The relationship between pre-sale price estimates and the hammer price for Australian paintings sold at auction

Realized price for paintings auctioned can systematically differ from prior estimates. We need to understand why experts get it wrong. This paper uses an econometric approach to investigate how pre-sales price estimates are formed and the impact that they have in determining auction prices for Australian paintings.

An empirical study of the world price of sustainability

The core goal of this study is to empirically investigate whether there is a “world price” of corporate sustainability. This is assessed in the context of standard asset pricing models—in particular, by asking whether a risk premium attaches to a sustainability factor after controlling for the Fama–French factors. Both time-series and cross-sectional tests are formulated and applied. The results show that (1) global Fama–French factors have strong power to explain global equity returns and (2) sustainability investments have no significant impact on global equity returns. The absence of a significant relationship between sustainability and returns implies that large institutional investors are free to implement sustainability mandates without fear of breaching their fiduciary duties from realising negative returns due to incorporating a sustainability investment process.

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.

Spatio-temporal analysis of house price convergence based on a demographical distance

Convergences of house prices have been studied for over three decades, but yet have been confirmed because of spatial heterogeneity and autocorrelations in house prices. A spatio-temporal approach was recently proposed to address the spatial and temporal issues related to house prices. However, most previous studies placed the focus on the spatial heterogeneity and autocorrelations from geographical locations, which neglected other spatial factors. In order to overcome this shortfall, this research argued a demographical distance, constructed by demographical structure and housing market scales, to investigate the house price convergences in Australian capital cities. The results confirmed the house price levels in Canberra, Brisbane and Perth converged to the house price level in Sydney.

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.