Price exhaustion and number preference : time and price confluence in Australian stock prices

Confluence occurs when different trading filters generate signals that point to the same directional move. Using regression analysis, this paper investigates confluence trading signals associated with number preference and price exhaustion, for a sample of Australian stocks. The results show that certain price levels tend to act as psychological barriers, and that price exhaustion signals are a real phenomenon in the Australian stock market. It is shown also that confluence exists in the Australian stock market. Importantly, confluence is associated with price retracements that are of economic and statistical significance, offering profitable trading opportunities. The results suggest that Australian stocks do not follow a random walk.

Longitudinal changes in dietary patterns during adult life

Despite the growing interest in dietary patterns, there have been few longitudinal investigations. The objective of the present study was to extend an earlier method of dietary pattern assessment to longitudinal binary data and to assess changes in patterns over time and in relation to socio-demographic covariates. A prospective national cohort of 1265 participants completed a 5 d food diary at three time-points during their adult life (at age 36 years in 1982, 43 years in 1989 and 53 years in 1999). Factor analysis identified three dietary patterns for women (fruit, vegetables and dairy; ethnic foods and alcohol; meat, potatoes and sweet foods) and two patterns in men (ethnic foods and alcohol; mixed). Trends in dietary pattern scores were calculated using random effects models. Marked changes were found in scores for all patterns between 1989 and 1999, with only the meat, potatoes and sweet foods pattern in women recording a decline. In a multiple variable model that included the three time-points, socio-demographic variables and BMI time-dependent covariates, both non-manual social class and higher education level were also strongly associated with the consumption of more items from the ethnic foods and alcohol pattern and the mixed pattern for men (P<0[middle dot]0001) and the fruit, vegetables and dairy pattern and the ethnic foods and alcohol pattern for women (P<0[middle dot]01). In conclusion, longitudinal changes in dietary patterns and across socio-economic groups can assist with targeting public health initiatives by identifying stages during adult life when interventions to improve diet would be most beneficial to health.

Dietary patterns throughout adult life are associated with body mass index, waist circumference, blood pressure, and red cell folate

Dietary patterns are important in the prevention of chronic disease; however, there are few studies that include repeat measures of dietary patterns. The objective of this study was to assess the relations between dietary patterns during adult life (at ages 36, 43, and 53 y) and risk factors for chronic disease at age 53 y. Participants of a longitudinal study of health completed a 5-d food diary at 3 occasions during adult life (n = 1265). Factor analysis was used to identify dietary patterns and a pattern score was calculated from the consumption of the food items in each dietary pattern. Means and 95% CI for dietary pattern scores were calculated for each risk factor category using random effects models adjusted for socio-demographic and health-related behaviors. In women, the fruit, vegetables, and dairy pattern was inversely associated with BMI (P < 0.004), waist circumference (P = 0.0007), blood pressure (P = 0.02), and was positively associated with red cell folate (P < 0.03). The ethnic foods and alcohol pattern was also inversely associated with blood pressure (P = 0.008), whereas the meat, potatoes and sweet foods pattern was positively associated with glycated hemoglobin (P = 0.01). In men, a mixed pattern was inversely associated with waist circumference (P = 0.02) and blood pressure (P = 0.01), whereas there were no significant associations with the ethnic foods and alcohol pattern. Specific dietary patterns throughout adult life were associated with chronic disease risk factors.

Mean reversion in stock prices: new evidence from panel unit root tests

Purpose – There are several studies that investigate evidence for mean reversion in stock prices. However, there is no consensus as to whether stock prices are mean reverting or random walk (unit root) processes. The goal of this paper is to re-examine mean reversion in stock prices.
Design/methodology/approach – The authors use five different panel unit root tests, namely the Im, Pesaran and Shin t-bar test statistic, the Levin and Lin test, the Im, Lee, and Tieslau Lagrangian multiplier test statistic, the seemingly unrelated regression test, and the multivariate augmented Dickey Fuller test advocated by Taylor and Sarno.
Findings – The main finding is that there is no mean reversion of stock prices, consistent with the efficient market hypothesis.
Research limitations/implications – One issue not considered by this study is the role of structural breaks. It may be the case that the efficient market hypothesis is contingent on structural breaks in stock prices. Future studies should model structural breaks.
Practical implications – The findings have implications for econometric modelling, in particular forecasting.
Originality/value – This paper adds to the scarce literature on the mean reverting property of stock prices based on panel data; thus, it should be useful for researchers.

A model of the Australia-US exchange rate

This paper develops a model of exchange rate determination within an error correction framework. The intention is to identify both long and short term determinants that can be used to forecast the AUD/US exchange rate. The paper identifies a set of significant variables associated with exchange rate movements over a twenty year period from 1984 to 2004. Specifically, the overnight interest rate differential, Australia's foreign trade-weighted exposure to commodity prices as well as exchange rate volatility are variables identified that are able explain movements in the AUDIUS dollar relationship. An error correction model is subsequently constructed that incorporates an equilibrium correction term, a short-term interest rate differential variable, a commodity price variable and a proxy for exchange rate volatility. The model is then used to forecast out of sample and is found to dominate a naIve random walk model based on three different metrics.

Is South Korea’s stock market efficient?

This letter applies the Zivot and Andrews (Journal of Business and Economic Statistics, 10, 251-70, 1992) one break and the Lumsdaine and Papell (Review of Economic and Statistics, 79, 212-8, 1997) two break unit root tests to examine the random walk hypothesis for stock prices in South Korea. The results provide strong evidence that stock prices in South Korea are characterized by a unit root, which is consistent with the efficient market hypothesis.

Efficiency, cointegration and contagion in equity markets : evidence from China, Japan and South Korea

This paper empirically examines whether three East Asian stock markets, namely, those of China, Japan and South Korea, are individually and/or jointly efficient, and whether contagion exists between the cointegrated markets. While individual market efficiency is examined through testing for the random walk hypothesis, joint market efficiency is examined through testing for cointegration and contagion. The present study finds that the hypothesis of individual market efficiency is strongly rejected for the Chinese stock market, but not for the Japanese and the South Korean stock markets. However, when testing for cointegration, market efficiency is strongly rejected for all these markets. We take a simple case of contagion and find that although there is a long-term relationship among the three markets, the contagion hypothesis cannot be rejected only between Japanese and South Korean stock markets, indicating short-run portfolio diversification benefits from these two markets.

Effectiveness of interventions to promote physical activity among socioeconomically disadvantaged women : a systematic review and meta-analysis

Physical activity is important for preventing weight gain and obesity, but women experiencing socioeconomic disadvantage are at high risk of inactivity. This study aimed to determine the effectiveness of interventions to increase physical activity among women experiencing disadvantage, and the intervention factors (i.e. physical activity measure, delivery mode, delivery channel, setting, duration, use of theory, behavioural techniques, participant age, risk of bias) associated with effectiveness. We conducted a meta-analysis of controlled trials using random-effects models and meta-regression. Seven databases were searched for trials among healthy women (18–64 years), which included a physical activity intervention, any control group, and statistical analyses of a physical activity outcome at baseline and post-intervention. Nineteen studies were included (n = 6,339). Because of substantial statistical heterogeneity (χ2 = 53.61, df = 18, P < 0.0001, I2 = 66%), an overall pooled effect is not reported. In subgroup analyses, between-group differences were evident for delivery mode, which modestly reduced heterogeneity (to 54%). Studies with a group delivery component had a standardized mean difference of 0.38 greater than either individual or community-based delivery. Programs with a group delivery mode significantly increase physical activity among women experiencing disadvantage, and group delivery should be considered an essential element of physical activity promotion programs targeting this population group.

Measurement error causes scale-dependent threshold erosion of biological signals in animal movement data

Recent advances in telemetry technology have created a wealth of tracking data available for many animal species moving over spatial scales from tens of meters to tens of thousands of kilometers. Increasingly, such data sets are being used for quantitative movement analyses aimed at extracting fundamental biological signals such as optimal searching behavior and scale-dependent foraging decisions. We show here that the location error inherent in various tracking technologies reduces the ability to detect patterns of behavior within movements. Our analyses endeavored to set out a series of initial ground rules for ecologists to help ensure that sampling noise is not misinterpreted as a real biological signal. We simulated animal movement tracks using specialized random walks known as Lévy flights at three spatial scales of investigation: 100-km, 10-km, and 1-km maximum daily step lengths. The locations generated in the simulations were then blurred using known error distributions associated with commonly applied tracking methods: the Global Positioning System (GPS), Argos polar-orbiting satellites, and light-level geolocation. Deviations from the idealized Lévy flight pattern were assessed for each track after incrementing levels of location error were applied at each spatial scale, with additional assessments of the effect of error on scale-dependent movement patterns measured using fractal mean dimension and first-passage time (FPT) analyses. The accuracy of parameter estimation (Lévy μ, fractal mean D, and variance in FPT) declined precipitously at threshold errors relative to each spatial scale. At 100-km maximum daily step lengths, error standard deviations of ≥10 km seriously eroded the biological patterns evident in the simulated tracks, with analogous thresholds at the 10-km and 1-km scales (error SD ≥ 1.3 km and 0.07 km, respectively). Temporal subsampling of the simulated tracks maintained some elements of the biological signals depending on error level and spatial scale. Failure to account for large errors relative to the scale of movement can produce substantial biases in the interpretation of movement patterns. This study provides researchers with a framework for understanding the limitations of their data and identifies how temporal subsampling can help to reduce the influence of spatial error on their conclusions.

Cooperative and competitive structures of trust relations in teams

This article argues that it is not just trust-generating but also trust-inhibiting mechanisms that operate in teams, and that these cooperative and competitive structures of interpersonal relations of trust within teams may affect team performance. Specifically, we propose that the presence of trust-generating structures (e.g., reciprocity, trusting in the referrals of others we trust, trusting in high performers and more experienced people) and the absence of trust-inhibiting structures (e.g., not trusting in the referrals of others we trust) are more likely to be associated with successful teams. Using exponential random graph models, a particular class of statistical model for social networks, we examine three professional sporting teams from the Australian Football League for the presence and absence of these mechanisms of interpersonal relations of trust. Quantitative network results indicate a differential presence of these postulated structures of trust relations in line with our hypotheses. Qualitative comparisons of these quantitative findings with team performance measures suggest a link between trust-generating and trust-inhibiting mechanisms of trust and team performance. Further theorization on other trust-inhibiting structures of trust relations and related empirical work is likely to shed further light on these connections.

An efficient and distributed file search in unstructured peer-to-peer networks

Peer-to-peer (P2P) networks are gaining increased attention from both the scientific community and the larger Internet user community. Data retrieval algorithms lie at the center of P2P networks, and this paper addresses the problem of efficiently searching for files in unstructured P2P systems. We propose an Improved Adaptive Probabilistic Search (IAPS) algorithm that is fully distributed and bandwidth efficient. IAPS uses ant-colony optimization and takes file types into consideration in order to search for file container nodes with a high probability of success. We have performed extensive simulations to study the performance of IAPS, and we compare it with the Random Walk and Adaptive Probabilistic Search algorithms. Our experimental results show that IAPS achieves high success rates, high response rates, and significant message reduction.

Engineering a distributed infrastructure for large-scale cost-effective content dissemination over urban vehicular networks

This paper proposes a practical and cost-effective approach to construct a fully distributed roadside communication infrastructure to facilitate the localized content dissemination to vehicles in the urban area. The proposed infrastructure is composed of distributed lightweight low-cost devices called roadside buffers (RSBs), where each RSB has the limited buffer storage and is able to transmit wirelessly the cached contents to fast-moving vehicles. To enable the distributed RSBs working toward the global optimal performance (e.g., minimal average file download delays), we propose a fully distributed algorithm to determine optimally the content replication strategy at RSBs. Specifically, we first develop a generic analytical model to evaluate the download delay of files, given the probability density of file distribution at RSBs. Then, we formulate the RSB content replication process as an optimization problem and devise a fully distributed content replication scheme accordingly to enable vehicles to recommend intelligently the desirable content files to RSBs. The proposed infrastructure is designed to optimize the global network utility, which accounts for the integrated download experience of users and the download demands of files. Using extensive simulations, we validate the effectiveness of the proposed infrastructure and show that the proposed distributed protocol can approach to the optimal performance and can significantly outperform the traditional heuristics.

External shocks and tourist arrivals to Cambodia

This article investigates how external shocks affect tourist arrivals to Cambodia. The study relies on the random walk approach to test whether the shocks to tourist arrivals are temporary or persistent in nature. To facilitate the empirical investigation, the study applies and compares the results from different unit root tests and variance-ratio tests to the monthly tourists' arrival data from 1994 to December 2012. Both tests provide evidence of random walk hypothesis, implying that shocks to tourists' arrival to Cambodia have a persistent effect requiring short- to medium-term policies to combat the vulnerability due to those shocks. Public-private coordinated policies could reduce the impact, as we found that once the crisis (external shocks) is minimized, the magnitude of the shocks decays slowly.