Financial Market Data Versus Accounting Data: Which Better Explains Stock Returns?
This paper presents the comparison of how financial market and accounting data affect stock prices and returns. The goal was to ascertain whether financial information or accounting data dominate in evaluating stock prices. Most valuation techniques used by firms are based on models using either acc...
Gespeichert in:
Veröffentlicht in: | International advances in economic research 2020-02, Vol.26 (1), p.59-72 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | This paper presents the comparison of how financial market and accounting data affect stock prices and returns. The goal was to ascertain whether financial information or accounting data dominate in evaluating stock prices. Most valuation techniques used by firms are based on models using either accounting variables (earnings, book value, cash flows, research and development expenses) or financial market data (e.g. beta, market value, interest). The answer is of great importance for valuators and investors as it will help them focus on the most important variables and make better valuations and choices. This answer is also important for accounting standard setters as the preferred method will serve as an indicator for the quality of financial statements and their importance to users. The paper contributes to the existing literature in the fields of value relevance of accounting information and firm valuation and accounting standards (e.g. International Financial Reporting Standards, United States General Accepted Accounting Principles). To answer this question, share prices were estimated based on financial data using the capital asset pricing model and for accounting data, using Ohlson’s model. The results were tested for both methodologies by comparing estimated share prices with actual ones. The greater the correlation between the two variables the better the explanatory power of the model. The focus was on S&P 500 firms for the period 2002–2017. |
---|---|
ISSN: | 1083-0898 1573-966X |
DOI: | 10.1007/s11294-020-09774-4 |