Recent theoretical work argues that information risk is a non-diversifiable risk factor that is priced in the capital market. Using accruals quality to proxy for information risk, Francis et al. (2005) provide empirical support for this argument using a sample of US firms. This paper re-examines the interplay of accruals quality, information risk and cost of capital in Australia, where a number of important institutional and regulatory differences are hypothesized to affect the relation between accruals quality and cost of capital. The results suggest that, while accruals quality impacts on the cost of capital for Australian firms, some salient differences exist. In contrast to findings for US firms, the costs of debt and equity for Australian firms are largely influenced by accruals quality arising from economic fundamentals (i.e., innate accrual quality) but not discretionary reporting choices (i.e., discretionary accrual quality). This finding is consistent with our predictions based on the Australian institutional and regulatory environment. In addition, using both the asset pricing tests in Francis et al. (2005) and Core et al. (2008), we provide evidence consistent with accruals quality being a priced risk factor.

This article examines the efficiency of the National Football League (NFL) betting market. The standard ordinary least squares (OLS) regression methodology is replaced by a probit model. This circumvents potential econometric problems, and allows us to implement more sophisticated betting strategies where bets are placed only when there is a relatively high probability of success. In‐sample tests indicate that probit‐based betting strategies generate statistically significant profits. Whereas the profitability of a number of these betting strategies is confirmed by out‐of‐sample testing, there is some inconsistency among the remaining out‐of‐sample predictions. Our results also suggest that widely documented inefficiencies in this market tend to dissipate over time.

No abstract

Given the high correlation between a firm's stock price and market capitalisation, it is possible that the well-documented size anomaly is masking a share-price effect. Using a seemingly unrelated regression model to accommodate contemporaneous correlation between portfolios, we estimate the separate effects of firm size and share price on returns to Australian equity portfolios. The analysis is also extended to estimate seasonal components of size and price effects. Our major findings are: (i) firm size and share price have significant and independent effects on portfolio returns averaged over all months, (ii) the familiar negative relation between size and returns is confirmed across all months, and (iii) the relation between share price and returns is negative in July and positive in all other months (with the exception of January where no price effect occurs). These findings, which are consistent across subperiods and robust to method variations, highlight the need for future research to provide an economic foundation for the relation between average returns, size and price.

Proposed by M. Stutzer (1996), canonical valuation is a new method for valuing derivative securities under the risk-neutral framework. It is nonparametric, simple to apply, and, unlike many alternative approaches, does not require any option data. Although canonical valuation has great potential, its applicability in realistic scenarios has not yet been widely tested. This article documents the ability of canonical valuation to price derivatives in a number of settings. In a constant-volatility world, canonical estimates of option prices struggle to match a Black-Scholes estimate based on historical volatility. However, in a more realistic stochastic-volatility setting, canonical valuation outperforms the Black-Scholes model. As the volatility generating process becomes further removed from the constant-volatility world, the relative performance edge of canonical valuation is more evident. In general, the results are encouraging that canonical valuation is a useful technique for valuing derivatives.