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In this paper we employ a GMM‐based approach to test the restrictions imposed by a two‐factor ‘market and oil’ pricing model when a risk‐free asset is assumed to exist. We examine the Australian market which has several interesting features including self‐sufficiency in relation to oil, a large concentration of natural resource companies, susceptibility to the ‘Dutch disease’ and a diverse industry base. We extend previous literature by examining industry sector equity returns as different industry groups are likely to have different exposures to an oil factor, particularly in Australia. In the formal tests, we find evidence in favour of the model, particularly for industrial sector industries. The preferred model includes a domestic portfolio proxy for market returns in addition to the oil price factor and we find evidence of a positive market risk premium as well as a significantly priced oil factor.

The purpose of this paper is to provide some insights into the exchange rate exposure of Australian stock returns.

Using a dynamic econometric approach that allows for both asymmetry and time‐varying risk exposures in both the exchange rate variable and the market variable, a large sample of Australian firms were tested over the period of January 2001 and December 2005. The data were analysed using three different classification methods, forming portfolios according to industry sector, size deciles, and censoring deciles.

Although the evidence of exchange rate exposure is limited across the sample of industries, the following were found: a time‐varying asymmetric effect primarily in the utilities sector, time‐varying exposure in the materials and energy sectors, and an asymmetric effect in the technology sector. Further, some time‐varying asymmetric exchange rate exposure was found across most size and censoring deciles and also substantial evidence of a positive asymmetric effect in the market beta across all three classification methods.

This approach varies from previous studies in this area that only allow for asymmetry and time variation in exchange rate exposures. The paper also examines the Australian stock market, a market which has not been extensively tested in this area of empirical research.

This paper empirically assesses the determinants of conditional stock index autocorrelation with particular emphasis on the impact of return volatility that are theoretically linked through the behaviour of feedback traders.

The S&P 100, 500 and the NASDAQ 100 index are considered and volatility in each series is captured using option‐implied estimates taken from the Chicago Board Options Exchange. A seemingly unrelated regression approach is used in which trading volume and volatility are simultaneously modelled.

The results of this study suggest that low or even negative return autocorrelations are more likely in situations where: return volatility is high; price falls by a large amount; traded stock volumes are high; and the economy is in a recessionary phase.

The results confirm that previous related work showing a link between autocorrelation and volatility is not induced by a mechanical relation.

Usage of endogenously determined volatility measures in this area of the literature is justified.

This study provides a robustness test of the autocorrelation/volatility relation, as well as a further exploration of the utility inherent in option‐implied volatility.

The purpose of this paper is to examine whether portfolios comprising high‐ranked corporate social performance (CSP) firms out/underperform portfolios comprised of low‐ranked CSP firms. The authors employed a US sample covering the period 1998‐2007.

In the context of the Fama and French model augmented by momentum and industry factors, the authors test the significance of the alpha for a CSP difference portfolio, defined as high‐ranked minus low‐ranked CSP stocks.

The results are consistent with the “no‐linkage” hypothesis, which argues that no significant difference in the risk‐adjusted performance is expected between high‐ and low‐ranked CSP‐formed portfolios. Furthermore, little evidence was found that high‐ or low‐ranked CSP‐formed portfolios, irrespective of the portfolio formation type, systematically differ with regard to performance, size, book‐to‐market or momentum factors.

The authors employ sustainability CSP rankings that focus on environmental, social and governance (ESG) materiality factors, in contrast to many prior studies that solely use KLD ratings or just focus on a subarea of CSP. Moreover, the authors' dataset considerably improves upon previous studies employing similar data in which individual company rankings are not available.

Daniel and Titman (1997) contend that the Fama‐French three‐factor model’s ability to explain cross‐sectional variation in expected returns is a result of characteristics that firms have in common rather than any risk‐based explanation. The primary aim of the current paper is to provide out‐of‐sample tests of the characteristics versus risk factor argument. The main focus of our tests is to examine the intercept terms in Fama‐French regressions, wherein test portfolios are formed by a three‐way sorting procedure on book‐to‐market, size and factor loadings. Our main test focuses on ‘characteristic‐balanced’ portfolio returns of high minus low factor loading portfolios, for different size and book‐to‐market groups. The Fama‐French model predicts that these regression intercepts should be zero while the characteristics model predicts that they should be negative. Generally, despite the short sample period employed, our findings support a risk‐factor interpretation as opposed to a characteristics interpretation. This is particularly so for the HML loading‐based test portfolios. More specifically, we find that: the majority of test portfolios tend to reveal higher returns for higher loadings (while controlling for book‐to‐market and size characteristics); the majority of the Fama‐French regression intercepts are statistically insignificant; for the characteristic‐balanced portfolios, very few of the Fama‐French regression intercepts are significant.

In this paper we empirically investigate the tendency for beta risk to mean‐revert across industries. Using a sample of Australian stocks over the ten‐year period 1989 to 1998, our key results are as follows. We generally observe evidence of a mean reversion tendency — in particular, this seems most appropriate for the Gold, Energy, Finance and Consumer industry groupings. Moreover, there is some evidence that the mean reversion of beta is different across industries. Furthermore, we see that the maximum mean reversion beta occurs for the Gold industry — a value of approximately 1.4 (1.6) for the OLS (Scholes‐Williams) beta analysis. On the other hand, the minimum mean reversion beta based on the ‘All Stocks’ OLS analysis occurs for Miscellaneous Industries with a value of 0.4, while a similar minimum mean reversion beta based on the Scholes‐Williams analysis occurs for the Consumer industry grouping.

This paper examines the market timing ability of a sample of 62 Australian International equity funds using the returns‐based approach of Henriksson and Merton (1981) (H&M) and Treynor and Mazuy (1966) (T&M). Specifically, the primary focus is to investigate whether market timing ability bears any relationship to the stated fund allocation policy. Generally, the results indicate that fund managers do not successfully time the market. We also find that there is no relationship between the manager's stated level of activity on allocation and their market timing abilities as calculated using the H&M and T&M models. Managers are not successfully implementing their stated policies. These results are consistent with an irrelevance of perceived management style to fund policies and hence performance. Furthermore, it is indicative that fund managers are not successfully targeting particular classes of risk averse investors.

This paper aims to provide a critical discussion of the application of the research pitching template developed by Professor Robert Faff to a research topic of tax avoidance and firm risk. This letter provides a brief commentary on using the pitching template and discusses personal reflections on the pitching process.

This pitching research letter applies Faff’s pitching template and provides a critical commentary of the pitching process.

The team found that Faff’s pitching template is a valuable tool for conceiving research ideas. It helped the authors to identify, develop and articulate key aspects of the project. Further, they believe that completing the template was a beneficial and rewarding exercise, especially for early-career researchers.

This pitching research letter is tied to the team’s research idea that was pitched at the 2020 AFAANZ “Shark Tank” event. It provides original commentary on the use of Faff’s pitching template. It is not meant to retrofit published papers.