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Is your business worth investing in? For most of you, the answer is a definitive 'Yes.' But in the business world, talk is cheap. So if you want to attract investors, you'll need to be able to walk the talk, i.e., put your money where your mouth is.
There's no better way to do that than with a financial analysis report. After all, numbers don't lie. They're the smoking gun investors need before investing in your business.
Want to learn how to write a financial analysis report that attracts investors? This article covers six simple steps to follow. But first:
A financial analysis report shows the financial performance of your business over a specified period of time, usually on a quarterly or yearly basis. It's like a medical report but for your business's financial health.
In several countries, financial reporting is a requirement. The Securities and Exchange Commission requires companies to disseminate these digital reports to their shareholders in the United States. In addition, these financial reports are usually made available to the public if they're publicly-listed companies
A financial analysis report is invaluable to both you and your stakeholders. Let's discuss why you need it in the next section.
To make the right financial decisions for your business, you need data. This helps you lay a solid foundation for future performance and economic growth opportunities.
However, you need to be able to keep track of and make sense of all your financial data. That's where a financial analysis report comes in. It helps you organize, analyze, and paint a clearer picture of your business's cash flow and allows for seamless management of business expenses too.
Aside from those, here are a couple of more reasons why you need a financial analysis report:
A financial analysis report is easy on the eyes. It's a watered-down version of your finances that communicates essential data you need to make financial decisions.
You ensure the transparency your stakeholders want, too.
Generally, financial reports help you understand cash inflows and outflows . For example, if you know your affiliate sales and operating expenses, the cost of getting links to increase website traffic , social media marketing campaign expenditure, and the money coming in, you can make better financial decisions.
The information can help with debt ratios, budgeting, debt-to-asset financial ratio analysis, and calculating profit margins.
Suggested Reads: 10 Ways to Improve Your Business's Finance Position
Historical and real-time financial data help create financial models to predict future financial performance. These reports help you identify trends, patterns, and problems. As a result, you can plan for them early enough.
To create a financial analysis report, you must have all your data in a single document. It becomes easier for you to do your taxes, saves you time, and reduces the chances of making errors. Moreover, it's an official document that the Internal Revenue Service can use to calculate your taxes.
At the end of the day, the goal of a financial report is to provide insight into your organization's finances. Then, using both historical and current data, you can set SMART business goals to make better decisions for future performance.
Finally, it's essential to consider the ongoing nature of financial analysis and the need for periodic reviews. Implementing a project review process allows you to regularly assess the financial health of your business, identify any emerging trends or issues, and make informed adjustments to your financial strategies. This continuous evaluation ensures that your financial analysis remains up-to-date and relevant, providing you and your stakeholders with accurate insights into your business's performance.
Suggested Reads: 2022 Business Expense Categories Cheat Sheet: Top 15 Tax-Deductible Categories
Financial analysis makes it easy for you to identify the strengths and weaknesses of your business. Using that information will not only help your business grow but also thrive. What's more, doing financial analysis over specific periods helps you stay on top of your game by:
A periodic financial analysis includes a financial ratio analysis; specifically, a Liquidity Ratio called the Current Ratio Analysis. The Current Ratio is the sum of all your current assets divided by the sum of your current liabilities. It shows if you're liquid enough to meet your upcoming debts. So, if you aren't, you can adjust your financial strategy the soonest.
When you perform a periodic financial analysis, you can determine your company's profitability and make regular adjustments. A profitability ratio is a financial metric that can help you cut production costs and boost your bottom line.
You can use a profitability ratio (featured below) to determine your profit margin on sales, i.e., your gross profit margin. Here's the formula.
It's your sales revenue minus the total cost of goods sold (COGS) divided by revenue.
Another perk of doing financial analysis over a specific period is that it helps you better manage inventory . This way, you ensure it's always enough to meet projected sales. You do this using a financial management ratio called the Inventory Turnover Ratio.
Calculate the Turnover Ratio by dividing your total sale by your inventory.
The results of a periodic financial analysis yield your debt-to-equity ratio, too. It's a financial metric that shows how you've raised capital for your business. You want to check your stability and revenue growth every step of the way to determine whether your business is viable in the long run.
The debt-equity ratio is calculated by dividing your total liabilities by your shareholder's equity. It's usually included when you write a financial analysis report.
Generally speaking, the higher your debt-equity ratio, the higher the risk, and vice versa. Investors use this financial metric to check your company's stability and ability to raise money to grow.
Financial analysis over specific periods helps you identify opportunities to optimize operational efficiency for revenue growth. That is, regular annual reports help you spot patterns and trends. This allows you to nip problematic areas in the bud and prepare in advance.
For instance, you can adjust seasonal sales fluctuations, variable costs, etc.
Now that you understand a financial analysis report's 'what' and 'why,' it's time to look at the 'how.'
Here's how to write a financial analysis report:
The first section of your financial analysis report is the company overview. Here, you want to highlight the potential of your business. It's pretty much what you do in a business plan . Investors rely on your company overview to understand your competitive edge.
The question you want to answer here is - is your business worth the investment you're asking for? Think of the introductions in business plans or on Shark Tank to give you a better idea. As a general rule of thumb, you want to use plain language when writing your description.
You want to share, in brief, your history, business model, type of organization, description, etc. You can share what sector you're in as well as the size and scale of your business.
Featured below is an excellent example of a fictional company's overview.
Start by reviewing your quarterly or yearly financing activities, financial data, and statements. Then go through published business studies and industry-specific trade journals.
You should consider adding a snippet about how you compare to the industry average among your competitors. Like a business plan, you want to show potential investors why they should choose you. You can use Porter's Five Forces model to analyze your competition.
It pays to be as precise and comprehensive as possible when writing the main content. So, you’ll need to organize your data and, sometimes, make some calculations yourself. For instance, when writing your sales forecast , you need your sales data for the past three years before you organize it in financial reporting software or spreadsheets. Tally the data on a yearly, monthly (for the 1st year), and quarterly (for the last two years) basis.
You can write this part using a spreadsheet. But feel free to use financial reporting software if spreadsheets aren’t your cup of tea.
There are other sections you should create for your report’s main body.
Let’s look at them one by one:
With your sales forecast in place, it's time to figure out how much it'll cost. When setting up your expense budget , ensure it includes variable costs like your marketing budget and fixed costs like rent. In addition, you'll need to create an estimate for items like interest and taxes.
A cash flow statement summarizes all the money or its equal coming in (cash inflow) or leaving (cash outflow) a business. To create one, you need historical financial data or project it one year ahead if you're starting. Don't forget your cash flow statement is connected to your invoice.
Tally your net profit using your sales forecast, expense budget, and cash flow statement data. Your net profit margin is your gross margin less taxes, interest, and expenses. Try and be as precise as possible since this can stand in as your profit and loss (P&L) statement .
Your next step is to calculate your company's net worth. How? By managing your assets and liabilities, i.e., those items that don't appear in your P&L statement.
To do that, ballpark your monthly cash on hand. That is, equipment, inventory, land, and accounts receivable. Then sum up your liabilities, i.e., outstanding loan debts and accounts payable.
The last step in writing a company financial analysis report is calculating your break-even point. That's where your business expenses match your sales volume. Use the formula below to find your three-year sales forecast; this will help you find your break-even point.
Needless to say, if you're operating a profitable business model, then your company's revenue should be higher than your operating expenses. Again, this information helps reassure potential investors of your business' stability and revenue growth potential.
Refrain from assuming that people know the concepts you'll discuss in your report. Instead, define them in general terms first before you start talking about specifics.
The company valuation part is one of the most critical sections of your financial analysis report. Why? Because it helps potential investors see the value of investing in your company.
To determine your business' valuation is to find your company's value. You do this by analyzing your company data, including all the data you have discussed. There are three main ways to do it, i.e., using the following:
The goal here is to outline your current assets and liabilities. Moreover, the above techniques help you determine your business' stocks and current value. To do this, most accountants or financial officers use insights from and final average accounts of your balance sheet.
Risk analysis helps potential investors see your company's investment potential. That includes both current and future risks. You can start risk analysis by running a SWOT analysis .
But remember that your SWOT analysis is microscopic. So for the best results in your valuation, combine it with other techniques. For example, doing a PESTLE analysis . Here's a template you can use for that:
A PESTLE analysis gives you more details and offers two main benefits. First, it helps you understand your marketing environment and other macro factors that affect your company's financials.
When writing the financial analysis report of a company, you need to include a brief overview of your company's financial statements. To do this, summarize each component of the 3-statement model:
Let's discuss each of them:
Cash flow statement. Potential investors look at your cash flow statement summary for two reasons. One, it lets them see if you make enough money to settle your debts. Two, it helps them decide whether your company is worth investing in.
Income statement . A summary of this does two things. First, it shows you gaps in increasing operating profit by allowing you to boost sales revenue , reduce cost, or both. It's also an income statement showing how effective your strategies are at the start of your financial year.
Balance sheet. The balance sheet shows your debt coverage and asset liquidity in real time. The difference between assets and liabilities gives you the 'owner's equity.' Here's an example of a balance sheet:
Note that summarizing each of these three components doesn't mean just including tables in your report. Instead, explain what the data means in paragraph form, too.
The last section of the financial analysis report of a company is a summary. You want to share your final views about the company and your opinion on whether it's a profit or loss. That said, be sure to substantiate all your claims.
That means having evidence containing factual data, financial accounts, and proven financial theories. You can also include the outlook of the company. That is the type of organization, industry trends, economic growth strategies, and how they'll affect the company.
By now, you should understand the value of a company financial analysis report and how to write one. Not only does it show you the financial health status of a company, but it's also the smoking gun investors look for before investing in any business.
To any organization, a financial analysis report is a compass to optimize operational efficiency for growth. It is also a crucial part in portfolio management especially when you need to open your business up to other stakeholders.
Summarising, to write a financial analysis report, you need to:
Write your company overview , sales forecast, and other essential sections. Once those are out of the way, you can perform company valuation and risk analysis. Then, all that's left is to summarize what was discussed.
Daryl Bush is the Business Development Manager at Authority.Builders . The company helps businesses acquire more customers through improved online search rankings. He has extensive knowledge of SEO and business development.
Expense reconciliation: how does it work.
120+ Finance Research Topic Ideas To Fast-Track Your Project
If you’re just starting out exploring potential research topics for your finance-related dissertation, thesis or research project, you’ve come to the right place. In this post, we’ll help kickstart your research topic ideation process by providing a hearty list of finance-centric research topics and ideas.
PS – This is just the start…
We know it’s exciting to run through a list of research topics, but please keep in mind that this list is just a starting point . To develop a suitable education-related research topic, you’ll need to identify a clear and convincing research gap , and a viable plan of action to fill that gap.
If this sounds foreign to you, check out our free research topic webinar that explores how to find and refine a high-quality research topic, from scratch. Alternatively, if you’d like hands-on help, consider our 1-on-1 coaching service .
These research topic ideas explore a breadth of issues ranging from the examination of capital structure to the exploration of financial strategies in mergers and acquisitions.
The list below presents a series of research topics exploring the multifaceted dimensions of investment banking, with a particular focus on its evolution following the 2008 financial crisis.
These research topic ideas are centred on venture capital and private equity investments, with a focus on their impact on technological startups, emerging technologies, and broader economic ecosystems.
This list includes a range of research topic ideas focused on asset management, probing into the effectiveness of various strategies, the integration of technology, and the alignment with ethical principles among other key dimensions.
Here we explore research topics related to hedge fund operations and strategies, including their implications on corporate governance, financial market stability, and regulatory compliance among other critical facets.
This list explores various research topic ideas related to financial planning, focusing on the effects of financial literacy, the adoption of digital tools, taxation policies, and the role of financial advisors.
The following list delves into research topics within the insurance sector, touching on the technological transformations, regulatory shifts, and evolving consumer behaviours among other pivotal aspects.
These topic ideas span the development of asset pricing models, evaluation of machine learning algorithms, and the exploration of ethical implications among other pivotal areas.
The following topic ideas explore treasury management, focusing on modernisation through technological advancements, the impact on firm liquidity, and the intertwined relationship with corporate governance among other crucial areas.
The following research topic ideas explore the transformative potential of blockchain, the rise of open banking, and the burgeoning landscape of peer-to-peer lending among other focal areas.
These topic ideas span commercial banking, encompassing digital transformation, support for small and medium-sized enterprises (SMEs), and the evolving regulatory and competitive landscape among other key themes.
The folowing research topic ideas are centred around international finance and global economic dynamics, delving into aspects like exchange rate fluctuations, international financial regulations, and the role of international financial institutions among other pivotal areas.
These finance-related research topic ideas are starting points to guide your thinking. They are intentionally very broad and open-ended. By engaging with the currently literature in your field of interest, you’ll be able to narrow down your focus to a specific research gap .
When choosing a topic , you’ll need to take into account its originality, relevance, feasibility, and the resources you have at your disposal. Make sure to align your interest and expertise in the subject with your university program’s specific requirements. Always consult your academic advisor to ensure that your chosen topic not only meets the academic criteria but also provides a valuable contribution to the field.
If you need a helping hand, feel free to check out our private coaching service here.
thank you for suggest those topic, I want to ask you about the subjects related to the fintech, can i measure it and how?
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I am doing financial engineering. , can you please help me choose a dissertation topic?
I’m studying Banking and finance (MBA) please guide me on to choose a good research topic.
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China Finance Review International, forthcoming
30 Pages Posted: 10 Nov 2021
UNSW Australia Business School, School of Accounting
Date Written: October 28, 2021
The literature on financial statement analysis attempts to improve fundamental analysis and to identify market inefficiencies with respect to financial statement information. In this paper, I review the extant research on financial statement analysis. I then provide some preliminary evidence using Chinese data and offer suggestions for future research, with a focus on utilising unique features of the Chinese business environment as motivation.
Keywords: financial statement analysis, fundamental analysis, forecasting, persistence, mean reversion
JEL Classification: M40, M41
Suggested Citation: Suggested Citation
Unsw australia business school, school of accounting ( email ).
Sydney, NSW 2052 Australia
Paper statistics, related ejournals, financial accounting ejournal.
Subscribe to this fee journal for more curated articles on this topic
Asian Journal of Accounting Research
ISSN : 2459-9700
Article publication date: 3 September 2019
Issue publication date: 11 December 2019
The Chinese Telecoms Industry has been rapidly growing over the years since 2001. An analysis of financial performance of the three giants in this industry is very important. However, it is difficult to know how many ratios can be used best with little information loss. The paper aims to discuss this issue.
A total of 18 financial ratios were calculated based on the financial statements for three companies, namely, China Mobile, China Unicom and China Telecom for a period of 17 years. A principal component analysis was run to come up with variables with significance value above 0.5 from each component.
At the end, the authors conclude how financial performance can be analysed using 12 ratios instead of the costly analysis of too many ratios that may be complex to interpret. The results also showed that ratios are all related as they come from the same statements, hence, the authors can use a few to represent the rest with limited loss of information.
This study will help different stakeholders who are interested in the financial performance of each company by giving them a shorter way to analyse performance. It will also assist those who do financial reporting on picking the ratios which matter in reflecting the performance of their companies. The use of PCA gives unbiased ratios that are most significant in assessing performance.
Mbona, R.M. and Yusheng, K. (2019), "Financial statement analysis: Principal component analysis (PCA) approach case study on China telecoms industry", Asian Journal of Accounting Research , Vol. 4 No. 2, pp. 233-245. https://doi.org/10.1108/AJAR-05-2019-0037
Emerald Publishing Limited
Copyright © 2019, Reginald Masimba Mbona and Kong Yusheng
Published in Asian Journal of Accounting Research . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
The financial performance of a company is a primary concern for every stakeholder especially for investors, both aspiring and current ones. The measurement of the financial health of a company through the reported financial statements gives a qualitative analysis of the company’s position as well as an account of how the company has utilised its capital in production. According to Bhunia et al. (2011) , financial performance analysis involves using reported results in a company’s financial statements to obtain the quantitative performance characteristics of a company with the aim of determining how efficient the company has been in terms of the use of their resources according to the decisions made by the management.
Financial statement analysis using ratios has been one of the most commonly used primary models of assessing business performance. It is one of the primary models of assessment of a firm’s performance over years and as well as comparing it to the rest of the players in the industry. Due to limited time for those who do the analysis of financial statements and also given the fact that these ratios are mostly correlated, the number of ratios that are being evaluated has to be reduced so that focus is given to a few with minimum loss of data ( Taylor, 1986 ). Using principal component analysis (PCA), the study reduced the number of variables for any further regression analysis from 17 variables to 3 variables. Likewise, the number of ratios that are important have also been reduced with only significant ratios for each principal component now being used to analyse the performance of these companies as well as their industry. This study proves that the performance of a company can be analysed using just a few factors or by focusing on fewer ratios, which is cost effective with lesser time as well as obtaining more precise results that have least duplication of calculations.
Since 2002, China has been the largest telecom market by subscriber base and the industry has been attracting a lot of investment within and outside China ( Uria-Recio and O’Connor, 2004 ). The telecom industry in China has been the backbone of the economy that is highly dependent on the internet and online services ( Grubman, 2010 ). Their research, innovation and building of different technologies including the current 5G that they are jointly working on have given China high growth to make it compete with countries like the USA that are considered as earlier entrants into this market. Their internet and data services have facilitated access to online shopping, IPTV, online messaging and calling platforms, data cloud and many other services that are available at very fast speed and cheap rates. The rapid build-up of the industry’s infrastructure has been the main sign of the aggressive growth and development over the past two decades ( Lu, 2000 ).
The Chinese Telecom industry was heavily controlled by the government through the ownership and formation of policies on investment, areas of operations and tariffs charged. In late 2001, China successfully joined the World Trade Organization and this meant that it had to adjust some of its policies including regulations on players in its telecoms industry. Even though they opened the doors for foreigners, this industry remained monopolised by the three state-owned companies who have been competing for the highest market share, best financial performance and top innovation into new technologies including 5G network. Over the past years, they have cemented their dominance by taking over the other small players in the industry that were state owned as well. This study, thus, seeks to assess the financial performance of this industry since the doors for open competition were opened in this sector.
China Telecom is an incorporated company in the People’s Republic of China as China Telecom Corporation Limited with the aim of providing information services. These are, but not limited to wireline and telecommunication services, broadband and wireless internet access services, information services and other services that relate to information and telecommunications. According to the company’s report, there were at least 250m mobile subscribers, 134m broadband subscribers and 122m active access lines. The company is currently listed on the Hong Kong Stock Exchange and the New York Stock Exchange where they trade American Depositary Shares ( Telecom, 2019 ).
This is a company which is incorporated on Hong Kong and New York Stock Exchanges since 1997 with a constituent stock of Hang Seng Index in Hong Kong. Since its formation, China Mobile has grown to have the highest market share in the telecommunications globally with the highest number of subscribers, of which 887m are mobile subscribers while 113m of them are broadband subscribers. Mobile services in the form of mobile voice and data services are the main businesses of the company and other services include wireline broadband and other services in the telecommunications industry ( Mobile, 2019 ).
China Unicom, which was formed in 1994, is one of the oldest Telecoms Company in China and in the 2000s was listed on the Hong Kong and New York Stock Exchange. The company is the second largest mobile services provider in China with a subscriber base of 248m mobile subscribers, and 60m fixed line subscribers. Their service coverage includes all the telecommunications services and it has been doing exceptionally well in the mobile and fixed networks provision ( Unicom, 2019 ).
The rest of this paper is structured as follows: literature review, research objectives, methodology, discussion and analysis of results and finally the conclusion.
Financial analysis involves the use of quantitative information from financial statements, that is, income statement, balance sheet and statement of cash flows in order to come up with relationships of the items that are reported by the company according to the accounting standards for reporting. In doing this, the company is able to evaluate its decisions during a financial year or a given period and see its strengths, weaknesses and areas that need attention in the organisation ( Abraham, 2004 ; Bhargava, 2017 ; Schönbohm, 2013 ). Additionally, “they also provide clues on where the management might find more resources to boost its revenue” ( Mahajan and Yaday, 2016 ). In a case study on India’s telecommunications industry, Bhargava (2017) concludes that due to the increased contribution of the telecoms industry to different economies the financial health of the industry is important to the whole economy. Therefore, there is need for measurement of this constantly to monitor the economic performance of the whole industry. The telecoms industry is highly capital intensive and investors will be interested in knowing the “the financial condition and worthiness” of the industry which is achieved through financial analysis. However, even though it is beneficial it has to be noted that the ratios isolate the assessed factors from the rest of the report; hence, precaution has to be taken when interpreting them ( Abraham, 2004 ).
Even though ratios were seen as less significant due to the introduction of more sophisticated statistical analysis tools, authors still believe that they are still a useful tool in measuring performance. For example, a study which was done by Altman (1968) proved how ratios are still useful in prediction of bankruptcy using the case of manufacturing firms. Other studies on proving the importance and usefulness of ratios by Lewellen (2004) and Floros et al. (2009) found that investment ratios are useful in predicting market values of shares.
With this in mind, this study looks at internal determinants of performance as in the study by Allen et al. (2011) and another by Burja (2011) . These are factors within the control of management and can be able to influence them through their decisions. Through this, “the management can anticipate changes in the external environment and try to position the company to take advantage of anticipated developments” ( Burja, 2011 ). The external environment includes factors like demographic changes, GDP, inflation and other external environmental factors. However, besides the quantitative factors, management also have to analyse qualitative factors internally and externally even though these have no standard set to assess them as their measurement can be highly subjective.
A lot of other case studies have been done on financial performance analysis using ratios ( Eversull and Rotan, 1997 ; Collier et al. , 2010 ; Hossan and Habib, 2010 ; Grubman, 2010 ; Bhargava, 2017 ). For example Al-Jafari and Al Samman (2015) investigated the determinants of profitability for industrial firms in Oman. By utilising ordinary least squares (OLS) model on seven ratios, they drew up conclusions on the relationship between profitability ratios and other calculated non-profitability ratios. They found that there is a positive significant relationship between profitability, firm size, growth, fixed assets and working capital. Additionally, they also conclude that management efficiency on these large firms gives them better profit returns.
While Burja (2011) only focussed on the micro or internal environment in his regression analysis of financial performance, Allen et al. (2011) carried out an investigation on both internal and external environment to see how it impacts the profitability of the firm. This was a distinguished study as it included both internal and external factors in the regression analysis.
In a case study on the furniture industry, Traian-Ovidiu and Daniel-Teodor (2013 ) and Tsuji (2014) made a detailed analysis of a company’s statements to aid those who use them for investment decisions. Their studies focussed on bringing together financial ratios from financial statements and market data from stock markets to see how the indices on the market are influenced by the performance of different rations on the reported statements.
A study on the Indian public sector looked at how strategic industries with the government as major player performs financially ( Bhunia et al. , 2011 ). The case study looked at the ratios for India’s pharmaceutical industry financial reports. Using a number of statistical methods including standard deviation, mean and also regression analysis, they established the relationship between profit measure and other performance measures.
According to Buse et al. (2010 ) economic rate of return (ERR) is an important ratio in financial statement analysis because they considered it as an indicator of the economic performance of a company. In their study, they took ERR as a comprehensive ratio that looks at the organisation return and contribution with consideration of both internal and external factors affecting the business.
Kofi-Akrofi (2013 ) carried out a similar study but he, however, used multiple regression to look at the profitability of Telecommunications in Ghana for a period of four years. In his research, the main objective was to establish the relationship between the two main statements, hence, he treated them as independent from each other. A study by Oloko et al. (2014) looked at the telecoms industry but they focussed on how management style, cost of labour and competition impacts performance and profitability of Kenya’s Telkom.
While the literature reviewed covers a number of case studies on financial statements using ratios, some gaps exist. First, we have found that none has so far focussed on the Chinese telecoms especially the period after the Chinese Government opened its doors to the world to invest in their industries. Second, few research studies have used PCA to find out which ratios give best performance analysis with least loss of data from amongst the pool of all ratios. From the review of the past studies, we realized that different ratios were used and some are correlated because they are all from the same statements. A similar study was done by Taylor (1986) which focussed on the Australian firms. The study did not point to a specific industry; hence, with differences in industries the model might not be a one-size-fits-all especially given also the differences in the operational environment between China and Australia. Third, using PCA allows the use of at least 18 ratios reducing subjectivity effects on which ratios should be used for further analysis which include regression analysis on performance. Finally, as shown in our correlation matric we can see that all ratios are related which means that there is no independency to carry out the regression. This relationship comes from the fact that these ratios use data from the same statement. By applying PCA we create new independent variables that allow for effective further analysis with even lesser variables.
To carry out a PCA on 18 financial ratios for the Chinese Telecoms Industry to reduce the number of variables.
To analyse how the components are related to each other.
To recommend a combination or mix of ratios that best assess and analyse performance in the industry.
To examine the ratios with highest variation and assess their impact on the industry.
In previous studies on relationship analysis for financial statements and financial ratios, two models have mainly been used. The first one is the panel OLS regression model which has been applied by a number of accounting articles on financial performance and in most literature less than ten variables are used ( Al-Jafari and Al Samman, 2015 ; Jakob, 2017 ; Burja, 2011 ). The second model has been the multiple regression which was adopted by other researchers ( Bhunia et al. , 2011 ; Kofi-Akrofi, 2013 ; Buse et al. , 2010 ).
In this research, we use PCA which is a statistical tool that is used to reduce the variables that are used in data analysis with minimum loss of the original data ( Karamizadeh et al. , 2013 ). It has been used in a number of industries with one of the most common being in biometrics or “bioimaging” where physical features are used to identify a person with application on mobile phones, security systems. PCA has also been used for dimension reduction of large volumes of data and also in image compressing ( Arab et al. , 2018 ; Karamizadeh et al. , 2013 ; Polyak and Mikhail, 2017 ). The application of PCA in reducing variables as already noted in the literature review makes it a useful tool in modern days where large volumes of data are compiled and compared for its usefulness. In accounting field, PCA was used in a study by Taylor (1986) to reduce the number of ratios used in analysis of Australian companies since a lot of ratios are available, this makes the model very useful in helping investors and those who study ratios on knowing the most important ratios as it offers a way to reduce the numbers of ratios by statistically taking those that are most important with limited bias. The fact that PCA creates a new set of artificial variables which are independent makes it less complex to do regressions and come up with conclusions on related variables. In itself the PCA only reduces the variables that can be further used for regression analysis.
The first principal component combines the X -variables that have the maximum variance amongst all the combinations. Much of the variation in the data is taken by this first component. The second one likewise also takes the maximum remaining variation in the data with the condition that the correlation between the first and the second component is 0. This continues until the “ i th” component, which will account to the last variation that has not been accounted for by the other components with the condition still remaining that its correlation with the other components is 0. This condition is what creates the independence of the variable being used.
The principal component estimation uses eigenvectors as the coefficient to come up with the following basic equations: (1) Y 1 = e ˆ 11 Z X 1 + e ˆ 12 Z X 2 + e ˆ 13 Z X 3 + ⋯ + e ˆ 1 i Z X i , (2) Y 2 = e ˆ 21 Z X 1 + e ˆ 22 Z X 2 + e ˆ 23 Z X 3 + ⋯ + e ˆ 2 i Z X i , (3) Y i = e ˆ i 1 Z X 1 + e ˆ i 2 Z X 2 + e ˆ i 3 Z X 3 + ⋯ + e ˆ i i Z X i , where Y is the principal component; e ˆ the eigenvector; ZX the standardized value of the ratios used.
A total of 18 accounting ratios that are used in most literature in accounting and are deemed to be the most important measures of profitability, liquidity, management efficiency, leverage, valuation and growth, cash flow indicator and effective tax rate. This list, however, is not exhaustive; it has the ability to cover more ratios. Some of the ratios differ from the ones by Taylor (1986) because they are more relevant to the telecoms industry as used in previous studies. Second, in his study, Taylor used “debt coverage” due to missing data for interest cover but for this study we used interest cover as all relevant data were available ( Table I ).
The data used are from 2001 to 2017. This is the period that has financial statements available on the websites of the companies. Statistical Package for Social Sciences 20 was then used for the analysis of the financial statement with Microsoft Excel 13 used in the calculation of the final coefficients for each principal component. Standardized data were used instead of the original data as the ratios have different units of measurement. If the raw data are used, then a PCA will tend to give more emphasis to those variables that have higher variances than those variables that have lower variances meaning results will depend on the unit of measurement for each variable and since these data do not have that we used the standardized values.
All the financial data are secondary data taken from the company’s annual financial reports as presented on their websites and also from trusted journals and websites ( Table II ).
The matrix in Table III shows the relations within the ratios, which means we cannot have any ratio that is independent from the other, hence, we cannot use these ratios in regression as independent variables. This means we need to create new variables using PCA that will be independent from each other.
The financial statements of the three telecoms companies in China were used to assess the firms’ performance. Thus, PCA was adopted to suggest the most suitable ratios that can best explain the firms’ performance while ensuring minimum data loss among the pool of ratios. Using the data from the industry, which is described in Table II , we use standardized values of the ratios in the extraction of the principal component.
In this section, we first examined the components that have been extracted and the new independent variables according to our first objectives. Then second, we looked at the ratio mix that can be used for analysis of the telecoms industry performance.
Based on the extraction in Table IV , we only need four components to use as variables in the telecoms industry instead of the initial 18. These new variables are not only independent but are more easily comparable than the initial variables we had. The first principal component covers the highest variation in the data with an initial eigenvalue of 7.982, which represent 44.344 per cent of the variance. Three other components needed to, at least, get to 85 per cent of the variance, which is significant with least data being lost in the analysis. This contradicts with the initial conclusion that was made on Australian firms, who used similar ratios but got four components at 64.8 per cent Taylor (1986) . This variation is huge and is likely to be because of these data being focussed on one industry, hence, reducing the differences in valuation and reports of numerous firms. The increased percentage means there is lesser data loss from the four components and this allows for better analysis of the financial statements. From the PCA for the telecoms industry, we remain with four variables, Y1–Y4 whose calculation based on Equations (1) –( 3) ( Table V ).
Table VI shows us the mix of ratios that PCA extract to give significant analysis on the performance of the telecoms industry. The 12 ratios represent the mix that has important ratios from the classes that we have in general. The performance of the telecoms industry is measured mainly with four classes of ratios.
First, profitability of the company is very important as also concluded in research studies by Altman (1968) , Collier et al. (2010) and Mahajan and Yaday (2016) . In component 1, we see profitability measures having a very significant value of above 0.8. This is supported through most literatures that use the profitability of a firm as one of the primary indicators of its performance or as the dependent variable in most of the regression analysis, for example, return on assets ROA which was used by Kofi-Akrofi (2013 ) and Al-Jafari and Al Samman (2015) . Profit maximisation should be the main goal of management so as to give the high return expected by their shareholders and measured by ROSE. This is achieved by maintaining a high and constant profit margin throughout operations of the industry with a balance being kept between the profits and the expenditure of the firm especially in the salaries.
Second, liquidity in the industry is very important as proved by component 1. From the analysis, we established the importance of working capital assets as well as the importance of the operating cash to the firms which are also included in literature as significant measures as in the studies published by Bhunia et al. (2011) , Neves (2011) , Baños-Caballero et al. (2012) , Knauer and Wöhrmann (2013) . Operating cash has the highest value in component 1 which may signify its importance in the industry. The combination of the cash and the other current assets shows how performance in this industry is dependent on the liquid assets at the disposal of the firms. These resources are important for use in growth and expansion of operations. In analysing the individual companies it is interesting to see how failure to maintain high liquidity has led to the struggle of China Telecom and China Unicom to perform well and this supports what Singhania et al. (2014) noted the necessity of maintaining a balance between liquidity and profitability. In an analysis done on individual companies as the study built on the industry average, it was observed that China Telecom and China Unicom have been struggling to maintain favourable liquidity balances which has always left them as market followers behind China Mobile in terms of ability to generate profits, launch new services and upgrad to newer technologies including 4G network coverage.
Third, the management efficiency in the industry has also been argued by Al-Jafari and Al Samman (2015) in their study on firms in Omani. The decisions of management in allocation of their short-term resources are of importance and the relationship of this with the liquidity is that short-term decision of management in allocation of their non-fixed assets has impact on their performance. The use of the current ratios to measure their performance gets rid of the historical cost effect from the valuation of fixed assets, which makes it difficult to measure current performance. This factor supports the fact that we can measure the quality of management decisions through analysis of the financial results by relating their outcome to turnover. Even though in 2015 the Chinese Government introduced the tower company to take over network towers of the industry, DBS Vickers Securities (2015) noted that the effect of this on the performance of the company cannot be reflected. This is even though we cannot ignore it as this analysis put more emphasis on liquid resources of the company. Management also has to effectively allocate its expenses to the salaries and wages of its workers as this ratio is important in this service industry. There is need to always keep a favourable rate of return per worker for the industry which means that worker reward should always be related to what is being gained from the output of that worker. Whilst within the service industry there is no specific and accurate measure of the output, we can use the revenue paid to workers to see their relationship with the turnover. The higher this is, the better.
Of particular interest in our findings is the importance of customer growth and revenue per customer. As companies in the industry compete for customers, they still need to find the balance between customer growth and what they gain from it (revenue from the customer). With the government regulating the tariffs Zhiling (2002) and also as companies running different promotions to lure customers to their network, there is a need for management to keep that growth balancing with the revenue growth. In analysing the industrial data, we have noted that the revenue growth is not matching the customer growth and as a result this is very risky for the industry players that may be aiming for customers at the expense of high revenues as it will not be beneficial to its investors. This eventually can lead to a conflict between the government and other shareholders as the company tries to offer services to all at affordable rates with the public shareholder that will mainly be looking forward to high returns from the customer base.
In the financing section, only equity ratio is included in the components. The absence of the interest cover in measuring of performance is likely to prove that the model of financing is not of great importance when measuring the performance in the industry, which has very high capital requirements through investment in fixed assets. However, the allocation of capital is very important as also supported by the return of stockholder equity ratio. This means that management is expected to generate high returns for its shareholders in all their operations. The interests of the shareholders are further cemented by the EPS that needs to remain high and be maintained as the firms grow. The other stakeholders with fixed returns like the fixed tax, fixed interest always have their returns regardless of the performance yet the shareholders’ returns are based on how the firm has performed. Management has to keep a low volatility in their EPS and ROCE to maintain high investment and also attract more investors and partners.
Based on the results from the PCA analysis carried on 18 ratios over 17 years, profitability, liquidity, customer growth and management efficiency are the main performance highlighters for the industry. Maintaining all these will result in favourable returns to the shareholder of this industry. We cannot look at these factors in isolation as they are correlated and they are all combined when assessing the overall performance of the industry or individual firms. A combination of 12 ratios is able to give meaningful conclusion about the industry and can effectively analyse operations of the firms.
According to Jakob (2017) , state-owned enterprises are often claimed to be less profitable and less efficient compared to private corporations. A comparison can be carried out within an environment that has both private and public firms. In 2015, the Chinese Government introduced the tower company to take over network towers of the industry DBS Vickers Securities (2015 ). It will be important to see how this change is important and can benefit other governments and industry as well if they implement it.
List of accounting ratios used as variable
Ratio class | Ratio name | Notation | Formula |
---|---|---|---|
Profitability ratios | Return on assets | ROA | Net income/average assets |
Return on shareholder equity | ROSE | Net income/average stockholder equity | |
Profit margin | PM | Net income/revenue | |
Liquidity ratios | Current ratio | CR | Current assets/current liabilities |
Networking capital ratio | WCR | Current assets – current liabilities/total assets | |
Management efficiency ratios | Total assets turnover | TAT | Revenue/total assets |
Revenue per worker wage | R/W | Revenue/salary expense | |
Revenue per fixed asset | R/FA | Revenue/fixed assets | |
Working capital turnover | WCT | Current assets – current liabilities/revenue | |
Leverage ratios | Debt ratio | DR | Long term liabilities/total assets |
Equity ratio | ER | Shareholder’s equity/total assets | |
Debt equity ratio | DER | Total long term debts/shareholder’s capital | |
Times interest cover | TI | Income before interest and tax/interest expense | |
Valuation and growth | Earnings per share | EPS | Net profit/average number of shares |
Customers revenue | R/C | Revenue/number of subscribers | |
Customer growth | CG | Yearly change in customers/customer in base year | |
Cash flow indicator | Cash flow indicator | OC/S | Operating cash/sales |
Tax | Effective tax rate | ETxR | Tax/income before tax |
Descriptive statistics for telecoms industry
Minimum | Maximum | Mean | SD | Variance | ||
---|---|---|---|---|---|---|
ROA | 17 | 0.034 | 0.155 | 0.07047 | 0.028777 | 0.001 |
ROSE | 17 | 0.044 | 0.227 | 0.09906 | 0.044561 | 0.002 |
PM | 17 | 0.071 | 0.197 | 0.12612 | 0.038696 | 0.001 |
CR | 17 | 0.475 | 1.461 | 0.71694 | 0.300431 | 0.090 |
WCR | 17 | −0.255 | 0.044 | −0.14247 | 0.090237 | 0.008 |
TAT | 17 | 0.366 | 0.563 | 0.49141 | 0.044887 | 0.002 |
R/W | 17 | 7.060 | 14.586 | 11.23800 | 2.411187 | 5.814 |
R/FA | 17 | 0.438 | 0.725 | 0.62741 | 0.075328 | 0.006 |
WCT | 17 | −19.003 | 7.642 | −0.50535 | 6.929393 | 48.016 |
DR | 17 | 0.369 | 0.504 | 0.44800 | 0.039541 | 0.002 |
ER | 17 | 0.457 | 0.585 | 0.53306 | 0.038073 | 0.001 |
DER | 17 | 0.738 | 1.123 | 0.90176 | 0.128357 | 0.016 |
TI | 17 | 13.193 | 193.340 | 68.81465 | 58.139654 | 3,380.219 |
EPS | 17 | 0.655 | 2.353 | 1.68376 | 0.602397 | 0.363 |
R/C | 17 | 77.940 | 120.250 | 98.09888 | 14.579564 | 212.564 |
CG | 17 | 0.035 | 1.000 | 0.18359 | 0.234845 | 0.055 |
OC/S | 17 | 0.299 | 0.497 | 0.38606 | 0.063964 | 0.004 |
ETxR | 17 | 0.215 | 0.595 | 0.28076 | 0.085013 | 0.007 |
Valid (listwise) | 17 |
Inter-item correlation matrix for China telecoms Industry
ROA | ROSE | PM | CR | WCR | TAT | R/W | R/FA | WCT | DR | ER | DER | TI | EPS | R/C | CG | OC/S | ETxR | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ROA | 1.000 | 0.992 | 0.840 | 0.454 | 0.653 | −0.135 | 0.670 | −0.358 | 0.054 | −0.338 | 0.244 | −0.443 | −0.658 | −0.488 | −0.228 | 0.836 | 0.835 | 0.138 |
ROSE | 0.992 | 1.000 | 0.824 | 0.416 | 0.606 | −0.085 | 0.632 | −0.324 | 0.064 | −0.322 | 0.261 | −0.437 | −0.650 | −0.435 | −0.199 | 0.798 | 0.812 | 0.209 |
PM | 0.840 | 0.824 | 1.000 | 0.396 | 0.655 | −0.493 | 0.770 | −0.474 | −0.158 | −0.395 | 0.162 | −0.432 | −0.817 | −0.565 | −0.644 | 0.617 | 0.902 | 0.272 |
CR | 0.454 | 0.416 | 0.396 | 1.000 | 0.927 | −0.343 | 0.427 | 0.105 | 0.350 | −0.738 | −0.436 | −0.339 | −0.395 | −0.397 | −0.340 | 0.329 | 0.573 | 0.032 |
WCR | 0.653 | 0.606 | 0.655 | 0.927 | 1.000 | −0.462 | 0.640 | −0.142 | 0.235 | −0.726 | −0.269 | −0.437 | −0.604 | −0.591 | −0.494 | 0.520 | 0.797 | 0.040 |
TAT | −0.135 | −0.085 | −0.493 | −0.343 | −0.462 | 1.000 | −0.262 | 0.632 | 0.281 | 0.219 | 0.305 | 0.042 | 0.413 | 0.589 | 0.555 | −0.229 | −0.528 | −0.068 |
R/W | 0.670 | 0.632 | 0.770 | 0.427 | 0.640 | −0.262 | 1.000 | −0.324 | −0.127 | −0.217 | −0.156 | −0.089 | −0.762 | −0.654 | −0.635 | 0.536 | 0.766 | −0.013 |
R/FA | −0.358 | −0.324 | −0.474 | 0.105 | −0.142 | 0.632 | −0.324 | 1.000 | 0.509 | −0.388 | 0.080 | −0.275 | 0.373 | 0.752 | 0.083 | −0.657 | −0.470 | 0.150 |
WCT | 0.054 | 0.064 | −0.158 | 0.350 | 0.235 | 0.281 | −0.127 | 0.509 | 1.000 | −0.481 | 0.089 | −0.420 | 0.287 | 0.226 | 0.121 | −0.078 | −0.057 | 0.025 |
DR | −0.338 | −0.322 | −0.395 | −0.738 | −0.726 | 0.219 | −0.217 | −0.388 | −0.481 | 1.000 | −0.115 | 0.826 | 0.299 | −0.054 | 0.505 | 0.013 | −0.444 | −0.324 |
ER | 0.244 | 0.261 | 0.162 | −0.436 | −0.269 | 0.305 | −0.156 | 0.080 | 0.089 | −0.115 | 1.000 | −0.640 | 0.107 | 0.459 | 0.069 | 0.072 | −0.033 | 0.234 |
DER | −0.443 | −0.437 | −0.432 | −0.339 | −0.437 | 0.042 | −0.089 | −0.275 | −0.420 | 0.826 | −0.640 | 1.000 | 0.191 | −0.229 | 0.330 | −0.103 | −0.368 | −0.351 |
TI | −0.658 | −0.650 | −0.817 | −0.395 | −0.604 | 0.413 | −0.762 | 0.373 | 0.287 | 0.299 | 0.107 | 0.191 | 1.000 | 0.571 | 0.676 | −0.417 | −0.867 | −0.151 |
EPS | −0.488 | −0.435 | −0.565 | −0.397 | −0.591 | 0.589 | −0.654 | 0.752 | 0.226 | −0.054 | 0.459 | −0.229 | 0.571 | 1.000 | 0.279 | −0.687 | −0.691 | 0.290 |
R/C | −0.228 | −0.199 | −0.644 | −0.340 | −0.494 | 0.555 | −0.635 | 0.083 | 0.121 | 0.505 | 0.069 | 0.330 | 0.676 | 0.279 | 1.000 | 0.077 | −0.581 | −0.293 |
CG | 0.836 | 0.798 | 0.617 | 0.329 | 0.520 | −0.229 | 0.536 | −0.657 | −0.078 | 0.013 | 0.072 | −0.103 | −0.417 | −0.687 | 0.077 | 1.000 | 0.653 | −0.164 |
OC/S | 0.835 | 0.812 | 0.902 | 0.573 | 0.797 | −0.528 | 0.766 | −0.470 | −0.057 | −0.444 | −0.033 | −0.368 | −0.867 | −0.691 | −0.581 | 0.653 | 1.000 | 0.120 |
ETxR | 0.138 | 0.209 | 0.272 | 0.032 | 0.040 | −0.068 | −0.013 | 0.150 | 0.025 | −0.324 | 0.234 | −0.351 | −0.151 | 0.290 | −0.293 | −0.164 | 0.120 | 1.000 |
Total variance explained
Initial eigenvalues | Extraction sums of squared loadings | |||||
---|---|---|---|---|---|---|
Component | Total | % of variance | Cumulative % | Total | % of variance | Cumulative % |
1 | 7.982 | 44.344 | 44.344 | 7.982 | 44.344 | 44.344 |
2 | 3.430 | 19.056 | 63.400 | 3.430 | 19.056 | 63.400 |
3 | 2.217 | 12.315 | 75.715 | 2.217 | 12.315 | 75.715 |
4 | 1.779 | 9.883 | 85.598 | 1.779 | 9.883 | 85.598 |
5 | 0.967 | 5.370 | 90.968 | |||
6 | 0.719 | 3.997 | 94.965 | |||
7 | 0.432 | 2.401 | 97.365 | |||
8 | 0.234 | 1.298 | 98.663 | |||
9 | 0.108 | 0.602 | 99.266 | |||
10 | 0.059 | 0.327 | 99.592 | |||
11 | 0.038 | 0.212 | 99.805 | |||
12 | 0.016 | 0.088 | 99.893 | |||
13 | 0.012 | 0.067 | 99.960 | |||
14 | 0.005 | 0.028 | 99.988 | |||
15 | 0.001 | 0.008 | 99.996 | |||
16 | 0.001 | 0.004 | 100.000 | |||
17 | 1.001E-016 | 5.560E-016 | 100.000 | |||
18 | −1.876E-016 | −1.042E-015 | 100.000 |
Component | ||||
---|---|---|---|---|
1 | 2 | 3 | 4 | |
-score: ROA | 0.091 | 0.428 | 0.216 | |
-score: ROSE | 0.118 | 0.464 | 0.192 | |
-score: PM | 0.011 | 0.199 | −0.240 | |
-score: CR | 0.320 | −0.530 | 0.374 | |
-score: WCR | 0.224 | −0.352 | 0.252 | |
-score: TAT | −0.528 | 0.308 | 0.408 | 0.355 |
-score: R/W | −0.154 | −0.042 | −0.032 | |
-score: R/FA | −0.456 | 0.751 | −0.222 | 0.101 |
-score: WCT | −0.041 | −0.129 | ||
Z-score: DR | −0.488 | −0.786 | 0.310 | 0.014 |
-score: ER | −0.052 | 0.434 | −0.232 | |
-score: DER | −0.391 | −0.809 | −0.227 | 0.103 |
-score: TI | −0.836 | 0.115 | 0.029 | 0.279 |
-score: EPS | −0.705 | 0.188 | −0.200 | |
-score: R/C | −0.594 | −0.159 | 0.366 | |
-score: CG | −0.309 | 0.409 | 0.433 | |
-score: OC/S | −0.026 | 0.023 | −0.039 | |
-score: ETxR | 0.134 | 0.436 | 0.131 | −0.538 |
Ratio name | Notation | Ratio name | Notation |
---|---|---|---|
Return on assets | ROA | Working capital turnover | WCT |
Return on shareholder equity | ROSE | Equity ratio | ER |
Profit margin | PM | Earnings per share | EPS |
Current ratio | CR | Customers revenue | R/C |
Networking capital ratio | WCR | Customer growth | CG |
Revenue per worker wage | R/W | Cash flow indicator | OC/S |
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Finance Dissertation Made Easier!
Embarking on your dissertation adventure? Look no further! Choosing the right finance dissertation topics is like laying the foundation for your research journey in finance, and we're here to light up your path. In this article, we will be diving deep into why dissertation topics in finance matter so much. We've got some golden writing tips to share with you! We're also unveiling the secret recipe for structuring a stellar finance dissertation and exploring intriguing topics across various finance sub-fields. Our buffet of finance dissertation topics will surely set your research spirit on fire!
Finance dissertations are academic papers that delve into specific finance topics chosen by students, covering areas such as stock markets, banking, risk management, and healthcare finance. These dissertations require extensive research to create a compelling report and contribute to the student's confidence and satisfaction in the field of finance. Now, let's understand why these dissertations are so important and why choosing the right finance dissertation topics is crucial!
Choosing the dissertation topics for finance students is essential as it will influence the course of your research. It determines the direction and scope of your study. You must make sure that the finance dissertation topics you choose are relevant to your field of interest. Here are a few reasons why finance thesis topics are important:
Opting for relevant finance thesis topics ensures that your research contributes to the existing body of knowledge and addresses contemporary issues in finance. Choosing a dissertation topic relevant to the industry can make a meaningful impact and advance understanding in your chosen area.
Selecting finance dissertation topics that align with your interests and career goals is vital. When genuinely passionate about your research area, you are more likely to stay motivated during the dissertation process. Your interest will drive you to explore the subject thoroughly and produce high-quality work.
Well-chosen finance dissertation topics can open doors to various future opportunities. They can enhance your employability by showcasing your expertise in a specific finance area. They may also lead to potential research collaborations and invitations to conferences in your field of interest.
Your choice of topics for dissertation in finance also influences the availability of academic supervisors with expertise in your chosen area. Selecting a well-defined research area increases the likelihood of finding a supervisor to guide you effectively throughout the dissertation. Their knowledge and guidance will greatly contribute to the success of your research.
Writing a dissertation requires a lot of planning, formatting, and structuring. It starts with deciding on topics for a dissertation in finance, conducting tons of research, deciding on methods, and so on. Below are some tips to assist you along the way, and here is a blog on the 10 tips on writing a dissertation that can give you more information, should you need it!
It is important to choose finance research topics within the given timeframe and resources. Select a research area that interests you and aligns with your career goals. This will help you stay inspired throughout the dissertation process.
A comprehensive literature review forms the backbone of your research. After choosing the finance dissertation topics, dive deep into academic papers, books, and industry reports. Gain a solid understanding of your chosen area to identify research gaps and establish the significance of your study.
Clearly define your dissertation's research questions and objectives. It will provide a clear direction for your research and guide your data collection, analysis, and overall structure. Ensure your objectives are specific, measurable, achievable, relevant, and time-bound (SMART).
Depending on your research methodology and your finance dissertation topics, collect and analyse relevant data to support your findings. It may involve conducting surveys, interviews, experiments, and analysing existing datasets. Choose appropriate statistical techniques and qualitative methods to derive meaningful insights from your data.
Pay attention to the structure and organisation of your dissertation. Follow a logical progression of chapters and sections, ensuring that each chapter contributes to the overall coherence of your study. Use headings, subheadings, and clear signposts to guide the reader through your work.
Once you have completed the writing process, take the time to proofread and edit your dissertation carefully. Check for clarity, coherence, and proper grammar. Ensure that your arguments are well-supported, and eliminate any inconsistencies or repetitions. Pay attention to formatting, citation styles, and consistency in referencing throughout your dissertation.
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Now that you know what a finance dissertation is and why they are important, it's time to have a look at some of the best finance dissertation topics. For your convenience, we have segregated these topics into categories, including cryptocurrency, risk management, internet banking, and so many more. So, let's dive right in and explore the best finance dissertation topics:
1. The Impact of Regulatory Frameworks on the Volatility and Liquidity of Cryptocurrencies.
2. Exploring the Factors Influencing Cryptocurrency Adoption: A Comparative Study.
3. Assessing the Efficiency and Market Integration of Cryptocurrency Exchanges.
4. An Analysis of the Relationship between Cryptocurrency Prices and Macroeconomic Factors.
5. The Role of Initial Coin Offerings (ICOs) in Financing Startups: Opportunities and Challenges.
1. The Effectiveness of Different Risk Management Strategies in Mitigating Financial Risks in Banking Institutions.
2. The Role of Derivatives in Hedging Financial Risks: A Comparative Study.
3. Analysing the Impact of Risk Management Practices on Firm Performance: A Case Study of a Specific Industry.
4. The Use of Stress Testing in Evaluating Systemic Risk: Lessons from the Global Financial Crisis.
5. Assessing the Relationship between Corporate Governance and Risk Management in Financial Institutions.
1. Customer Adoption of Internet Banking: An Empirical Study on Factors Influencing Usage.
Enhancing Security in Internet Banking: Exploring Biometric Authentication Technologies.
2. The Impact of Mobile Banking Applications on Customer Engagement and Satisfaction.
3. Evaluating the Efficiency and Effectiveness of Internet Banking Services in Emerging Markets.
4. The Role of Social Media in Shaping Customer Perception and Adoption of Internet Banking.
5. Fraud and Identity Theft are Accomplished via Internet Banking.
1. The Impact of Microfinance on Poverty Alleviation: A Comparative Study of Different Models.
2. Exploring the Role of Microfinance in Empowering Women Entrepreneurs.
3. Assessing the Financial Sustainability of Microfinance Institutions in Developing Countries.
4. The Effectiveness of Microfinance in Promoting Rural Development: Evidence from a Specific Region.
5. Analysing the Relationship between Microfinance and Entrepreneurial Success: A Longitudinal Study.
1. The Impact of Digital Transformation on Retail and Commercial Banking: A Case Study of a Specific Bank.
2. Customer Satisfaction and Loyalty in Retail Banking: An Analysis of Service Quality Dimensions.
3. Analysing the Relationship between Bank Branch Expansion and Financial Performance.
4. The Role of Fintech Startups in Disrupting Retail and Commercial Banking: Opportunities and Challenges.
5. Assessing the Impact of Mergers and Acquisitions on the Performance of Retail and Commercial Banks.
1. The Performance and Risk Characteristics of Hedge Funds: A Comparative Analysis.
2. Exploring the Role of Private Equity in Financing and Growing Small and Medium-Sized Enterprises.
3. Analysing the Relationship between Real Estate Investments and Portfolio Diversification.
4. The Potential of Impact Investing: Evaluating the Social and Financial Returns.
5. Assessing the Risk-Return Tradeoff in Cryptocurrency Investments: A Comparative Study.
1. The Impact of Exchange Rate Volatility on International Trade: A Case Study of a Specific Industry.
2. Analysing the Effectiveness of Capital Controls in Managing Financial Crises: Comparative Study of Different Countries.
3. The Role of International Financial Institutions in Promoting Economic Development in Developing Countries.
4. Evaluating the Implications of Trade Wars on Global Financial Markets.
5. Assessing the Role of Central Banks in Managing Financial Stability in a Globalised Economy.
1. The Impact of Sustainable Investing on Financial Performance.
2. The Role of Green Bonds in Financing Climate Change Mitigation and Adaptation.
3. The Development of Carbon Markets.
4. The Use of Environmental, Social, and Governance (ESG) Factors in Investment Decision-Making.
5. The Challenges and Opportunities of Sustainable Finance in Emerging Markets.
1. The Valuation of Distressed Assets.
2. The Pricing of Derivatives.
3. The Risk Management of Financial Institutions.
4. The Regulation of Investment Banks.
5. The Impact of Technology on the Investment Banking Industry.
1. The Development of New Actuarial Models for Pricing Insurance Products.
2. The Use of Big Data in Actuarial Analysis.
3. The Impact of Climate Change on Insurance Risk.
4. The Design of Pension Plans That Are Sustainable in the Long Term.
5. The Use of Actuarial Science to Manage Risk in Other Industries, Such as Healthcare and Finance.
1. Study the Relations Between Corporate Governance Structures and Financial Performance
2. Testing the Effects of Capital Structure on Firm Performance Across Different Industries
3. Effectiveness of Financial Management Practices in Emerging Markets
4. Integrating Sustainability and CSR Initiatives Impacts a Corporation’s Financial Performance and Enhances its Brand Reputation.
5. A Comparative Study of the Financing Strategies Employed in Mergers and Acquisitions.
Embarking on a dissertation report on finance topics journey requires careful consideration of various factors. Your choice of topic in finance research topics is pivotal, as it sets the stage for the entire research process. We suggest the following tips that can help you pick the perfect dissertation topic:
1. Identify your interests and strengths
2. Check for current relevance
3. Feedback from your superiors
4. Finalise the research methods
5. Gather the data
6. Work on the outline of your dissertation
7. Make a draft and proofread it
Lastly, we have discussed the importance of finance thesis topics and provided valuable writing tips and tips for finding the right topic. We have also presented a list of thesis topics for finance students within various subfields. With this, we hope you have great ideas for finance dissertations. Good luck with your finance research journey!
How do i choose a dissertation topic in finance, what is the best topic for a thesis in finance, where can i find a dissertation topic in finance, what is the recommended length for a finance dissertation, how do you write a dissertation in finance.
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Within an increasingly volatile world, The Greenbrier Companies, Inc. ( NYSE: GBX ), as part of the global rail industry is well-placed to take advantage of efforts to bring local or regional stability. Rail transport has become an increasingly important capacity to have, as shipping lanes are closed or threatened, or pipelines are attacked or impeded from delivering oil across borders. Within the context of what is arguably an increasingly energy-poor world, rail transport also helps to address the need to cut down on energy use in transport, as well as helping to cut emissions. Greenbrier's financial results have been decent and steady in the past few years. The outlook is promising for the longer term due to favorable external factors. I am looking to buy sizable dips in this stock.
As I pointed out in an article in the Spring, when Greenbrier's stock was trading in the low $50s/share, I was ready to take profits. In other words, I had it as a hold, but I was leaning toward selling. I ended up selling my entire position, as I saw the risk/reward potential at that price level as being unfavorable. Now that its share price moved into the mid $40s/share range, I still have it as a hold, but now I am looking at a favorable entry point, in other words, I am a hold for now, but I am leaning toward starting to buy in response to a favorable buying opportunity. As I shall explain in the article, this change has less to do with Greenbrier's performance, but rather with external factors.
For the last quarter ending in May, Greenbrier reported a revenue decline of almost 5% from $862.7 million to $820.2 million. Revenues are set to drop for the fiscal year compared with 2023, based on the company's outlook.
Net earnings increased by about 1% to $33.9 million for the quarter compared with the same period. The profit margin is rather thin at about 4% of revenues, which I highlighted in the past about this company. It means that there is very little room to work with, in terms of discounting to stave off competition, or to keep sales going during hard economic times. Deliveries declined for the period from 5,600 carts to 5,400. The order backlog grew just slightly by about 2%, to 29,400 units.
Its debt situation is overall steady. Interest on debt was similar to the previous quarter, coming in at $24.7 million. That is about 3% of total revenue. I worry when interest costs steadily remain above 5% of revenues for most companies. Its total debt, including leasing non-recourse debt, is $1.76 billion. That is a bit high for my liking, but its non-leasing-related debt is $835 million. That is equal to about a quarter's worth of revenues.
Within the context of higher interest rates that have persisted since the post-COVID recovery, looking at a company's overall debt situation is now more important than it has been during the low interest rate era of 2008-2021. Greenbrier seems to be managing the debt and interest cost situation competently, keeping it sustainable.
With global trade frictions, geopolitical big power competition, conflicts, and political trends, such as the green movement that is helping to shift the way we approach just about all economic activities, the need for new adaptations arises. Perhaps the least talked about factor that calls for serious adaptation to changes is what I have been heralding lately as the most important economic factor to watch, which is the growing evidence that suggests we may be entering an era of global scarcity, especially when it comes to crude oil. All these major factors of change seem to be aligning in favor of a bullish long-term thesis for the rail transport industry.
While it is not universal worldwide, in terms of policies and effort level, there is a broad push to reduce emissions from our economic activities in most major economies worldwide. Some economies, such as the EU already achieved significant reductions and are looking to keep the progress going. Replacing truck freight with rail transport can reduce emissions per ton of goods transported by about eight-fold by some estimates .
Somewhat related, is the much less talked about effort to reduce transport fuel consumption, due to impending shortages. A little-known fact about the global state of the crude oil supply situation is that we reached a monthly peak in production in the fall of 2018 at 84.6 mb/d. As of March of this year, the world was producing 82.5 mb/d based on the EIA's global data . A significant factor that contributed to the peak in global crude oil production for the period was played by the OPEC + efforts to reduce supply, which totals an amount of 5.9 mb/d.
It should be noted that there is no guarantee that OPEC + could add 5.9 mb/d in production if called upon at the moment. We just assume that they have the capacity to do so, even though several members are producing most of their oil from very old fields that are prone to depletion-related declines. My take is that behind those official cuts, there are very real declines in production capacity hiding from public view. Notably, Saudi Arabia claims to have the capacity to produce 12.5 mb/d, while so far this century, it never proved capable of producing more than 10.5 mb/d on a sustained basis. Even those periods of production that surpassed 10 mb/d were somewhat brief.
Federal Reserve Bank of St. Louis
If my thesis is correct and there is a severe scarcity issue on the horizon, then making the global economy less dependent on truck transport for hauling goods is a good long-term adaptation, that can shield economies around the world from price spikes and outright shortages. Investing in rail transport is therefore a logical policy at the government level, as well as in terms of private enterprise investment.
There is no clear point in time that we can pinpoint as the beginning of the halting and then reversing of the globalization of the economy, and it was not a single-factor pivot. In my view, it happened last decade, with the start of the conflict in Ukraine in 2013-2014, then the US-China trade frictions that started under the Trump administration's trade & tariff policies. The COVID crisis reinforced the global perception that an over-dependence on the global supply chain is a vulnerability.
This decade we saw an acceleration in the process of the world cutting old economic and transport ties. The Ukraine war went into full conflict mode in 2022, and so did the Russia-Western World economic confrontation. Transport in the Black Sea has been disrupted, the Nord Stream pipelines transporting natural gas from Russia to Germany were blown up, and Ukraine recently partially halted pipeline transport from Russia to EU countries through its territory. The conflict in the ME region, starting with the Hamas attack on Israel last fall is also causing global supply disruptions indirectly, as the Yemen Houthi militia is attacking shipping through the Red Sea . The tech war with China on the one hand and the US & the EU on the other is also intensifying, leading to other economic ties being cut.
Since global transport & trade are increasingly coming under disruptive pressure, due to various factors converging toward the same outcome, it is logical to conclude that many of those old supply flows are set to be replaced by new regional or national ones. This is a potential long-term benefit for the rail transport industry.
Perhaps the most obvious example of how the current global economic and geopolitical situation is creating higher demand for rail transport is the example of Ukraine's need to shift its transport of exports from its Black Sea ports to land-based transport due to full-blown hostilities breaking out with Russia. Russia either conquered or blockaded some ports, giving rise to a need to transport Ukraine's grains and other exports and many imports by rail. Neighboring countries such as Hungary & Romania had to invest in extra capacities or revive old rail transport capacities to meet the new demand.
Greenbrier is well-positioned to take advantage of this particular, geopolitically triggered opportunity. It has production, refurbishment, and repair facilities for railcars in Romania & Poland . The magnitude of demand that is set to materialize for the long term in the region as a result of ongoing events is unclear, given that the war is ongoing and the shape of an eventual peace is yet to be revealed, but there is significant demand growth already happening, as evidenced by investments that are already being made in the region in expanding rail transport capacities.
The EU is a growing market for companies involved in the rail transport industry, not only due to geopolitical events but also because of other considerations, such as the goals for emissions cuts, as well as the fact that the EU does not have very significant petroleum reserves and production. Therefore, it is reliant on imports, which is an extra stimulant toward more efficiency in freight as well as public transport.
As we can see, the EU has seen steady and significant growth in rail transport over the past decade. It is a different picture from what we are seeing in the US.
US rail freight transport volume (Statista)
The difference in the past performance of rail transport in the EU versus the US comes down mostly to environmental policies, which in my view are reinforced by a long-term policy of fostering efficiency due to resource scarcities, as well as geopolitical trends, such as the conflict with Russia. We may see a similar trend develop in the US as in Europe, as the reshoring of manufacturing activities and other trends can give rise to higher internal transport needs to facilitate the resulting expansion in the domestic supply chains.
A european economic implosion remains the greatest potential risk for greenbrier.
Greenbrier stock price and other metrics (Seeking Alpha)
With a forward P/E of just under 11, Greenbrier's valuation seems cheap within the context of the broader market, where the S&P 500 is currently trading at around 28. Compared with most industrial peers, it is trading at a much more modest discount. Bombardier Inc. ( OTCQX:BDRBF ) for instance, also produces some of the same products, and it is currently trading at a forward P/E ratio of just under 15.
The one great risk factor, aside from the fact that Bombardier has a more diverse product profile, that perhaps justifies a lower P/E ratio for Greenbrier, remains its deep reliance on the European market for both production and sales. The long-term outlook for Europe's economy remains bleak in my view. The green agenda continues to be a drag on its industrial capacity, and the economic divorce from Russia leaves it vulnerable to energy scarcity shocks. It is also falling behind technologically compared with major peers such as the US, China, and others around the world.
The combined effect of all the negative factors amounts to a risk of the EU going into an economic tailspin at some point. It might perhaps be triggered by an energy price shock or by another eurozone crisis. Regardless, when the next crisis comes, it will be met by an already weakening EU economy, which for the first half of this decade hardly managed to produce any economic growth . A European economic crisis could translate into a crisis for Greenbrier as well, in my opinion. Its sales and perhaps its production facilities can potentially plunge.
Keeping in mind the risks, as well as the potential long-term external trends that are beneficial for the rail transport industry, thus for Greenbrier, I see as a hold between $40-$50/share. If it declines along with the broader market under $40/share, I see it as a buying opportunity, assuming that the overall positive external thesis remains intact. It came close to going under $40/share this summer on two different occasions, but it held above that price. Given the broader market volatility we saw in the past few months, I believe that there is a good chance that the buying opportunity I am looking for will occur. At that point, I intend to buy incrementally on the way down. Its solid financial performance combined with favorable external market factors makes it a good candidate to buy its stock at a bargain price, and then wait for a recovery to occur.
Editor's Note: This article discusses one or more securities that do not trade on a major U.S. exchange. Please be aware of the risks associated with these stocks.
This article was written by
Analyst’s Disclosure: I/we have no stock, option or similar derivative position in any of the companies mentioned, and no plans to initiate any such positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.
Seeking Alpha's Disclosure: Past performance is no guarantee of future results. No recommendation or advice is being given as to whether any investment is suitable for a particular investor. Any views or opinions expressed above may not reflect those of Seeking Alpha as a whole. Seeking Alpha is not a licensed securities dealer, broker or US investment adviser or investment bank. Our analysts are third party authors that include both professional investors and individual investors who may not be licensed or certified by any institute or regulatory body.
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Master in International Financial Analysis. Level: Master. Application period: 2023-10-16 - 2024-05-02. Start date: Autumn 2024. City: Jönköping. Degree: Degree of Master of Science (60 credits) with a major in Business Administration, 60 credits. JIBS is double accredited by EQUIS and AACSB .
Opting for relevant finance thesis topics ensures that your research contributes to the existing body of knowledge and addresses contemporary issues in finance. Choosing a dissertation topic relevant to the industry can make a meaningful impact and advance understanding in your chosen area. 2. Personal Interest.
Greenbrier's solid and steady financial results in the past few years are due, in part, to beneficial external trends. Click here to read an analysis of GBX stock now.