Accounting Valuation Definition
Accounting valuation is the valuation of a company’s assets and liabilities for the purpose of financial reporting. Assets owned by a company and the liabilities accrued over a certain period of time must be correctly valued and included in the company’s balance sheet when compiling a financial report.
There are many methods of valuation of a company’s assets and liabilities and they are all important for the preparation of a company’s financial statement.
A Little More on What is Accounting Valuation
Accuracy in the value of assets held by a company is crucial, especially for the purpose of preparation of financial statements. In accounting, diverse valuation methods exist, for instance, the accepted options model and assets price model are some of the valuation methods. The valuation of assets is also dependent on the type of asset being valued. For example, the valuation of fixed assets is based on historical price while marketable assets are valued using the current market value.
However, valuation on its own is not enough for the preparation of financial statements, analysis of the valuation is likewise important. The valuation of a company’s assets and liabilities can be done quarterly, monthly or annually. The information provided is used for the compilation of financial reports.
Reference for “Accounting Valuation”
Academic research on “ Accounting Valuation”
Accounting valuation, market expectation, and cross-sectional stock returns, Frankel, R., & Lee, C. M. (1998). Accounting valuation, market expectation, and cross-sectional stock returns. Journal of Accounting and economics, 25(3), 283-319. This study examines the usefulness of an analyst-based valuation model in predicting cross-sectional stock returns. We estimate firms’ fundamental values (V) using I/B/E/S consensus forecasts and a residual income model. We find that V is highly correlated with contemporaneous stock price, and that the V/P ratio is a good predictor of long-term cross-sectional returns. This effect is not explained by a firm’s market beta, B/P ratio, or total market capitalization. In addition, we find errors in consensus analyst earnings forecasts are predictable, and that the predictive power of V/P can be improved by incorporating these errors.
Accounting valuation, market expectation, and the book-to-market effect, Frankel, R. M., & Lee, C. (1998). Accounting valuation, market expectation, and the book-to-market effect. Market Expectation, and the Book-to-Market Effect. Accounting-based valuation theory suggests that a firm’s value (V) is a combination of its book value (B) and market expectations of future earnings. We empirically evaluate the ability of this model to explain the book-to-market (B/P) effect. We find that our empirical proxies of V dominate B in cross-sectional correlations with price, and that the resulting V/P ratios also predict cross-sectional returns. In addition, we find that errors in analyst consensus forecasts are predictable, and that returns from trading on these predictable errors account for much of the B/P effect.
Accounting, valuation and duration of football player contracts, Amir, E., & Livne, G. (2005). Accounting, valuation and duration of football player contracts. Journal of Business Finance & Accounting, 32(3‐4), 549-586. FRS 10 requires investments in player contracts by football companies to be capitalized and amortized. Given the high degree of uncertainty associated with such contracts, it is not clear that this treatment is consistent with asset capitalization criteria. The evidence provided in this paper does not support inconclusively this capitalization requirement in that it indicates weak association of investment in player contracts with three measures of future benefits. In particular, the duration of this association is at most two years, which is shorter than the duration implied by the amortization period reported by sample companies. Nonetheless, other findings suggest that market participants seem to agree with the treatment prescribed by FRS 10. These results should be of interest to practitioner and standard setters who (axiomatically) regard intangibles acquired in an arm’s length transaction as assets.
Linear accounting valuation when abnormal earnings are AR (2), Callen, J. L., & Morel, M. (2001). Linear accounting valuation when abnormal earnings are AR (2). Review of Quantitative Finance and Accounting, 16(3), 191-204. The Ohlson (1995) model assumes that abnormal earnings follow an AR(1) process primarily for reasons of mathematical tractability. However, the empirical literature on the Garman and Ohlson (1980) model finds that the data support an AR(2) lag structure for earnings, book values and dividends. Moreover, the AR(2) process encompasses a far richer variety of time series patterns than does the AR(1) process and includes the AR(1) process as a special case. This paper solves the Ohlson model directly for an AR(2) abnormal earnings dynamic. The model is estimated on a time series firm-level basis following the approach used by Myers (1999). It is found that, like the Ohlson AR(1) model, the Ohlson AR(2) model severely underestimates market prices even relative to book values. These results further bring into question the empirical validity of the Ohlson model.
Taxation of international investment and accounting valuation, De Waegenaere, A., & Sansing, R. C. (2008). Taxation of international investment and accounting valuation. Contemporary Accounting Research, 25(4), 1045-1066.
Accounting valuation: Is earnings quality an issue?, Cornell, B., & Landsman, W. R. (2003). Accounting valuation: Is earnings quality an issue?. Financial analysts journal, 59(6), 20-28. From a valuation perspective, no “best”—or even consistent—measure of pro forma earnings exists. An increasing number of companies are including pro forma earnings together with net income figures in their earnings releases. The explanation offered by these companies is that the pro forma numbers reflect the company’s true earning power more accurately than net income numbers based on generally accepted accounting principles. Company support for such estimates of earnings is echoed by analysts. Regulators, however, are concerned about the potentially misleading qualities of non-GAAP earnings measures. In response to concerns about pro forma earnings, the Financial Accounting Standards Board recently proposed an agenda project related to the use of pro forma data in which it cites three concerns. First, companies are increasingly relying on pro formaperformance measures in earnings releases and other investor-related communications. Second, no common definitions of the elements of financial performance exist and practices regarding their presentation are inconsistent. Third, no consensus exists about which performance measures should be in financial statements. The concern over which measure of income is the most meaningful for valuation has produced a host of empirical studies designed to estimate the “quality” of competing earnings measures. The specific results are a mixed bag; findings depend on the earnings measures being compared, the time period, the sample of companies, and the metric used. The overall result, however, is that the differences in information conveyed by the competing definitions of earnings—from GAAP earnings to pro forma income—are not large. In addition, the empirical studies suffer from the problems that non-GAAP earnings also are not unambiguously defined and that different companies compute pro forma income differently. As a result, studies that compare GAAP earnings with pro forma income may not be comparing the same two measures for all companies. The thesis of this article is that, from a valuation perspective, the entire debate about earnings quality is theoretically unresolvable. No consistently meaningful way is available to condense all the historical financial information that is relevant for forecasting future performance into one measure (or a time series of one measure). Furthermore, attempts by regulatory/standard-setting bodies to determine an appropriate definition of “pro forma income” distracts attention from more-critical problems involving omissions and ambiguities in the constituent items that make up any measure of earnings. We make two arguments. First, none of the measures of earnings, including GAAP, condenses financial statement information satisfactorily for forecasting purposes. Second, no meaningful criterion exists for determining whether one earnings measure is better than another. The principal conclusion of the discussions is that efforts to determine which measure of earnings is appropriate for a company to disseminate are misguided. What is critical is that the basic elements that comprise any measure of earnings be presented with sufficient clarity and at a sufficient level of disaggregation that investors can answer fundamental questions about revenues, costs, and capital. If sufficient data are available to answer these questions, investors can aggregate the basic information into any earnings measure they believe provides the most insight into forecasting future cash flows. The second conclusion is that, although companies should be free to provide any aggregate measure of earnings that they deem appropriate, they should follow some basic guidelines. Because none of the alternatives to GAAP earnings is precisely defined or consistently applied, companies that release non-GAAP numbers should explain how the numbers differ from the GAAP numbers.