar or different trends over time.
• You will document the distribution of leverage in each country in 2007 and 2017 to see if the distribution has changed over time. You can use histograms, kernel density plots and percentile plots to show the distributions.

• Analyse the determinants of leverage in each country. So you will have four sets of results.
• Initially, explore the relations between various firm characteristics (such as firm size, profitability, growth opportunity etc.) and leverage using scatter plot.
• You will then conduct correlation analysis to determine if there are significant correlations between these characteristics and leverage.
• Then use simple linear regressions to quantify the relation between leverage and these characteristics one at a time. Here you will use regressions with one independent variable (see lecture 7).
• Finally you will use multiple linear regression analysis to consider the effects of all the different firm characteristics on leverage.
• You will compare and contrast the results you get from the above analysis for four countries in your sample: Australia, China, Japan and the U.K.

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TFIN605 Data Analytics in Finance                                                                                                                                                                Spring 2020

I have posted three papers on Moodle for you to read for this assignment.

You should read Rajan and Zingales (1995) to get background on the determinants of leverage ratio. They also have plot of percentile distribution of leverage that you can try to replicate for your sample.

The paper on East Asian leverage includes analysis that you can try to replicate in your report for the four countries in your sample. Pages 37-41 are especially relevant. The paper is also available here:

The La Cava and Windsor (2016) paper looks at cash to asset ratio, so it is not directly relevant for your analysis. But you can look at the types of analysis and plots and graphs they have used and use similar analysis for leverage ratios in your report.

You should also do additional research via google on the determinants of leverage and use those sources as references in your report.

The report will:

1. Summarise the relevant literature (research papers) and research question.
2. Perform descriptive data analysis and data visualisation.
3. Draw inference and conclusion and relate the findings to existing research.

Marking Criteria

The following criteria will be used to assess the assignment:

1. Quality of literature review and ability to clearly state the relevant research questions and hypotheses.
2. Effectiveness in applying the relevant conceptual framework from weeks 1 through 7 in analysing a financial issue.
3. Quality of analyses and soundness of arguments.
4. Accuracy of programming codes.
5. Clarity of writing and quality of presentation.