Principles of Expense Recognition
The IASB Conceptual Framework defines expenses as reductions in economic benefits occurring throughout... Read More
Financial analysis is the process of interpreting and evaluating a company’s performance
and position in the context of its economic environment. Analysts use financial analysis to make investment decisions and recommendations.
As a generic term, the financial statement analysis framework describes the process of assessing financial statements, supplemental information, and other sources of information. Essentially, the financial statement analysis framework helps analysts draw conclusions and make informed recommendations, such as whether to invest in a company or extend a loan.
The financial statement analysis framework involves six steps. These include:
Step 1: Articulate the Purpose and Context of the Analysis
This step guides further decisions about the approach, tools, data sources, and final report format. It also defines the target audience, end product, and timeframe. Further, it identifies the requisite resources and resource constraints. After this, the analyst should be able to compile the specific questions to be answered by the analysis.
The output from this step includes:
Step 2: Collect Data
The analyst gathers the necessary data to answer the specific questions compiled in Step 1. The sources of information at this stage include:
At this step, the analysts should be able to produce output such as completed questionnaires where applicable and financial statements and other quantitative data, structures in a consumable form.
Step 3: Process Data
The analyst processes the data collected in step 2 using various analysis tools. This may involve computing financial ratios and growth rates, creating charts, preparing common-size financial statements, or performing statistical analyses such as regression analysis.
Step 4: Analyze and Interpret the Data
The analyst assesses the data processed in step 3. The analyst should be able to interpret the output of the analysis and use it to support a conclusion or recommendation. The results from this step include analytical results, forecasts, and valuations.
Step: Develop and communicate conclusions and recommendations:
The analyst should communicate the conclusion and recommendations derived from the analysis in an appropriate format that answers the questions posed in Step 1. The analyst uses analytical results and previous reports based on institutional guidelines to answer the questions posed in Step 1.
The format of communicating conclusions or recommendations depends on the analytical objectives, institution, audience, and requirements of the regulatory agencies or professional standards.
Step 6: Follow-up
The analyst should perform periodic reviews to determine if the initial conclusions and recommendations still hold. This may require a periodic repeat of all the previous steps.
Question
In which step of the financial statement analysis framework would performing sensitivity analysis most likely be involved?
- Follow-up.
- Processing data.
- Collecting input data.
Solution
The correct answer is B.
In the financial statement analysis framework, performing sensitivity analysis is most appropriately categorized under the step of “Processing Data.” Sensitivity analysis is a technique used to assess the impact of changes in input variables on the outcome of a financial model. It involves varying key assumptions or parameters within the model to evaluate how these changes affect the results. This process is a part of data processing, as it involves manipulating and analyzing the collected data to gain deeper insights into the financial performance and risks associated with a company.
A is incorrect.“Follow-up” is concerned with reviewing the conclusions and recommendations of the analysis over time to ensure their continued validity. It does not involve the actual processing or analysis of data.
C is incorrect. “Collecting input data” involves gathering the necessary financial statements, economic data, and other relevant information required for the analysis. It precedes the processing of data and does not encompass the analytical techniques such as sensitivity analysis that are applied to the collected data.