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Balance Sheet Projection Guide [Step-by-Step]
Source: wallstreetprep.com
Article summary:
1. The balance sheet forecast model in Excel should include at least two years of historical data and reclassify GAAP to suit the company's needs.
2. Working capital items, such as accounts receivable and inventories, should be forecasted based on revenue and operating forecasts.
3. Long-term assets, such as PP&E and intangible assets, should be forecasted based on the company's operations, including capital expenditures and depreciation. Goodwill is usually straight-lined in a financial model, while deferred tax assets and liabilities are grown with revenue or straight-lined depending on available information.
Article analysis:
The article titled "Balance Sheet Projection Guide [Step-By-Step]" provides a step-by-step guide on how to forecast the balance sheet for a company, using Apple as an example. While the article offers some useful information and guidance, there are several potential biases and missing points of consideration that should be noted.
Firstly, the article heavily relies on sources from Wall Street Prep, which is a financial training and consulting firm. This reliance on a single source raises questions about potential bias and whether the information provided is objective. It would have been more balanced to include other reputable sources or provide a broader range of perspectives.
Additionally, the article does not explore potential risks or limitations of balance sheet forecasting. Forecasting future financials is inherently uncertain and subject to various external factors such as economic conditions, industry trends, and regulatory changes. It would have been helpful to acknowledge these uncertainties and provide guidance on how to incorporate them into the forecast.
Furthermore, the article lacks evidence for some of its claims. For example, when discussing working capital items, it suggests growing accounts receivable with sales but does not provide any justification or supporting data for this assumption. Including empirical evidence or industry benchmarks would have strengthened the credibility of the recommendations.
The article also fails to present alternative viewpoints or counterarguments. For instance, when discussing long-term debt forecasting, it assumes that companies will continue borrowing to maintain a stable capital structure without considering scenarios where companies may choose to reduce their debt levels or face difficulties in accessing credit markets.
There are also instances where the article includes promotional content for Wall Street Prep's other resources, such as their investment banking primer and financial modeling best practices guide. While it is understandable that they want to promote their own materials, it detracts from the objectivity of the article.
In conclusion, while the "Balance Sheet Projection Guide" provides some useful information on forecasting balance sheets, it has several potential biases and shortcomings. The heavy reliance on a single source, lack of evidence for claims, missing considerations, and promotional content all raise questions about the objectivity and completeness of the article. It would be beneficial to consult additional sources and consider a broader range of perspectives when conducting balance sheet projections.
Topics for further research:
Limitations of balance sheet forecasting
Factors affecting balance sheet projections
Incorporating uncertainties in financial forecasting
Industry benchmarks for working capital items
Alternative viewpoints on long-term debt forecasting
Critiques of Wall Street Prep's balance sheet projection methodology