Academic journal article Journal of Economics, Finance and Administrative Science

The Relevance of Using Accounting Fundamentals in the Mexican Stock Market/La Relevancia De Utilizar Fundamentos De Contabilidad En la Bolsa Mexicana De Valores

Academic journal article Journal of Economics, Finance and Administrative Science

The Relevance of Using Accounting Fundamentals in the Mexican Stock Market/La Relevancia De Utilizar Fundamentos De Contabilidad En la Bolsa Mexicana De Valores

Article excerpt

1. Introduction

This paper examines whether the application of a set of accounting fundamental signals can provide value relevance to investors in the Mexican Stock Market. The use of fundamental analysis has been shown to be successful in developed markets. However, in emerging markets there is little evidence of the use of fundamental analysis to better understand financial markets. Research on this relationship in developed markets is considerable (Ball & Brown, 1968; Kothari, 2001; Richardson, Tuna, & Wysocki, 2010). Growing evidence of temporary market mispricing -also known as earnings announcement drift or accounting anomalies-in developed markets (Abarbanell & Bushee, 1998; Piotroski, 2000; Piotroski, 2005) and the scarcity of research on this topic in developing markets (Aggarwal & Gupta, 2009; Lopes & Galdi, 2008) was a motivation to further examine this phenomenon in one of the most important Latin American markets, the Mexican Stock Market.

One contribution of this paper is to demonstrate the potential use of accounting fundamental signals to investors in an emerging market. According to valuation theory, accounting earnings are converted over time into free cash flow to investors, creditors and the firm, which constitute the main components for estimating the intrinsic value of the firm, as reflected in the stock price. Accounting fundamental analysis examines detailed accounting data -reported in financial statements- to improve understanding of how efficiently and effectively a firm generates earnings over time, as well as its potential to grow and convert these earnings into free cash flows. However, the way in which financial statement data can be used and how this is related to future earnings and future stock returns in Latin American markets is still not completely understood.

Besides the contribution to the existing literature on capital markets in Latin America, the findings of this paper can help investors not only to identify possible abnormal returns to an investment strategy, but also to increase the expected utility by using accounting data to construct hedge portfolios. As such, an optimal balance between expected return and market and country risk can be achieved.

Two scores constructed by changes in accounting signals are proposed in this paper. These scores are hypothesized to be positively related to future one-year and two-year stock returns. After an extensive literature review, these two scores -F-score and L-score- are developed based on two seminal papers, Piotroski (2000) and Lev and Thiagarajan (1993). These scores are constructed so that the higher the score, the more the likelihood of future one-year and two-year market excess returns. To further eliminate the alternative explanation that these scores might measure previous factors found in the literature that are consistently related to future returns, econometric models are designed to show how these scores add value relevance beyond the factors provided in the literature -book-to-market ratio, firm size, and earnings per share.

Findings suggest that both L-score and F-score provide value relevant information for investors when forming portfolios. A significant relationship was found between the scores and one-year and two-year stock returns and excess market returns. A further sensitivity analysis shows that simple equally-weighted portfolios constructed with high F-score stocks can yield consistent positive returns. (1)

2. Theoretical perspectives

Most of the research on accounting fundamental analysis in capital markets has used archival data and econometric models based on multiple regression models, sometimes complemented with time-series analysis for forecasting. The main independent variables of these models are accounting signals that are usually based on percentage changes from one period to another. The main dependent variables of these models are contemporary earnings and returns, future earnings and future returns, and analyst forecasting of returns. …

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