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Article
Publication date: 13 July 2015

Donna M. Dudney, Benjamas Jirasakuldech, Thomas Zorn and Riza Emekter

Variations in price/earnings (P/E) ratios are explained in a rational expectations framework by a number of fundamental factors, such as differences in growth expectations and…

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Abstract

Purpose

Variations in price/earnings (P/E) ratios are explained in a rational expectations framework by a number of fundamental factors, such as differences in growth expectations and risk. The purpose of this paper is to use a regression model and data from four sample periods (1996, 2000, 2001, and 2008) to separate the earnings/price (E/P) ratio into two parts – the portion of E/P that is related to fundamental determinants and a residual portion that cannot be explained by fundamentals. The authors use the residual portion as an indicator of over or undervaluation; a large negative residual is consistent with overvaluation while a large positive residual implies undervaluation. The authors find that stocks with larger negative residuals are associated with lower subsequent returns and reward-to-risk ratio, while stocks with larger positive residuals are associated with higher subsequent returns and reward-to-risk ratio. This pattern persists for both one and two-year holding periods.

Design/methodology/approach

This study uses a regression methodology to decompose E/P into two parts – the portion of E/P than is related to fundamental determinants and a residual portion that cannot be explained by fundamentals. Focussing on the second portion allows us to isolate a potential indicator of stock over or undervaluation. Using a sample of stocks from four time periods (1996, 2000, 2001, and 2008, the authors calculate the residuals from a regression model of the fundamental determinants of cross-sectional variation in E/P. These residuals are then ranked and used to divide the stock sample into deciles, with the first decile containing the stocks with the highest negative residuals (indicating overvaluation) and the tenth decile containing stocks with the highest positive residuals (indicating undervaluation). Total returns for subsequent one and two-year holding periods are then calculated for each decile portfolio.

Findings

The authors find that high positive residual stocks substantially outperform high negative residual stocks. This is true even after risk adjustments to the portfolio returns. The residual E/P appears to accurately predict relative stock performance with a relatively high degree of accuracy.

Research limitations/implications

The findings of this paper provide some important implications for practitioners and investors, particularly for the stock selection, fund allocations, and portfolio strategies. Practitioners can still rely on a valuation measure such as E/P as a useful tool for making successful investment decisions and enhance portfolio performance. Investors can earn abnormal returns by allocating more weights on stocks with high E/P multiples. Portfolios of high E/P multiples or undervalued stocks are found to enjoy higher risk-adjusted returns after controlling for the fundamental factors. The most beneficial performance holding period return will be for a relatively short period of time ranging from one to two years. Relying on the E/P valuation ratios for a long-term investment may add little value.

Practical implications

Practitioners and academics have long relied on the P/E ratio as an indicator of relative overvaluation. An increase in the absolute value of P/E, however, does not always indicate overvaluation. Instead, a high P/E ratio can simply reflect changes in the fundamental factors that affect P/E. The authors find that stocks with larger negative residuals are associated with lower subsequent returns and coefficients of variation, while stocks with larger positive residuals are associated with higher subsequent returns and coefficients of variation. This pattern persists for both one and two-year holding periods.

Originality/value

The P/E ratio is widely used, particularly by practitioners, as a measure of relative stock valuation. The ratio has been used in both cross-sectional and time series comparisons as a metric for determining whether stocks are under or overvalued. An increase in the absolute value of P/E, however, does not always indicate overvaluation. Instead, a high P/E ratio can simply reflect changes in the fundamental factors that affect P/E. If interest rates are relatively low, for example, the time series P/E should be correspondingly higher. Similarly, if the risk of a stock is low, that stock’s P/E ratio should be higher than the P/E ratios of less risky stocks. The authors examine the cross-sectional behavior of the P/E (the authors actually use the E/P ratio for reasons explained below) after controlling for factors that are likely to fundamentally affect this ratio. These factors include the dividend payout ratio, risk measures, growth measures, and factors such as size and book to market that have been identified by Fama and French (1993) and others as important in explaining the cross-sectional variation in common stock returns. To control for changes in these primary determinants of E/P, the authors use a simple regression model. The residuals from this model represent the unexplained cross-sectional variation in E/P. The authors argue that this unexplained variation is a more reliable indicator than the raw E/P ratio of the relative under or overvaluation of stocks.

Details

Managerial Finance, vol. 41 no. 7
Type: Research Article
ISSN: 0307-4358

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Article
Publication date: 11 February 2014

Andreas Rauterkus and George Munchus

– This study aims to examine empirically the relationship between loan denials and lender distance and location.

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Abstract

Purpose

This study aims to examine empirically the relationship between loan denials and lender distance and location.

Design/methodology/approach

This study uses the 2003 Survey of Small Business Finance (SSBF) to draw the sample. This survey, conducted by the Board of Governors of the Federal Reserve, collects information on small businesses' use of financial services. In total the survey gathered information representing 4,240 firms (all sample firms have fewer than 500 employees). A number of statistical tests are conducted to test the relationship between loan denials and lender characteristics.

Findings

The results of this study indicate that credit scores have no impact on the geographical location and lender distance; however, lender distance decreases with the length of relationship with the lender and the age of the business. This suggests that informationally opaque businesses seek out lenders nearby to maximize the value of soft information, whereas established businesses put no value on that. However, the probability of loan denial is not affected by the distance between the borrower and the lender. At the same time borrowers in rural areas are more likely to be denied. Thus, there seems to be a location effect in lending.

Originality/value

This study closes a gap in the literature with regard to the value of soft information in light of increasing bank consolidation. Furthermore, this paper uses borrower data, making this – to the authors' knowledge – the first study on lending distance that does not utilize lender data.

Details

Journal of Small Business and Enterprise Development, vol. 21 no. 1
Type: Research Article
ISSN: 1462-6004

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