The Relative Performance of Small Cap Firms and Default Risk across the Business Cycle: International Evidence
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Abstract
I. INTRODUCTION The time-varying nature of the firm size effect has been the subject of growing interest, particularly in the aftermath of the recent financial crisis. Small-cap firms provide a significant nexus for entrepreneurship and innovation and hence might be viewed as less prone to governance problems than large firms. (1) This could in part explain the superior performance of small-cap firms over long time horizons, and during times of recovery from economic downturns. Lower productivity and high exposure to debt may in part explain their underperformance over recessions, as reported in the academic literature (2) and in the popular press. (3) Kim and Burnie (2002) suggest that the time-varying nature of the firm size effect may be attributable to the business cycle per se, as captured by dummy variables in their regression model. Smaller firms may also suffer from relatively lower productivity and high financial leverage during downturns (Chan and Chen, 1991). More recently, Switzer (2010) shows that the US small cap premium is significantly related to default risk in the economy, which may impact investments in R&D and innovation. This paper extends previous work that has focused on the US to look at the impact of the business cycle on the small cap premium internationally, in particular, for stocks in G-7 countries and in the Middle-East North African (MENA) region. New evidence is presented indicating that default risk, which may be tied to innovative investments, is not priced in non-common law settings where protection of shareholders and creditors in bankruptcy states is limited. The remainder of this paper is organized as follows. The data are described in Section II. Section III looks at the innovative efforts and performance of small-caps vs. large caps across countries over recent business cycle peaks and troughs. Section IV revisits the small cap premium for G-7 and MENA countries. As is shown therein, the small firm anomaly appears to be largely a North American phenomenon in the post 2000 period. Section V looks at business cycle effects and the impact of various risk factors on the time variation of the small firm premia across countries. The paper concludes with a summary in Section VI. II. DESCRIPTION OF THE DATA The small cap and large cap portfolios for the returns for France, Germany, Italy, Japan and the UK, are the Morgan Stanley portfolio size based series that begin in January 1995. The US small cap series is based on monthly returns on the Ibbotson/DFA small stock portfolio, which is available from January 1926. The U.S. large cap portfolio from Morningstar/Ibbotson is the S&P 500. The U.S. market portfolio proxy is the CRSP value weighted portfolio of NYSE, AMEX and NASDAQ stocks, which is available since 1926. The US risk free rate is the 1 month T-bill rate, from WRDS. For the series, the only continuous extant proxy for Canadian small firms is Nesbitt Burns Small Cap Index, which is available since producing a benchmark series in January 1987. The US risk factors are obtained from Morningstar EnCorr. Default risk (bond default premium) is measured by the geometric difference between total returns on long-term corporate bonds and long-term government bonds. Term Structure risk (bond horizon premium) is measured by the geometric difference between Government Long Bond and Treasury Bill Returns. Inflation is based on the US consumer price index. R&D and sales data of firms are from COMPUSTAT, with the S&P 600 Small Cap index used as the reference for compiling the small-cap company data. The business cycle peaks and troughs are based on the National Bureau of Economic Research (NBER) dates. III. DIFFERENTIAL RETURNS AND INNOVATIVE EFFORTS FOR SMALL-CAPS AND LARGE CAPS ACROSS COUNTRIES Figure 1 illustrates the differential returns for small-caps vs. large-caps for the G-7 countries. Recession intervals are highlighted with the grey shading of the graphs. …
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Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it