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This chapter takes a general approach to financial statement analysis and
continues the discussion begun in the first 11 chapters. The chapter begins
with a reminder that different users use financial statements for different
purposes. Regardless of specific purposes, all users perform financial
statement analysis in order to help them in decision-making. Recall that in
order for information to be useful for decision-making, it must be relevant.
Information will be relevant if it has feedback value and predictive value.
Financial statement analysis tools and techniques provide the means by
which users can assess past performance and predict future performance.
The chapter outlines three types of data that are used in financial statement
analysis: raw financial data, common size data, and ratio data. Financial
statement analysis assesses performance within a firm over time (time-series
analysis) and/or across firms in the same industry (cross-sectional analysis).
Raw financial data are the information that appears on the financial
statements, for example, total assets or current liabilities. Common size data
are derived by expressing each line item on the financial statements as a
percentage of a common base, for example, expressing all items on the
income statement as a percentage of sales, or all items on the balance sheet as
a percentage of total assets. Ratio data express the relationship between two
or more elements of data within financial statements and between financial
statements. The chapter also discusses some limitations in ratio analysis as
they are based on GAAP, with its many choices, estimates, and assumptions.
The ratios discussed in this chapter fall into six categories:
o Performance ratios
o Turnover ratios
o Short-term liquidity ratios
c h a p t e r
1 2
FINANCIAL STATEMENT
ANALYSIS
H Chapter 12 8/26/08 2: 30 PM Page 245
Financial Accounting Study Guide Chapter One.pdf
(4.6 MB, 需要: 1 个论坛币)
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