Today we will take a brief look into the most commonly used types of Financial Analysis. We will see some examples but will not go into detail for each method. This article aims to show you the vast techniques you can apply when doing financial analytics. Hopefully, after reading it, you will be better equipped to pick the right methods to use in specific situations. In future articles, we will dig deeper into all the techniques and their application and interpretation.
Keep in mind that this is by far, not an extensive list. These are just some of the methods we believe are most common when analyzing financial data.
We will take a look at the following types of financial analysis:
- Vertical Analysis;
- Horizontal Analysis;
- Ratio Analysis;
- Scenario & Sensitivity Analysis;
- Variance Analysis;
Vertical analysis, or also known as Common Size analysis, is a technique in which we list line items as a percentage of the same base figure within the statement we are analyzing. This method is especially helpful when we compare the performance of companies with different sizes, as it shows us relative proportions of accounts. It can also be applied in series analysis when we compare prior periods or periods of varying lengths, like quarter-to-year comparisons.
Let’s make Vertical Analysis easier to understand with an example. Let’s say company ACME has Selling expenses of 250,000 thousand Euro in 2X19. We are comparing ACME to a much bigger competitor to see how the business is doing. The competitor, Umbrella Corp., has 14,000,000 thousand Euro Selling expenses in 2X19. Comparing the two figures is pointless and will not tell us much. However, if we apply Vertical analysis, we can get the following:
|Selling expenses as % of Sales||20.83%||23.03%|
Once we present the Selling expenses as a percentage of Sales, they become more comparable. Now we can see that the relative portion of costs for realizing sales is higher in Umbrella Corp. We do not have any further information, but so far, it seems like ACME is better at managing their sales related expenses.
We now know how to perform Vertical analysis. We use Sales as a base figure when analyzing Income Statements, while for Balance sheets, Total Assets, and Total Liabilities are used (keep in mind those numbers are the same).
Horizontal analysis, or Trend analysis, is a financial statement analysis method that shows us changes in the amounts of corresponding line items over time. In Horizontal analysis, we can compare two or more periods of the same company, to identify and analyze trends and support future forecasts. We can either apply this method to absolute values or compare the percentage off a base period. Comparing off a base period means we use the first period in the series as a baseline (100%) and present the amounts of all subsequent periods as percentages off the baseline.
Let’s see an example. We have the following in our analysis of the ABC company.
|2X14||2X15||15 vs. 14||2X16||16 vs. 15||2X17||17 vs. 16||FC 2X18|
We are looking at the data for the financial years 2X14, 2X15, 2X16, and 2X17. We have calculated the change between the years and can conclude that sales follow a stable positive trend over the four years. We also identify that the average growth is 20% year-on-year. Using this average growth, we can forecast the Sales for 2X18 at the amount of 518 thousand Euro.
Ratio Analysis is a quantitative method for financial analysis, which is the major part of Fundamental analysis. This method allows us to compare information from the financial statements and get more insight into a company’s operational efficiency, liquidity, and profitability. Ratio analysis is a commonly used way to make sense of all the available information for a business. Reviewing ratios is more involving than just comparing figures from the financial statements. The method involves evaluating the performance and financial position of a company by using information from the financial statements for one or more periods. Ratios can be used to analyze the performance of the business against historical data or other companies.
Establishing a trendline based on a ratio over a large number of reporting periods is also a way to highlight changes in the business that would not be evident if analyzing just from the perspective of a specific point in time. Calculating ratios for competitors and comparing them to the average can show how the business is doing compared to other similar companies. We compare to similar companies based on the assumption that companies in the same industry should typically have similar ratios.
We can summarize the most common categories of Ratios in the following:
- Operating performance
- Operating efficiency
- Financial and Business risk
We will look in detail in each group and perform case studies with actual data in future articles. For now, let’s see an example of a ratio.
The Current Ratio is a Liquidity ratio, part of the Ratios used to analyze the Solvency of the business. Liquidity ratios measure how liquid the company is, meaning how easily can the assets be converted into cash, comparing this liquidity to the current liabilities.
Current Ratio = Current Assets / Current Liabilities
Let’s say the ACME company has 200 thousand euro current assets and 180 thousand euro current liabilities. The Current Ratio will then equal
= 200 / 180 = 1.11 Euro assets for each Euro of liabilities. Usually, values between 1.2 and two are considered sufficient. A value lower than 1.2 might be an indication for the management that the ACME company may soon suffer from poor financial health. Analyzing the current ratio is not enough to draw this conclusion. To evaluate the result, we need to perform more extensive analysis, including a lot more ratios and financial analysis methods.
Valuation analysis is when we estimate the fair value of a business or other assets. It is a more sophisticated method and is more common in investment banking, private equity funds, mergers & acquisitions, leveraged buyouts, etc. It looks like a lot of number crunching, but it also has a creative side to it. Building valuation models cannot account for each factor influencing the value of a business in reality, so analysts have to make certain assumptions, on which the accuracy of their model depends.
The most common valuation methods used are:
- DCF analysis;
- Comparable Company Analysis; and
- Precedent Transaction Analysis.
We will take a deeper dive into valuation methods and models in future articles.
These methods go well together. Sensitivity analysis, or a What-If analysis, in financial modeling, is the process of changing one key input and analyzing how sensitive the model is to that change. In Scenario Analysis, we create separate scenarios for each input variable in our model.
Scenarios and Sensitivity analysis are essential in creating good financial models and minimizing the risk within them. Preparing different realistic scenarios and making sure our business model is capable of dealing with all the changes is the foundation of financial modeling itself.
Ane example of Sensitivity analysis can be when we decide to understand the impact of people entering the shopping mall on the total sales for the day. We determine that an increase of 10% in customers entering the mall increases sales by 5%. That way, we can build a financial model with a sensitivity analysis based on what-if statements around this relationship between people visiting the shopping mall and total sales. Now we know that if we increase people visiting with 10%, 50%, or 100%, we can expect a 5%, 25% or 50% increase in total sales respectively. This analysis shows us that the number of people visiting the mall influences sales.
Scenarios can be built to reflect the expected delivery costs of the ACME company’s restaurant supply division. We can prepare a Worst Case, Best Case, and Likely Case scenarios for prices of fuel and truck drivers, and our model will show what would that mean for the business. Scenarios are also useful for decision analysis. When we lay out scenarios in advance, the decision makers can see the expected impact of each course of action.
We will look into Scenarios and Sensitivity Analysis more in-depth in future articles.
Variance analysis looks at the differences between planned and actual numbers. This method is used a lot in management accounting as a way to maintain control over the business. When we perform variance analysis, we compare the actual amount incurred/sold to either budgeted amount, planned amount, or standard amount.
Variances can be two types based on their effect:
- (F) Favorable Variance – when actual results are better than expected results;
- (A) Adverse Variance – when actual results are worse than expected results.
A specific level of variance analysis allows the management to understand why discrepancies and fluctuations occur in the business and how to better control them. When calculating variances, we should always take the planned or budgeted amount and subtract the actual value. This way, we ensure that a positive number means a favorable variance, and a negative number – adverse variance.
The most common variances used in financial analysis are:
- Sales variances
- Sales Price variance
- Sales Volume variance
- Variable cost variances
- Direct Material variances
- Direct Labour cost variances
- Variable production overhead variances
- Fixed production overhead variances
- Budget Variance
- Volume Variance
We will not look into those in detail here. We will have a dedicated article to Variance Analysis. But to get a better understanding, let’s look at one example.
ACME produces bricks (among other things). They have a line of fire bricks. The standard cost card for the bricks includes direct materials of 5 kg per brick, at EUR 2.50 per kg. In March the company sold 5,000 bricks. The actual direct materials for those 5,000 bricks were 27,000 kg at EUR 2.35 per kg.
We will calculate the Direct Material variances for ACME.
Direct material price variance
27,000 used kg should have cost 67,500 Euro (at the standard cost of EUR 2.50 per kg).
But instead, they cost ACME 63,450 Euro (at the actual cost of EUR 2.35 per kg).
This gives us a Price variance of 67,500 – 63,450 = 4,050 Euro (F)
The Price variance shows us the effect of the change in cost/price.
This is a favorable variance, as we have decreased our cost by optimizing the price per kg.
Direct material quantity variance
ACME produced and sold 5,000 bricks that should have required 25,000 kg.
Instead, 27,000 kg were used to produce 5,000 bricks.
Valuing these at the standard cost, we have the effect of using more materials to =
= (25,000 x 2.50) – (27,000 x 2.50)
= 62,500 – 67,500
= (5,000) Euro (A).
The Quantity variance shows us the effect of the change in quantity.
This is an adverse variance, as we have used more material to produce the same quantity of product.
Direct material total variance
We calculate the Direct material variance as a sum of the Price and Quantity variances. Calculating it here we get
Total Variance = 4,050 + (5,000)
= (950) Euro (A)
The total variance is adverse, which means management should look into it. Even though the price variance is favorable, management should look into why the ACME company is spending more materials than the standard 5 kg per brick. This can be due to poor material quality (external factor) or due to problems with ACME’s machinery and equipment (internal factor).
Today we looked into various types of Financial Analysis, which are most commonly used to evaluate the performance of a business or project. Now you should have a better idea of what methods of analysis you can use in different situations. Most of the time, one approach is not enough to fully understand the analyzed business/project. Usually, analysts use a combination of techniques to derive more relevant conclusions about the business/project. This enables them to suggest the proper actions to the management or potential investors.
Thank you for reading! These were the most common Financial Analysis methods.
FCCA, FMVA, Co-founder of Magnimetrics
Hi! I am a finance professional with 10+ years of experience in audit, controlling, reporting, financial analysis and modeling. I am excited to delve deep into specifics of various industries, where I can identify the best solutions for clients I work with.
In my spare time, I am into skiing, hiking and running. I am also active on Instagram and YouTube, where I try different ways to express my creative side.
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The information and views set out in this publication are those of the author(s) and do not necessarily reflect the official opinion of Magnimetrics. Neither Magnimetrics nor any person acting on their behalf may be held responsible for the use which may be made of the information contained herein. The information in this article is for educational purposes only and should not be treated as professional advice. Magnimetrics accepts no responsibility for any damages or losses sustained in the result of using the information presented in the publication.