Accurate and informed financial decision-making is crucial for the successful operation of any business organisation. Business analysts use financial analysis to navigate company finances and better understand future outlooks.
Making informed business decisions becomes easier with the data obtained from financial analysis. Along with assessing the impact of various scenarios, businesses can evaluate the robustness of their financial projections.
Business analysts create financial models for different kinds of businesses. An integral part of the financial modelling technique is sensitivity analysis. This blog explores the nitty-gritty of sensitivity analysis and the impact of assumptions in financial models.
What Is Sensitivity Analysis?
Sensitivity analysis is also termed what-if analysis. It is a powerful financial modelling technique through which decision-makers can assess the outcome of financial models when there are changes in leading input variables.
There is a close relationship between dependent and independent variables. With sensitivity analysis, analysts can analyse this relationship closely and help organisations identify potential opportunities and risks. Overall, it leads to better financial decision-making for the organisation.
Every business organisation has a budget, whatever the magnitude of the same. Sensitivity analysis examines the impact on the budget when specific changes are made in the assumptions on which the budget is based. Hence, this analysis is also referred to as a what-if analysis.
Sensitivity analysis can be carried out manually or using a Microsoft Excel spreadsheet. However, manual calculations might seem challenging if the dataset is vast.
Primary Components of Sensitivity Analysis
Let’s look at the key components of sensitivity analysis in finance:
Financial Models
Different kinds of financial models are used in sensitivity analysis. Some of the prominent ones are:
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Capital Asset Pricing Model (CAPM)
Depending on the risk, this model calculates the expected return of any asset relative to the overall market.
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Discounted Cash Flow Model (DCF)
With the discounted cash flow model, analysts estimate the value of an investment based on its expected future cash flow, which is discounted to their present value.
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Black-Scholes Option Pricing Model
With this model, analysts can determine the fair price of a particular option. They consider various factors, including strike price, stock price and the expiration time.
Assumptions and Scenarios
The fundamentals for sensitivity analysis are scenarios and assumptions. Thus, analysts can test the results of input variables on different financial models.
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Baseline scenario
The baseline scenario presents the most expected assumptions. These are primarily based on present market situations and conditions and historical data.
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Alternative scenario
Alternative scenarios are a different version of baseline scenarios. These incorporate changes in primary assumptions to understand how they affect dependent variables.
Parameters and Variables
The pillar of sensitivity analysis rests on understanding the relationship between parameters and variables in financial models.
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Independent Variables
These are input variables which can change and impact a financial model’s outcome. Some of the best examples of independent variables are growth rates, interest rates and inflation rates.
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Dependent Variables
These are output variables but are impacted by independent variables. Instances of dependent variables include stock prices, internal rate of return and net present value.
Applications of Sensitivity Analysis in Finance
Sensitivity analysis has widespread application in finance. Let us take a look at some of them:
Financial Forecasting
Businesses can improve the reliability and accuracy of financial forecasting with sensitivity analysis. Some areas of financial forecasting include:
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Budgeting and financial planning
With the implementation of sensitivity analysis in budgeting and financial planning, business organisations identify potential opportunities and risks. This helps in better resource allocation and making more informed business decisions.
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Forecasts for revenue and earnings
Sensitivity analysis guides organisations towards developing accurate earning and revenue forecasts by adjusting prime variables like pricing, sales growth rates and customer retention.
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Cash Flow Projections
With sensitivity analysis, organisations can understand the impact on cash flow projections when there are changes in variables like capital expenditures, working capital requirements and financing costs.
Investment Analysis
When it comes to investment evaluation, sensitivity analysis plays a pivotal role. It includes the valuation of bonds and stocks and decisions regarding capital budgeting.
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Bonds and stocks valuation
If there are changes in key variables like dividend payout ratios or growth and interest rates, analysts can calculate how these changes might impact bonds and stock valuation. This provides clear perceptions about potential rewards and risk scopes.
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Decisions on capital budgeting
Sensitivity analysis experts evaluate the feasibility of various investment projects. This is done by analysing input variables like internal rate of return, revenues, costs and available rates of discounts on the project’s net value at present.
Risk Management
Sensitivity analysis proves to be invaluable for risk management for organisations. It helps identify, assess and combat risks.
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Market Risk Assessment
Market variables like interest rates, exchange rates, asset prices, etc., impact businesses significantly. Analysts can analyse these variables to help organisations evade exposure to market risks and develop necessary hedging strategies.
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Credit Risk Assessment
Sensitivity analysis assesses the potential impact on loan portfolios with changes in variables like borrower credit scores, interest rates and economic conditions.
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Operational Risk Assessment
Sensitivity analysis helps identify the impact of changes brought by operational variables like labour rates, production expenses, regulatory compliance expenses, etc.
Advantages of Sensitivity Analysis
There are several advantages of using sensitivity analysis, such as the following:
- It helps in making more accurate financial forecasts and predictions.
- It helps in informed decision-making, bringing the best results for the business.
- Provides credibility to financial models.
- Helps in identifying areas for improvement in the business organisation.
Conclusion
Sensitivity analysis is crucial for businesses to make sound investment decisions, from identifying potential risks and grabbing opportunities to catching analytical errors and simplifying complex models. Financial decision-makers of an organisation have the scope to make better choices and allocate resources more effectively with sensitivity analysis.
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FAQs
- Does sensitivity analysis help in financial statement forecasts?
Yes, sensitivity analysis helps in financial statement forecasts. Businesses can change the interest rate, tax rate, sales growth rate, etc. and see how it impacts cash flow, net income and return on investment.
- What is the feature of sensitivity analysis in MS Excel?
If you want to do sensitivity analysis in MS Excel, you have to use Data Tables. These tables provide a shortcut to calculate multiple versions in a single operation. You can also view and compare the different results of all the versions on the worksheet.
- Can sensitivity analysis be done manually?
Yes, sensitivity analysis can be done manually, too. However, if the data volume is vast, MS Excel is a better choice as it significantly lowers the risk of errors.
