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This note is concerned with the study of temporal development in several indices reflecting clustering effects in multilevel designs that are frequently utilized in educational and behavioral research. A latent variable method-based approach is outlined, which can be used to point and interval estimate the growth or decline in important functions of level-specific variances in two-level and three-level settings. The procedure may also be employed for the purpose of examining stability over time in clustering effects. The method can be utilized with widely circulated latent variable modeling software, and is illustrated using empirical examples. [ABSTRACT FROM AUTHOR]

Meta-analyses traditionally compare the difference in means between groups for one or more outcomes of interest. However, they do not compare the spread of data (variability), which could mean that important effects and/or subgroups are missed. To address this, methods to compare variability meta-analytically have recently been developed, making it timely to review them and consider their strengths, weaknesses, and implementation. Using published data from trials in major depression, we demonstrate how the spread of data can impact both overall effect size and the frequency of extreme observations within studies, with potentially important implications for conclusions of meta-analyses, such as the clinical significance of findings. We then describe two methods for assessing group differences in variability meta-analytically: the variance ratio (VR) and coefficient of variation ratio (CVR). We consider the reporting and interpretation of these measures and how they differ from the assessment of heterogeneity between studies. We propose general benchmarks as a guideline for interpreting VR and CVR effects as small, medium, or large. Finally, we discuss some important limitations and practical considerations of VR and CVR and consider the value of integrating variability measures into meta-analyses. [ABSTRACT FROM AUTHOR]

Weak-form efficiency means that stock prices should reflect all historical information and follow a random walk. This study examines the effect of the COVID-19 pandemic on the stock market weak-form efficiency of Arab countries, namely, Jordan, Lebanon, Kuwait, Morocco, Oman, Palestine, Bahrain, Egypt, Iraq, Qatar, Saudi Arabia, the United Arab Emirates, Syria, Tunisia, and Sudan. Daily data from July 1st, 2021 to November 12th, 2022 (370 trading days) are used to cover the period after starting the pandemic. The variance ratio and the runs test are used to test return predictability. The results show that the variance ratio values of Boursa Kuwait, the Egyptian Exchange, Tadawul, and the Amman Stock Exchange are statistically significant, indicating that their returns are unpredictable. In specific, the indices of these stock markets follow a random walk, and their price changes are independent. This is evidence that these stock markets are efficient at a weak level. In contrast, the insignificant values of the variance ratio indicate that returns are predictable in other Arab stock exchanges after the pandemic era. The findings of the Egyptian Exchange, Tadawul, and the Amman Stock Exchange are confirmed using the run test of weak-form efficiency. It reveals that the indices of these stock exchanges follow a random walk, while the indices of other Arab stock markets do not.

We investigated the population of Lithocarpus glaucus, an endangered plant species, within the provincial nature reserve E’huangzhang, Yangchun, Guangdong, to enhance their monitoring and conservation efforts. Employing ecological niche measurements, variance ratio analysis, χ² tests, and a combination of Pearson′s and Spearman′s rank correlation coefficients, we comprehensively analyzed the ecological niches and interspecific interactions among 31 dominant tree species in the L. glaucus community. Our findings reveal that L. glaucus ranks seconds in importance, after Homalium cochinchinense, with a significantly wide ecological niche. Among the 30 pairs of tree species combinations involving L. glaucus, the niche similarity ratios of 25 pairs were over 0.50, and the niche overlap values of 26 pairs were over 0.50, indicating high ecological similarity and overlap among the dominant species, suggesting potential competition in a resource scarce environment. Overall, the 31 dominant tree species exhibit significant positive associations, indicating that the L. glaucus community is in a relatively mature successional stage. The results of the χ² test as well as Pearson′s and Spearman′s rank correlation coefficients show that the interspecific associations among dominant canopy species are relatively weak, suggesting independent distribution patterns. In summary, the L. glaucus community is currently in a late successional stage, utilizing resources efficiently, with weak interspecific correlations and potential competitive risks. The L. glaucus population thrives in environments free from human disturbances, demonstrating strong survival potential. To enhance their recovery and growth, we recommend increasing light intensity within the forest, selectively removing dead or wind-felled trees, and managing species population sizes with significant negative associations to optimize the growth environment. [ABSTRACT FROM AUTHOR]

We show that three prominent consumption-based asset pricing models—the Bansal–Yaron, Campbell–Cochrane and Cecchetti–Lam–Mark models—cannot explain the dynamic properties of stock market returns. We show this by estimating these models with GMM, deriving ex-ante expected returns from them and then testing whether the difference between realised and expected returns is a martingale difference sequence, which it is not. Mincer–Zarnowitz regressions show that the models' out-of-sample expected returns are systematically biased. Furthermore, semi-parametric tests of whether the models' state variables are consistent with the degree of own-history predictability in stock returns suggest that only the Campbell–Cochrane habit variable may be able to explain return predictability, although the evidence on this is mixed. [ABSTRACT FROM AUTHOR]

In this article, we propose new semiparametric and bootstrap tests based on the ratio of two variances under a density ratio model and compare them with existing tests for testing the equality of two variances from two independent populations. We showed that the ratio of two independent variances follows an asymptotic log-normal distribution. Also presented in this article are large sample asymptotic results of the semiparametric estimator of the ratio of the two sample variances. We also present a theoretical comparison of our semiparametric test on the ratio of two variances with the existing non parametric test using Pitman's relative efficiency. Numerical comparisons of the performance of various tests are performed via simulation studies. We also use two numerical examples to illustrate the implementation of new tests. [ABSTRACT FROM AUTHOR]

This paper presents a new non-parametric seasonal unit root testing framework that is robust to periodic non-stationary volatility in innovation variance by making an extension to the fractional seasonal variance ratio unit root tests of Eroğlu et al. (Econ Lett 167:75–80, 2018). The setup allows for both periodic heteroskedasticity structure of Burridge and Taylar (J Econ 104(1):91–117, 2001) and non-stationary volatility structure of Cavaliere and Taylor (Econ Theory 24(1):43-71, 2008). We show that the limiting null distributions of the variance ratio tests depend on nuisance parameters derived from the underlying volatility process. Monte Carlo simulations show that the standard variance ratio tests can be substantially oversized in the presence of such effects. Consequently, we propose wild bootstrap implementations of the variance ratio tests. Wild bootstrap resampling schemes are shown to deliver asymptotically pivotal inference. The simulation evidence depicts that the proposed bootstrap tests perform well in practice and essentially correct the size problems observed in the standard fractional seasonal variance ratio tests, even under extreme patterns of heteroskedasticity. [ABSTRACT FROM AUTHOR]

Objective: Traditional finance emphasises market efficiency and inherent behavioural anomalies in investors. However, the emergence of the adaptive market hypothesis tends to suggest otherwise. The adaptive market hypothesis challenges market efficiency and behavioural finance by contesting that investors and market participants adapt to changing market environment. In essence, investors learn from their mistakes. The purpose of this study was to explore the concept of an adaptive market hypothesis in five international markets, namely, the JSE, CAC 40, NASDAQ, JPX-NIKKEI and DAX. Method: This study used a variance ratio test to explore the adaptive market hypothesis from January 2017 to April 2022. Results: the findings revealed the existence of adaptive markets in the CAC 40 and NASDAQ during the period under review. Conversely, there was no statistical evidence to support the adaptive concept in the JSE, JPX-NIKKEI, and the DAX. Originality/relevance: The implications of these findings is that investors in the CAC 40 and NASDAQ should consider active volatility scaling because of multiple betas, and hence fundamental analysis is worth the time. This study adds to the literature on adaptive markets hypothesis as well as market efficiency and behavioural finance. Keywords: Adaptive markets; market efficiency; behavioural finance; financial markets; variance ratio

Copyright of Journal of Academic Finance is the property of Academic Finance Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Early warning systems are too important tools in predicting the crisis in financial institutions say banks and stock markets. A consequence of crashes in a specified stock or stock market is financial crisis. This paper considers designing an early warning system based on random walk theory and maximal inequality. First, mathematical tools are presented, and the early warning system is designed, then some real data sets are analysed. The performance of system is evaluated by some different criteria. After it, using a dynamic programming approach, a modified version of mentioned early warning system is proposed. Finally, a conclusion section is given.

A meta-analytic approach was used to explore sex differences in within-sex variation across different versions of the Wechsler Intelligence Scale for Children (WISC). Mean sex differences and variance ratios (VRs) were obtained from 75 studies that included 124 independent samples, 571 effect sizes. The outcomes included full scale IQ, individual subtests, and composite indices based on the Cattell-Horn-Carroll ability model (e.g., visual processing, g V, and crystallized intelligence, g C). Although males were more variable in several domains (e.g., g V, g C), females were more variable for processing speed (g S), and there were no VR differences for still other domains (e.g., short-term verbal memory). The cross-domain differences in VRs were linearly related to the magnitude of mean sex differences, suggesting that the sex with the advantage at the mean is often the more variable sex. A theoretical model that accounts for this pattern is proposed. [ABSTRACT FROM AUTHOR]

Synchronous dynamics (fluctuations that occur in unison) are universal phenomena with widespread implications for ecological stability. Synchronous dynamics can amplify the destabilizing effect of environmental variability on ecosystem functions such as productivity, whereas the inverse, compensatory dynamics, can stabilize function. Here we combine simulation and empirical analyses to elucidate mechanisms that underlie patterns of synchronous versus compensatory dynamics. In both simulated and empirical communities, we show that synchronous and compensatory dynamics are not mutually exclusive but instead can vary by timescale. Our simulations identify multiple mechanisms that can generate timescale‐specific patterns, including different environmental drivers, diverse life histories, dispersal, and non‐stationary dynamics. We find that traditional metrics for quantifying synchronous dynamics are often biased toward long‐term drivers and may miss the importance of short‐term drivers. Our findings indicate key mechanisms to consider when assessing synchronous versus compensatory dynamics and our approach provides a pathway for disentangling these dynamics in natural systems. [ABSTRACT FROM AUTHOR]

The presence of the stock market has helped boost economic growth in Indonesia. However, high levels of volatility plus economic uncertainty make investors need to carry out strategies in investing in the capital market. This study aims to analyze the index movement of each industry sector on the stock exchange in Indonesia by testing the Efficient Market Hypothesis and estimating the growth of returns for each industrial sector. This research uses monthly data from 1996 to 2020 with research methods including variance ratios, data stationarity test, Autoregressive Integrated Moving Average (ARIMA), and Autoregressive Conditional Heteroskedasticity (ARCH). The results showed that the industrial sector on the Indonesia Stock Exchange was inefficient in its weak form. In forecasting, almost all indices experience a contraction of growth at the beginning of the forecasting period. Stakeholders are expected to be more active in the market by buying and selling, especially the contraction of shares. The market has proven to be inefficient in its weak form.

We prove that the Behrens–Fisher statistic follows a Student bridge distribution, the mixing coefficient of which depends on the two sample variances only through their ratio. To this end, it is first shown that a weighted sum of two independent normalized chi-square distributed random variables is chi-square bridge distributed, and secondly that the Behrens–Fisher statistic is based on such a variable and a standard normally distributed one that is independent of the former. In case of a known variance ratio, exact standard statistical testing and confidence estimation methods apply without the need for any additional approximations. In addition, a three pillar bridges explanation is given for the choice of degrees of freedom in Welch’s approximation to the exact distribution of the Behrens–Fisher statistic.

We aimed to explore the interspecific association of the main tree populations of a natural Cryptomeria fortunei community in the Tianbaoyan Nature Reserve, and reveal the interspecific relationship and succession trend of the Cryptomeria fortunei community. The main tree populations with the top 15 important values of a Cryptomeria fortunei community were selected as the research object. The variance ratio (RV), χ² test, association coefficient (CA), percentage co-occurrence (PC), and point correlation coefficient (CPC) were used to analyze and determine the interspecific associations, and classify the ecological species groups. The results showed that there were no significant negative associations among the 15 main tree populations of the Cryptomeria fortunei community in the Tianbaoyan Nature Reserve, the interspecific associations were low, and all groups tended to distribute independently. The χ² test results showed that among the 105 species pairs, 46 were positively associated and 59 were negatively associated, with a positive/negative association ratio of 0.78; and 75 were not significantly associated, accounting for 71.4%. The results of CA, PC, and CPC all show that the various groups are mostly insignificantly associated, with greater randomness, inconsistent habitat requirements, and a low probability of co-occurrence of species. Based on the results of species cluster analysis, interspecific association analysis, and ecological habits, the 15 main populations of the Cryptomeria fortunei community were divided into three ecological species groups. Species within the same group had similar ecological habits and resource needs, and the species pairs were interdependent and coexisted with mostly positive associations, while the species in different ecological groups were mostly negative associations. Therefore, to protect Cryptomeria fortunei natural forests, the species with positive correlations should be selected as the main species for the renewal of the Cryptomeria fortunei natural community to increase community diversity, reduce human disturbance, and promote the stability of the community. [ABSTRACT FROM AUTHOR]

Synchrony among population fluctuations of multiple coexisting species has a major impact on community stability, i.e. on the relative temporal constancy of aggregate properties such as total community biomass. However, synchrony and its impacts are usually measured using covariance methods, which do not account for whether species abundances may be more correlated when species are relatively common than when they are scarce, or vice versa. Recent work showed that species commonly exhibit such 'asymmetric tail associations'. We here consider the influence of asymmetric tail associations on community stability. We develop a 'skewness ratio' which quantifies how much species relationships and tail associations modify stability. The skewness ratio complements the classic variance ratio and related metrics. Using multi-decadal grassland datasets, we show that accounting for tail associations gives new viewpoints on synchrony and stability; e.g. species associations can alter community stability differentially for community crashes or explosions to high values, a fact not previously detectable. Species associations can mitigate explosions of community abundance to high values, increasing one aspect of stability, while simultaneously exacerbating crashes to low values, decreasing another aspect of stability; or vice versa. Our work initiates a new, more flexible paradigm for exploring species relationships and community stability. This article is part of the theme issue 'Synchrony and rhythm interaction: from the brain to behavioural ecology'. [ABSTRACT FROM AUTHOR]

This article introduces a new unit root test that combines the variance ratio framework with the Flexible Fourier Form under the generalized least squares detrending mechanism. The advantage of the proposed method against its alternatives can be listed as: (1) it suggests a non-parametric procedure that does not require any parametric or semi-parametric model to remove serial correlation in the innovation process; (2) it can reasonably adapt itself to deal with the multiple structural breaks with various functional specifications. In the simulation exercises, we show that the proposed method exhibits satisfactory performance in the size and size-adjusted power analysis. [ABSTRACT FROM AUTHOR]

We study the informational efficiency of the Saudi stock market (SSM), while accounting for corporate governance change, based on single, multiple, and variance ratio-based WALD tests and runs test. The main findings indicate that when the whole period is considered, the random walk hypothesis is rejected, but when divided into two sub-periods separated by the pre-corporate governance and the period marked by corporate governance change, the analysis demonstrates sub-period improvement in weak-form efficiency for the examined series. Robustness of results is verified by analysis using sector indices, which point to market efficiency. Interestingly, Hurst Exponent estimates evidence long-range dependence which suggests the predictability of stock prices and the prospect of speculative opportunities. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Economics & Finance (2437-0630) is the property of Association of Arab Universities and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Asymptotically correct simultaneous confidence bands (SCBs) are proposed in both multiplicative and additive form to compare variance functions of two samples in the nonparametric regression model based on deterministic designs. The multiplicative SCB is based on two-step estimation of ratio of the variance functions, which is as efficient, up to order n - 1 / 2 , as an infeasible estimator if the two mean functions are known a priori. The additive SCB, which is the log transform of the multiplicative SCB, is location and scale invariant in the sense that the width of SCB is free of the unknown mean and variance functions of both samples. Simulation experiments provide strong evidence that corroborates the asymptotic theory. The proposed SCBs are used to analyze several strata pressure data sets from the Bullianta Coal Mine in Erdos City, Inner Mongolia, China. [ABSTRACT FROM AUTHOR]

Early warning systems are too important tools in predicting the crisis in financial institutions say banks and stock markets. A consequence of crashes in a specified stock or stock market is financial crisis. This paper considers designing an early warning system based on random walk theory and maximal inequality. First, mathematical tools are presented, and the early warning system is designed, then some real data sets are analysed. The performance of system is evaluated by some different criteria. After it, using a dynamic programming approach, a modified version of mentioned early warning system is proposed. Finally, a conclusion section is given. [ABSTRACT FROM AUTHOR]

Abstract Color modification is one of the popular image forgery techniques. It can be used to eliminate criminal evidence in various ways, such as modifying the color of a car used in a crime. If the color of a digital image is modified, the locations of the interpolated and original samples may be changed. Because the original and interpolated pixels have different statistical characteristics, these differences can serve as a basic clue for estimating the degree of color modification. It is assumed that the variance of original samples is greater than that of the interpolated samples. Therefore, we present a novel algorithm for color modification estimation using the variance ratio of color difference images in the wavelet domain. The color difference model is used to emphasize the differences between the original and interpolated samples. For color difference images, we execute a wavelet transform and use the highest frequency subband to calculate variances. We define a variance ratio measurement to quantify the level of color modification. Additionally, changed color local regions can be efficiently detected using the proposed algorithm. Experimental results demonstrate that the proposed method generates accurate estimation results for detecting color modification. Compared to the conventional method, our method provides superior color modification detection performance.

Resiliency provides fundamental insights on the speed at which the marginal price impact increases as transaction volume increases in the stock market yet very few empirical research has been dedicated to its study. Consequently, this study was directed towards determining whether market resiliency is a predicator of economic growth. Secondly, the study also sought to examine whether real interest rate and risk premium moderate the relationship between stock market resiliency and the economic growth in Kenya. To solve the conundrum on the relationship between market resiliency and economic resiliency growth, a sagacious moderating regression analysis (MRA) was used. The liquidity and variance ratios were used as measures of resiliency while real interest rate and risk premium were taken as moderating variables. The CUSUM plots were used to determine the stability of the model. The results of this study shows that market resiliency is a predicator of economic growth and both real interest rates and risk premium moderates the relationship between stock market resilience and the economic growth in Kenya.

Meta‐analysis is increasingly used in biology to both quantitatively summarize available evidence for specific questions and generate new hypotheses. Although this powerful tool has mostly been deployed to study mean effects, there is untapped potential to study effects on (trait) variance. Here, we use a recently published data set as a case study to demonstrate how meta‐analysis of variance can be used to provide insights into biological processes. This data set included 704 effect sizes from 89 studies, covering 56 animal species, and was originally used to test developmental stress effects on a range of traits. We found that developmental stress not only negatively affects mean trait values, but also increases trait variance, mostly in reproduction, showcasing how meta‐analysis of variance can reveal previously overlooked effects. Furthermore, we show how meta‐analysis of variance can be used as a tool to help meta‐analysts make informed methodological decisions, even when the primary focus is on mean effects. We provide all data and comprehensive R scripts with detailed explanations to make it easier for researchers to conduct this type of analysis. We encourage meta‐analysts in all disciplines to move beyond the world of means and start unravelling secrets of the world of variance. [ABSTRACT FROM AUTHOR]

The equality of two group variances is frequently tested in experiments. However, criticisms of null hypothesis statistical testing on means have recently arisen and there is interest in other types of statistical tests of hypotheses, such as superiority/non‐inferiority and equivalence. Although these tests have become more common in psychology and social sciences, the corresponding sample size estimation for these tests is rarely discussed, especially when the sampling unit costs are unequal or group sizes are unequal for two groups. Thus, for finding optimal sample size, the present study derived an initial allocation by approximating the percentiles of an F distribution with the percentiles of the standard normal distribution and used the exhaustion algorithm to select the best combination of group sizes, thereby ensuring the resulting power reaches the designated level and is maximal with a minimal total cost. In this manner, optimization of sample size planning is achieved. The proposed sample size determination has a wide range of applications and is efficient in terms of Type I errors and statistical power in simulations. Finally, an illustrative example from a report by the Health Survey for England, 1995–1997, is presented using hypertension data. For ease of application, four R Shiny apps are provided and benchmarks for setting equivalence margins are suggested. [ABSTRACT FROM AUTHOR]

Understanding the mechanisms governing ecological stability—why a property such as primary productivity is stable in some communities and variable in others—has long been a focus of ecology. Compensatory dynamics, in which anti‐synchronous fluctuations between populations buffer against fluctuations at the community level, are a key theoretical mechanism of stability. Classically, compensatory dynamics have been quantified using a variance ratio approach that compares the ratio between community variance and aggregate population variance, such that a lower ratio indicates compensation and a higher ratio indicates synchrony among species fluctuations. However, population dynamics may be influenced by different drivers that operate on different timescales, and evidence from aquatic systems indicates that communities can be compensatory on some timescales and synchronous on others. The variance ratio and related metrics cannot reflect this timescale specificity, yet have remained popular, especially in terrestrial systems. Here, we develop a timescale‐specific variance ratio approach that formally decomposes the classical variance ratio according to the timescales of distinct contributions. The approach is implemented in a new R package, called tsvr, that accompanies this paper. We apply our approach to a long‐term, multisite grassland community dataset. Our approach demonstrates that the degree of compensation vs. synchrony in community dynamics can vary by timescale. Across sites, population variability was typically greater over longer compared to shorter timescales. At some sites, minimal timescale specificity in compensatory dynamics translated this pattern of population variability into a similar pattern of greater community variability on longer compared to shorter timescales. But at other sites, differentially stronger compensatory dynamics at longer compared to shorter timescales produced lower‐than‐expected community variability on longer timescales. Within every site, there were plots that exhibited shifts in the strength of compensation between timescales. Our results highlight that compensatory vs. synchronous dynamics are intrinsically timescale‐dependent concepts, and our timescale‐specific variance ratio provides a metric to quantify timescale specificity and relate it back to the classic variance ratio. [ABSTRACT FROM AUTHOR]

This paper examines the impact of time averaging and interval sampling data assuming that the data generating process for a given series follows a random walk with iid errors. We provide exact expressions for the corresponding variances, and covariances, for both levels and higher order differences of the aggregated series, as well as that for the variance ratio, demonstrating exactly how the degree of temporal aggregation impacts these properties. We empirically investigate this issue on exchange rates and find that the values of the variance ratios and autocorrelation coefficients at different frequencies are consistent with our theoretical results. We also conduct a simulation exercise that illustrates the potential effect that conditional heteroskedasticity and fat tails may have on the temporal aggregation of a random walk and of a highly persistent autoregressive process. [ABSTRACT FROM AUTHOR]

Abstract Background Within- and between-person variation in nutrient intake is well established, but little is known about variability in dietary flavonoid intake, including the effect of seasonality. Methods Within- and between-individual variability of flavonoid intake, and intake of flavonoid subclasses was examined in older adults (n = 79; mean age 70.1 y (range: 60y-80y)), using three separate 4-day weighed food records (WFR) collected approximately 4 months apart. The effects of seasonality were also examined. Mixed-effects linear regression models were used to estimate within- and between-individual variance components for flavonoids and subclasses. The number of days of dietary assessment required for a high level of hypothetical accuracy was calculated from variance ratios. Results Within- and between-individual variability was high for flavonoid intake, and intake of flavonoid subclasses, with variance ratios > 1. It was calculated that six days of WFR data are required for total flavonoid intake, and between 6 and 10 days was required for flavonoid subclasses. There was no effect of seasonality for total flavonoid intake or intake of flavonoid subclasses, with the exception that flavan-3-ol and flavanone intakes which were relatively low in summer, and in summer and winter, respectively. Conclusion While the effects of seasonality on total flavonoid intake may be small, within- and between-individual variation associated with flavonoid intake assessment appears to be substantial across 12 days of WFR data in older adults. It is recommended that a minimum of 6 days of weighed food records are collected to minimise the impact of within- and between-individual variability on total flavonoid intake assessments in this population.

Abstract Background China has undergone a rapid demographic and epidemiological transition with fast ecomonic development since the 1980s. Oral health is becoming a major public health problem as the prevalence of non-communicable diseases has greatly increased. Periodontal disease (PD) and caries are among the most prevalent oral diseases. PD accounts for the majority of tooth loss and increases with age. China’s third national epidemiological investigation on oral diseases (2005) revealed that periodontitis affected >50% of the adult population. The Global Burden of Disease Study 2013 (GBD2013) have been used to estimate DALYs for 301 acute and chronic diseases and injuries in 188 countries for 1990–2013. The estimation of burden of PD between 1990 and 2013 will provide a unique perspective for planning interventions and developing public health policies for PD even chronic diseases in China. Methods We used the GBD 2013 results for Years of Life Lost (YLLs) and Years Lived with Disability (YLDs) to calculate Disability Adjusted Life Years (DALYs) for PD in China. PD standardized DALYs rate (SDR) per 100,000 persons, the percentage of PD standardized DALYs rate (% PD SDR) in all diseases DALYs, and variance ratio of these two indexes between the years of 1990 and 2013 were compared by province, gender and age groups. Results Nationwide, compared to 1990, the SDR in 2013 increased slightly from 24.7 to 25.7, while the variance ratio of SDR for provinces in the middle, west and south of China showed a greater variation(4.8–6.2%). The % PD SDR in all disease DALYs increased from 0.06 to 0.11% for all groups. The four highest variance ratios % PD SDR in all diseases DALYs between 1990 and 2013 occurred in the west of China (97, 98.6, 108.4 and 112.8%). The PD SDR changed slightly in the women (20.3 to 21.7), meanwhile the variance ratio of PD SDR and % PD SDR in all diseases DALYs for the women (6.7 and 94.5%) was also higher than for men (2.1 and 60.6%). The highest variance ratio % PD SDR in all oral diseases DALYs occurred between 1990 and 2013 in ages 20 to 24 (50.7%) and 25 to 29 years (50.5%). Conclusion The PD standardized DALYs rate and % PD SDR in all diseases DALYs in China in 2013 has increased from 1990. Especially, the variance ratio of % PD SDR in all disease DALYs among Young population and women, in the west provinces of China have been becoming the highest in all age groups and national wide. Future intervention measurements should include young women of child-bearing age because women’s health impacts infant health. Periodontal disease has risk factors in common with a number of other non-communicable diseases (NCD) and conditions, and focusing on the common behavioral and environmental risk factors would be instrumental in the effective prevention of periodontal disease.

This study is based on pragmatic creations to make the hypothetical frame focusing on behavioral finance pattern for finding the sagacity of investors, stock returns, and effectiveness of stock market performance. The research investigates an extensive extent of Pakistan stock market Returns data from June 1994 to December 2018 along with the two economic segments including the Military phase (1999-2008) and Democratic phase (1994-1998) (2009-2018) to determine the Pakistan Stock market efficiency. To this end, autocorrelation and variance ratio tests were performed on the returns (weekly based) KSE 100 index during overall period as well as for both the Military Phase and the Democratic phase using adaptive pattern of market competence. The weak efficiency tests show trends of a stock performance, and consequently developing of bounded-adaptive market effectiveness. These tests recognized the presence of asymmetric dynamic behavior of returns obviousness in calculation of risk and return associations during two political states. These confirmations offer provision to investors bounded adaptive rationality, behavior, vigorous behavior of stock return and as a result establishing effectiveness of bounded adaptive market. [ABSTRACT FROM AUTHOR]

A hedging approach is used to examine the effectiveness of international diversification within the Gulf Co-operation Council (GCC) region. By using data covering the six GCC countries (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and UAE) and various sectors, we find that diversification across whole markets is more effective than diversification across sectors, irrespective of whether the constructed portfolios contain two or more assets. The results also reveal that diversification among several markets or sectors is more effective than diversification among two markets or sectors. [ABSTRACT FROM AUTHOR]

We propose a class of ratio tests that is applicable whenever a cumulation (of transformed) data is asymptotically normal upon appropriate normalization. The Karhunen–Loève theorem is employed to compute weighted averages. The test statistics are ratios of quadratic forms of these averages and hence scale-invariant, also called self-normalizing: The scaling parameter cancels asymptotically. Limiting distributions are obtained. Critical values and asymptotic local power functions can be calculated by standard numerical means. The ratio tests are directed against local alternatives and turn out to be almost as powerful as optimal competitors, without being plagued by nuisance parameters at the same time. Also in finite samples they perform well relative to self-normalizing competitors. [ABSTRACT FROM AUTHOR]

Building on recent and growing evidence that geographic location influences information diffusion, this paper examines the relation between firm's location and the predictability of stock returns. We hypothesize that returns on a portfolio composed of firms located in central areas are more likely to follow a random walk than returns on a portfolio composed of firms located in remote areas. Using a battery of variance ratio tests, we find strong and robust support for our prediction. In particular, we show that the returns on a portfolio composed of the 500 largest urban firms follow a random walk; however, all variance ratio tests reject the random walk hypothesis for a portfolio that includes the 500 largest rural firms. Our results are robust to alternative definitions of firm's location and portfolio formation. [ABSTRACT FROM AUTHOR]

Options trading can stimulate price efficiency in underlying stock markets by providing a platform for informed trades, increasing the production of information, and mitigating momentum arbitrage strategies and short-sale constraints. Using a large sample of 8146 firms with option trading from 1996 through 2014, this study examines the extent to which liquidity in option markets relates to the ability for stock prices to reflect all publicly available information. Variance ratio tests document that price efficiency monotonically increases across relative option liquidity deciles, proxied by the option-to-stock volume ratio, progressively becoming closer to random walk benchmarks. Evidence suggests that enhanced price efficiency is pronounced among small company stocks. [ABSTRACT FROM AUTHOR]

The rapid advance of information and communication technology (ICT) has revolutionized the dissemination of stock market information. Based on the noise trading theory, this study discusses whether the changes brought by ICT have promoted the transparency of stock market information or instead flooded the stock market with misinformation. A cross‐country panel dataset of 71 countries from 2002 to 2014 was established. The empirical methodologies include panel unit root tests, panel variance ratio tests, and panel multiple regressions. The results of panel unit root tests and panel variance ratio tests show that stock markets in countries with high ICT diffusion are efficient while stock markets in countries with low or medium ICT diffusion are not all efficient. The results of panel regressions further show that the effect of ICT diffusion in reducing market noises was more significant than its effect in magnifying the noises. [ABSTRACT FROM AUTHOR]

Many seed quality tests are conducted by first randomly assigning seeds into replicates of a given size. The replicate results are then used to check whether or not any problems occur in the realization of the test. The two main tools developed for this verification are the ratio of the observed variance of the replicate results to a theoretical variance and the tolerance for the range of the results. In this paper, we derive the theoretical distribution and its related properties of the sequence of numbers of seeds with a given quality attribute present in the replicates. From these theoretical results, we revisit the two quality checking tools widely used for the germination test. We show a precaution to be taken when relying on the variance ratio to check for under- or over-dispersion of the replicate results. This has led to the development of tables providing credible intervals of the variance ratio. The International Seed Testing Association tolerance tables for the range of the results are also compared with tolerances computed from the exact theoretical distribution of the range, leading us to recommend a revision of these tables. [ABSTRACT FROM AUTHOR]

This paper investigates the random walk behavior of real estate investment trust (REIT) subsectors using monthly return data from January 1994 to July 2015. Using variance ratio tests, we examine subsectors of lodging/resorts and self-storage and find that they do not follow a random walk, contradicting the weak-form efficient market hypothesis. Non-parametric runs tests help us find that office, industrial, mixed, free standing, shopping centers, apartments, manufactured homes, and timberland subsectors are weak-form efficient. The evidence in this study supports the idea that some subsec-tors are more informationally efficient than other subsectors.

This article is concerned with feature screening for the ultrahigh dimensional discriminant analysis. A variance ratio screening method is proposed and the sure screening property of this screening procedure is proved. The proposed method has some additional desirable features. First, it is model-free which does not require specific discriminant model and can be directly applied to the multi-categories situation. Second, it can effectively screen main effects and interaction effects simultaneously. Third, it is relatively inexpensive in computational cost because of the simple structure. The finite sample properties are performed through the Monte Carlo simulation studies and two real-data analyses. [ABSTRACT FROM AUTHOR]

Inconsistencies in the research findings on F-test robustness to variance heterogeneity could be related to the lack of a standard criterion to assess robustness or to the different measures used to quantify heterogeneity. In the present paper we use Monte Carlo simulation to systematically examine the Type I error rate of F-test under heterogeneity. One-way, balanced, and unbalanced designs with monotonic patterns of variance were considered. Variance ratio (VR) was used as a measure of heterogeneity (1.5, 1.6, 1.7, 1.8, 2, 3, 5, and 9), the coefficient of sample size variation as a measure of inequality between group sizes (0.16, 0.33, and 0.50), and the correlation between variance and group size as an indicator of the pairing between them (1,.50, 0, −.50, and −1). Overall, the results suggest that in terms of Type I error a VR above 1.5 may be established as a rule of thumb for considering a potential threat to F-test robustness under heterogeneity with unequal sample sizes. [ABSTRACT FROM AUTHOR]

Chatter occurs as an unexpected and unstable phenomenon in milling process, imposing an extremely negative effect on the workpiece and machining system. Therefore, a method that can identify chatter at an early stage is desperately needed. However, some aspects in terms of effectiveness, robustness, and practicality with existing methods deserve further improvement. In this paper, the characteristics of chatter in different stages are investigated. Considering the properties of a vibration signal when the onset of chatter occurs, an adaptive filter is designed to remove the spindle speed-related frequency components, and the chatter-related components can be amplified simultaneously with the filter. Next, the variance ratio (VR) of the filtered signal series to the original signal series is defined as the chatter indicator, which is very sensitive to chatter. After chatter is detected, a time frequency analysis method based on ensemble empirical mode decomposition (EEMD) and the Hilbert-Huang transform (HHT) is introduced to estimate the dominant chatter frequency. Milling experiments with different configurations of cutting conditions are performed and the results show that all the chatter can be detected at an early stage. In addition, the transients of the vibration signal caused by discontinuity of workpiece geometry or inhomogeneous material can be distinguished from the chatter. [ABSTRACT FROM AUTHOR]

This paper investigates the random walk behavior of real estate investment trust (REIT) subsectors using monthly return data from January 1994 to July 2015. Using variance ratio tests, we examine subsectors of lodging/resorts and self-storage and find that they do not follow a random walk, contradicting the weak-form efficient market hypothesis. Nonparametric runs tests help us find that office, industrial, mixed, free standing, shopping centers, apartments, manufactured homes, and timberland subsectors are weak-form efficient. The evidence in this study supports the idea that some subsectors are more informationally efficient than other subsectors. [ABSTRACT FROM AUTHOR]

Background: Within- and between-person variation in nutrient intake is well established, but little is known about variability in dietary flavonoid intake, including the effect of seasonality.Methods: Within- and between-individual variability of flavonoid intake, and intake of flavonoid subclasses was examined in older adults (n = 79; mean age 70.1 y (range: 60y-80y)), using three separate 4-day weighed food records (WFR) collected approximately 4 months apart. The effects of seasonality were also examined. Mixed-effects linear regression models were used to estimate within- and between-individual variance components for flavonoids and subclasses. The number of days of dietary assessment required for a high level of hypothetical accuracy was calculated from variance ratios.Results: Within- and between-individual variability was high for flavonoid intake, and intake of flavonoid subclasses, with variance ratios > 1. It was calculated that six days of WFR data are required for total flavonoid intake, and between 6 and 10 days was required for flavonoid subclasses. There was no effect of seasonality for total flavonoid intake or intake of flavonoid subclasses, with the exception that flavan-3-ol and flavanone intakes which were relatively low in summer, and in summer and winter, respectively.Conclusion: While the effects of seasonality on total flavonoid intake may be small, within- and between-individual variation associated with flavonoid intake assessment appears to be substantial across 12 days of WFR data in older adults. It is recommended that a minimum of 6 days of weighed food records are collected to minimise the impact of within- and between-individual variability on total flavonoid intake assessments in this population. [ABSTRACT FROM AUTHOR]

In this paper, we examine the stock market integration process amongst 17 Economic and Monetary Union (EMU) countries from January 2002 to June 2013 over a normal period as well as for the Global Financial Crisis (GFC) and Eurozone Debt Crisis (EDC) periods. We classify the economies in three groups (A, B and C) based on their GDP to examine whether the economic size influences financial integration. Seven indicators are used for the purpose, namely, beta convergence, sigma convergence, variance ratio, asymmetric DCC, dynamic cointegration, market synchronisation measure and common components approach. The results suggest that large-sized EMU economies (termed as Group A) exhibit strong stock market integration. Moderate integration is observed for middle-sized EMU economies with old membership (termed as Group B). Small-sized economies (termed as Group C) economies seemed to be least integrated within the EMU stock market system. The findings further suggest presence of contagion effects as one moves from normal to crisis periods, which are specifically stronger for more integrated economies of Group A. We recommend institutional, regulatory and other policy reforms for Group B and especially Group C to achieve higher level of integration. [ABSTRACT FROM AUTHOR]

The paper proposes three hypotheses for the factors of carbon price volatility on the basis of the existing literature, and then uses ensemble empirical model decomposition and variance ratio to analyze the carbon price volatility of the European Union emission trading system (EU ETS) and clean development mechanisms (CDM). The results show that carbon price volatility is mainly affected by the market mechanism and external environment. The frequency of the market mechanism is high, with the duration being $$<$$ 2 months and amplitudes $$<$$ 1 euro; the external environment has an impact on carbon price at a low frequency, with the duration lasting 5 months or more and amplitudes of more than 2 euros. From the comparison of the two markets, not only in duration, but also in amplitude, the market mechanism and heterogeneity environment are shown to have a more significant impact on EU ETS than on CDM. Compared with its early stages, the carbon market is no longer temperature sensitive. The carbon price has a clear downward trend, with that of the CDM market being the more obvious. [ABSTRACT FROM AUTHOR]

This note is concerned with examining the relationship between within-group and between-group variances in two-level nested designs. A latent variable modeling approach is outlined that permits point and interval estimation of their ratio and allows their comparison in a multilevel study. The procedure can also be used to test various hypotheses about the discrepancy between these two variances and assist with their relationship interpretability in empirical investigations. The method can also be utilized as an addendum to point and interval estimation of the popular intraclass correlation coefficient in hierarchical designs. The discussed approach is illustrated with a numerical example. [ABSTRACT FROM AUTHOR]

The composition and dynamics of plankton communities are critically affected by human-induced environmental changes. We analysed 33 years of phytoplankton monthly data collected in Lake Zurich (Switzerland), assigning organisms (genus level) to taxonomic groups (class, family), Reynolds associations and size categories. The aim was to understand how eutrophication and climate change have influenced taxa co-occurrence patterns within and between groups over the lake water column (14 depths, 0-135 m), using null-models to test for non-random spatial (depth) assembly. We found that the whole community showed high taxa co-occurrence levels, significantly deviating over time from random assembly concurrently with lake warming and reduced nutrient loading. This pattern was driven mostly by the depth structure of metalimnetic assemblages during summer and autumn. The prevalence of non-random spatial patterns changed for different taxonomic and functional groups, with only few significant deviations from null-model expectations. Within taxonomic and functional groups (particularly Classes and size categories), the frequency of spatial overdispersion of taxa decreased over time while the frequency of clustering increased. Our data suggest that the relative importance of mechanisms determining phytoplankton metacommunity dynamics have changed along with environmental gradients shaping water column structure. [ABSTRACT FROM AUTHOR]