Exploring the moderating role of growth options on the relation between board characteristics and management earnings forecasts

Manuscript Type
Empirical
Research Question/Issue
This study examines whether director independence, reputation, and financial expertise are related to management earnings forecast (MEF) activity. In particular, we examine whether such a relationship is moderated by firms’ growth options.
Research Findings/Insights
Using Australian archival data for 1,928 firm-years between 1999 and 2006, we find several board characteristics have a significant positive relationship with: (1) the likelihood of firms issuing MEFs; (2) their specificity; (3) their accuracy; and (4) a negative relationship with their bias. For (1), (2), and (3) we show that these relationships are accentuated for firms with high growth options.
Theoretical/Academic Implications
While the theory of voluntary disclosure suggests firms will disclose information that is favorable to them or their managers, well-governed firms issue informative MEFs that potentially reduce information asymmetries in capital markets. We extend the prior literature by showing that such a relation is enhanced in the presence of information asymmetry and moral hazard associated with growth options.
Practitioner/Policy Implications
Our results have strategic implications for nomination committees by showing that independent directors and those with strong reputations and financial expertise enhance the governance of high growth firms. We also inform the regulatory debate by showing that good corporate governance enhancing disclosure quality is context-specific – it is not a case of “one size fits all”.

Has the structural break slowed down growth rates of stock markets?

In this paper, we use the common structural break test suggested by Bai et al. (1998) to test for a common structural break in the stock prices of the US, the UK, and Japan. On the basis of the structural break, we divide each country's stock price series into sub-samples and investigate whether or not the structural break had slowed down the growth of stock markets. Our main findings are that when stock markets are modelled in a trivariate sense the common structural break turns out to be 1990:02, with the confidence interval including several episodes, such as the asset price bubble when housing prices and stock prices in Japan reached a peak in 1988/1989, the early 1990s recession in the UK, the business cycle peak of July 1990, the August 1990 Iraqi invasion of Kuwait and the March 1991 business cycle trough. Annual average growth rates suggest that the structural break has slowed down the growth rate of the US, the UK and Japanese stock markets.

Common trends and common cycles in stock markets

In this paper we examine the role of permanent and transitory shocks in explaining variations in the S&P 500, Dow Jones and the NASDAQ. Our modeling technique involves imposing both common trend and common cycle restrictions in extracting the variance decomposition of shocks. We find that: (1) the three stock price indices are characterized by a common trend and common cycle relationship; and (2) permanent shocks explain the bulk of the variations in stock prices over short horizons.

Investor heterogeneity and the cross-sectional stock returns in China

We examine the relationship between divergence of opinion and the cross-sectional stock returns in Chinese A share market where short-selling of stocks is prohibited by law. Using a proxy for divergence of opinion among the entire investor base, we document a positive relationship between divergent beliefs and future stock returns. This is in sharp contrast to Miller's (1977) prediction of a negative relationship between the two. The result is likely to be driven by the dominance of individual investors and their speculative trading behaviors in China. Miller's prediction is confirmed when divergence of opinion is measured using data on mutual fund holdings. Our results are robust to a number of common return predictors. We also find a significantly negative relationship between the fraction of tradable shares in listed Chinese companies and future stock returns. Increase in the fraction of tradable shares tends to reduce the predictability of stock returns using divergence of opinion.

Determinants of stock price bubbles

In this paper we propose a cross-sectional model of the determinants of asset price bubbles. Using 589 firms listed on the NYSE, we find conclusive evidence that trading volume and share price volatility have statistically significant effects on asset price bubbles. However, evidence from sector-based stocks is mixed. We find that for firms belonging to electricity, energy, financial, and banking sectors, and for the smallest size firms, trading volume has a statistically significant and positive effect on bubbles. We do not discover any robust evidence of a statistically significant effect of share price volatility on bubbles at the sector-level.

Neural network and interval type-2 fuzzy system for stock price forecasting

Stock price forecast has long been received special attention of investors and financial institutions. As stock prices are changeable over time and increasingly uncertain in modern financial markets, their forecasting becomes more important than ever before. A hybrid approach consisting of two components, a neural network and a fuzzy logic system, is proposed in this paper for stock price prediction. The first component of the hybrid, i.e. a feedforward neural network (FFNN), is used to select inputs that are highly relevant to the dependent variables. An interval type-2 fuzzy logic system (IT2 FLS) is employed as the second component of the hybrid forecasting method. The IT2 FLS’s parameters are initialized through deployment of the k-means clustering method and they are adjusted by the genetic algorithm. Experimental results demonstrate the efficiency of the FFNN input selection approach as it reduces the complexity and increase the accuracy of the forecasting models. In addition, IT2 FLS outperforms the widely used type-1 FLS and FFNN models in stock price forecasting. The combination of the FFNN and the IT2 FLS produces dominant forecasting accuracy compared to employing only the IT2 FLSs without the FFNN input selection.

Has political instability contributed to price clustering on Fiji's stock market?

The goal of this article is to examine evidence of stock price clustering on the South Pacific Stock Exchange, located in Fiji, and explore its determinants. We find that stock prices cluster at the decimal of 0 and 5, with almost half of prices settling on these two decimals. Upon investigating the determinants of price clustering on the South Pacific Stock Exchange we find that price level and volume of trade have a statistically significant positive effect on price clustering. We also propose and test a ‘panic trading’ hypothesis which states political instability induces price clustering. We find evidence that political instability in Fiji induces price clustering behaviour.

N-dimensional animal energetic niches clarify behavioural options in a variable marine environment

Animals respond to environmental variation by exhibiting a number of different behaviours and/or rates of activity, which result in corresponding variation in energy expenditure. Successful animals generally maximize efficiency or rate of energy gain through foraging. Quantification of all features that modulate energy expenditure can theoretically be modelled as an animal energetic niche or power envelope; with total power being represented by the vertical axis and n-dimensional horizontal axes representing extents of processes that affect energy expenditure. Such an energetic niche could be used to assess the energetic consequences of animals adopting particular behaviours under various environmental conditions. This value of this approach was tested by constructing a simple mechanistic energetics model based on data collected from recording devices deployed on 41 free-living Magellanic penguins (Spheniscus magellanicus), foraging from four different colonies in Argentina and consequently catching four different types of prey. Energy expenditure was calculated as a function of total distance swum underwater (horizontal axis 1) and maximum depth reached (horizontal axis 2). The resultant power envelope was invariant, irrespective of colony location, but penguins from the different colonies tended to use different areas of the envelope. The different colony solutions appeared to represent particular behavioural options for exploiting the available prey and demonstrate how penguins respond to environmental circumstance (prey distribution), the energetic consequences that this has for them, and how this affects the balance of energy acquisition through foraging and expenditure strategy.

Non-nested tests of a GDP-augmented Fama–French model versus a conditional Fama–French model in the Australian stock market

We extend Vassalou (2003) by conditioning the Fama–French model with the same macroeconomic variables used to construct a GDP factor. The motivation for doing so is to ascertain whether the ability of the GDP-augmented model to explain equity returns is actually due to news about future GDP growth or whether it is due to the macroeconomic conditioning variables used to construct the GDP factor. We compare the performance of a GDP-enhanced Fama–French model with the conditional Fama–French model using non-nested testing techniques. We find that the GDP-augmented model considerably underperforms the conditional version of the model.

Stores healthy options project in remote indigenous communities (SHOP@RIC): a protocol of a randomised trial promoting healthy food and beverage purchases through price discounts and in-store nutrition education

Background
Indigenous Australians suffer a disproportionate burden of preventable chronic disease compared to their non-Indigenous counterparts – much of it diet-related. Increasing fruit and vegetable intakes and reducing sugar-sweetened soft-drink consumption can reduce the risk of preventable chronic disease. There is evidence from some general population studies that subsidising healthier foods can modify dietary behaviour. There is little such evidence relating specifically to socio-economically disadvantaged populations, even though dietary behaviour in such populations is arguably more likely to be susceptible to such interventions.

This study aims to assess the impact and cost-effectiveness of a price discount intervention with or without an in-store nutrition education intervention on purchases of fruit, vegetables, water and diet soft-drinks among remote Indigenous communities.

Methods/Design
We will utilise a randomised multiple baseline (stepped wedge) design involving 20 communities in remote Indigenous Australia. The study will be conducted in partnership with two store associations and twenty Indigenous store boards. Communities will be randomised to either i) a 20% price discount on fruit, vegetables, water and diet soft-drinks; or ii) a combined price discount and in-store nutrition education strategy. These interventions will be initiated, at one of five possible time-points, spaced two-months apart. Weekly point-of-sale data will be collected from each community store before, during, and for six months after the six-month intervention period to measure impact on purchasing of discounted food and drinks. Data on physical, social and economic factors influencing weekly store sales will be collected in order to identify important covariates. Intervention fidelity and mediators of behaviour change will also be assessed.

Discussion
This study will provide original evidence on the effectiveness and cost-effectiveness of price discounts with or without an in-store nutrition education intervention on food and drink purchasing among a socio-economically disadvantaged population in a real-life setting.