Variance Ratio Research Articles

North Atlantic Subtropical Mode Water properties: intrinsic and atmospherically forced interannual variability

Abstract. This study investigates the contributions of the ocean's chaotic intrinsic variability (CIV) and atmospherically forced variability to the interannual fluctuations in the North Atlantic Subtropical Mode Water (STMW) properties. Utilizing a 0.25° regional 50-member ocean–sea-ice ensemble simulation driven by an original surface forcing method and perturbed initially, the forced variability in STMW properties is estimated from ensemble mean fluctuations, while CIV is determined from deviations around the ensemble mean within each member. The model successfully captures the main features of STMW, showing correct agreement with observation-based ARMOR3D data in terms of location, seasonality, mean temperature and volume, as well as interannual variance of STMW's main properties. CIV significantly impacts STMW, explaining 10 %–13 % and 28 %–44 % of the interannual variance of its geometric and thermohaline mean properties, respectively, with a maximum imprint on STMW temperature. Observation-based and simulated intrinsic-to-total variance ratios are mostly consistent, dispelling concerns about a signal-to-noise paradox. This study also illustrates the advantages of ensemble simulations over single simulations in understanding oceanic fluctuations and attributing them to external drivers, while also cautioning against overreliance on individual simulation assessments.

Liquidity and the Strategic Value of Information

Abstract In Kyle (1985), the ratio of fundamental variance to price impact measures the value of information to a monopolist strategic informed investor. We show this same statistic provides an approximation for the value of information in a more general setting with multiple differentially-informed investors, and estimate it using high-frequency stocks data. We find that the value of information rises during crises. The value of information is higher for large, growth, and momentum stocks. Its most dramatic spikes occur at the start of the Covid-19 pandemic and the financial crisis of 2008, when the Fed announces liquidity facilities.

An Analysis Comparing the Taguchi Method for Optimizing the Process Parameters of AA5083/Silicon Carbide and AA5083/Coal Composites that Are Fabricated via Friction Stir Processing

Aluminium metal matrix composites are widely used in automotive, aerospace, marine, and structural engineering due to their high strength-to-weight ratio and superior mechanical properties. Optimizing friction stir process parameters is critical to enhancing the performance of these materials. This study investigates the effects of FSP parameters such as rotational speed, tilt angle, and traverse speed, on the mechanical properties of AA5083/Silicon carbide and AA5083/Coal composites. Using a Taguchi L9 design of experiments, signal-to-noise ratio, and analysis of variance, this study identifies the optimal process settings for maximizing ultimate tensile strength, microhardness, and elongation. From the results, the study revealed that for AA5083/Silicon carbide composites, rotational speed was the most significant factor affecting tensile strength, while for AA5083/Coal composites, tilt angle played a more critical role. Rotational speed consistently influenced microhardness and elongation for both materials. The signal-to-noise ratio analysis indicates that optimal FSP parameters vary depending on the reinforcement material used. This study highlights the importance of tailoring FSP settings to specific reinforcements to achieve optimal mechanical properties. These findings contribute to the advancement of friction stir processing techniques for fabricating high-performance aluminium metal matrix composites, particularly for applications in industries requiring strong, lightweight, and corrosion-resistant materials.

Comparison of Lower-Limb Muscle Synergies Between Young and Old People During Cycling Based on Electromyography Sensors—A Preliminary Cross-Sectional Study

The purpose of this study was to analyze the lower-limb muscle synergies of young and older adults during stationary cycling across various mechanical conditions to reveal adaptive strategies employed by the elderly to address various common pedaling tasks and function degradation. By comparing lower-limb muscle synergies during stationary cycling between young and old people, this study examined changes in muscle synergy patterns during exercise in older individuals. This is crucial for understanding neuromuscular degeneration and changes in movement patterns in older individuals. Sixteen young and sixteen older experienced cyclists were recruited to perform stationary cycling tasks at two levels of power (60 and 100 W) and three cadences (40, 60, and 90 rpm) in random order. The lower-limb muscle synergies and their inter- and intra-individual variability were analyzed. Three synergies were extracted in this study under all riding conditions in both groups while satisfying overall variance accounted for (VAF) > 85% and muscle VAF > 75%. The older adults exhibited lower variability in synergy vector two and a higher trend in the variability of activation coefficient three, as determined by calculating the variance ratio. Further analyses of muscle synergy structures revealed increased weighting in major contribution muscles, the forward-shifting peak activation in synergy one, and lower peak magnitude in synergy three among older adults. To produce the same cycling power and cadence as younger individuals, older adults make adaptive adjustments in muscle control—increased weighting in major contribution muscles, greater consistency in the use of primary force-producing synergies, and earlier peak activation of subsequent synergy.

Assessing the Turkish version of the Individual Work Performance Questionnaire (IWPQ) for its validity and reliability

BackgroundsThis study aimed to assess the validity and reliability of the Turkish version of the Individual Work Performance Questionnaire (IWPQ).MethodsA total of 340 adult participants who had been working for at least 8 h a day completed the study questionnaire online. The questionnaire consisted of sections on demographics and socioeconomic characteristics, the IWPQ, and the ultrashortened version of the Utrecht Work Engagement Scale (UWES-3). Principal component analysis (PCA) with Promax rotation was conducted to assess the e three-factor structure for the Turkish version of the IWPQ. Cronbach’s alpha was used to determine internal consistency. The intraclass correlation coefficient (ICC) was used to assess test-retest reliability. Spearman correlation coefficients were calculated between the IWPQ and UWES-3 scales to evaluate convergent validity.ResultsThe three factors accounted for a total variance ratio of 60.7%. Cronbach’s alphas of three subscales (task performance, contextual performance, and counterproductive work behavior) were 0.894, 0.875, and 0.796, respectively. Test-retest reliability showed high agreement, with ICCs of 0.96, 0.98, and 0.91 for the respective scales. There was a statistically significant correlation between UWES-3 and the task performance subscale (ρ = 0.367 and p < 0.001), a statistically significant correlation between UWES-3 and the contextual performance subscale (ρ = 0.403 and p < 0.001), and a statistically significant correlation between UWES-3 and the CWB subscale (ρ=-0.352 and p < 0.001).ConclusionsThe Individual Work Performance Questionnaire (IWPQ) identifies work performance.The Turkish version of the IWPQ scales demonstrated validity and reliability in assessing individual work performance.

Investigating the market tightness of selected stocks in the Johannesburg Stock Exchange

The market tightness of equity securities is an integral component of financial market because it supports smooth trading and absorb market shocks. However, the contention has always been to effectively determine the level of tightness in equity securities with the application of proper methodology in order to make informed decisions. Therefore, aim of this study was to examine the level of market tightness in selected stocks in the Johannesburg stock exchange. Using a variance ratio model, the findings of this study indicates that most securities trading on the exchange lack market tightness. This was evident in the difference between the one, two and three months variances that were not equal to 1 . Therefore, a specialist system should be introduced in order to facilitate the execution of trades without significantly moving the prices of equity securities. This study improves the frontier of knowledge regarding liquidity management, by empirically investigating the market tightness of equity securities.

Bond market structure and volatility

AbstractWe apply variance ratio methodologies to examine market quality in the US corporate bond market. We find that the open‐to‐open to close‐to‐close return variance ratio is greater than one suggesting that the corporate bond market is less efficient during the opening hours than during the closing hours. We show that the higher variance ratio at the open is related to the market power of dealers at the open and the sources of power are from lower cost of inventory, lower asymmetric information, and more flexibility to intermediate a trade. Dealers appear to exert less market power for bonds with low volume and credit rating. The results are consistent with dealers behaving strategically to unload risky assets and take on safer assets.

Factors associated with the perception of university social responsibility among dental students from two universities in the Peruvian capital: a multivariable regression analysis

Students play a key role in university social responsibility (USR), as they are the protagonists of change and the fundamental axis in the teaching-learning process. This study aims to assess the factors associated with the perception of university social responsibility among dental students from two universities in the Peruvian capital. This analytical cross-sectional study assessed 754 students from two Peruvian universities between May and July 2023. The study utilized a validated 51-item questionnaire to assess sociodemographic factors and dental students’ perception of USR. A Poisson regression model with robust variance and prevalence ratio (PR) was used to assess the influence of variables such as age, sex, marital status, type of university, academic year, and awareness of taking subjects related to USR. The significance was set at p < 0.05. The perception of USR was rated as poor, fair, and good by 16%, 67%, and 17% of the participants, respectively. According to the study, dental students from public universities were 68% more likely to perceive their USR education as poor than those from private universities (APR = 1.68, 95% CI: 1.06–2.66), and those who were aware of taking MSR-related courses were 37% less likely to perceive their USR education as poor (APR = 0.63, 95% CI: 0.40–0.98). Similarly, dental students attending public universities were 2.28 times more likely to perceive poor organizational management in USR compared to their counterparts at private universities (APR = 2.28, 95% CI: 1.51–3.44). Additionally, students in their first and second academic years were 62% and 57% less likely to perceive poor organizational management in USR compared to those in their sixth year (APR = 0.38, 95% CI: 0.19–0.79 and APR = 0.43, 95% CI: 0.20–0.95; respectively). Furthermore, students from public universities were 2.31 times more likely to perceive social participation in USR poorly compared to their counterparts from private universities (APR = 2.31, 95% CI: 1.63–3.26). Lastly, it was observed that students from public universities were 2.51 times more likely to have a poor overall perception of USR compared to students from private universities (APR = 2.51, 95% CI: 1.67–3.78). Acknowledging the diverse contexts and challenges inherent in public and private institutions, it can be concluded that more than half of the dental students had a fair perception of USR. Additionally, attending a public university was found to be a risk factor for having a poor perception of USR. However, taking a course related to USR and being in the early years of the program were identified as protective factors against a poor perception of organizational training and management in USR. It is recommended that students be involved in USR activities, including the Sustainable Development Goals, from the first years of their university education, especially in public universities.

Gender Differences in Variability in Intimate Relationship Satisfaction: A Secondary Analysis and Meta-Analysis.

There is a long-standing interest in gender differences in satisfaction in intimate relationships. Whereas prior research has focused on gender differences in central tendency (i.e., means), we conducted two studies - a secondary analysis of data from a probability sample of Australian married couples and a meta-analysis - to examine gender differences in variability (i.e., variances). We hypothesized that compared to males, females would demonstrate greater variability in intimaterelationship satisfaction (i.e., greater female variability hypothesis), particularly at lower levels of relationship satisfaction. Results from a secondary analysis of data from 2,711 married couples in the Household, Income and Labour Dynamics in Australia (HILDA) survey and from a meta-analysis of 20 years of research (k = 171, N = 84,976), including independent samples from 33 countries, indicated that relative to males, females reported greater variability in relationship satisfaction. Obtained effect sizes (female-to-male variance ratios [VRs] of 1.42 for the HILDA sample and 1.19 for the meta-analysis) were larger than proposed cutoffs for meaningful group differences in variability. Analysis of tail ratios (ratios of the relative proportion of females divided by the relative proportion of males in the distributional tail regions) in the HILDA sample indicated that gender differences in variability were greater at lower (versus higher) levels of satisfaction. Findings support the greater female variability hypothesis and suggest that by focusing only on gender differences in means, the existing literature has underestimated gender differences in intimaterelationship satisfaction.

A comprehensive study on the effects of printing parameters on the mechanical properties of PLA

Purpose This study aims to investigate the effects of five different printing parameters, namely, printing speed (PS), printing temperature/nozzle temperature/extrusion temperature, heated-bed temperature, raster angle (RA) and layer height (LT), on mechanical properties. Design/methodology/approach American Society for Testing and Materials (ASTM) standards were used for the specimen design. Then, the Taguchi method was used for the design of the experiment and an L16 orthogonal array was preferred. Tensile, Shore D and surface roughness tests were conducted on polylactic acid test specimens. The test results were analyzed using the signal-to-noise ratio and analysis of variance (ANOVA). Findings As a result of the study, it was seen that RA is the most important parameter for the tensile strength, PS is for the hardness and LT is for the surface roughness. According to the ANOVA results, the effects of the RA, PS and LT on the maximum tensile strength, hardness and surface roughness were 41.59%, 69.51% and 44.6%, respectively. Originality/value To the best of the authors’ knowledge, this study is one of the most comprehensive parameter optimization studies for additive manufacturing in the literature because it includes five different printing parameters and three mechanical test procedures.

Enhanced performance of perovskite solar cell by optimization of thin film control parameters using Taguchi method

The objective of the study is to examine the influence of various thin film control parameters on the synthesis of carbon-based passivated perovskite solar cells. Passivation additives, namely MOF UiO-66-NH2 (20mg/ml) and inorganic additive KPF6 (1mg/ml), were applied to treat the perovskite solar cells simultaneously. A PSC device of a standard configuration FTO/TiO2/Perovskite layer/Additives/HTL/Carbon electrode is utilized for experimentation. The performance evaluation of the system was carried out using Taguchi method. The critical control parameters considered in the study are: type of perovskite; annealing temperature of perovskite layer; the number of perovskite coating layers; and the type of hole transport layer (HTL). Each parameter is allocated three levels. An orthogonal array was designed using the Taguchi technique to optimize the quality control parameters. The signal-to-noise (S/N) ratio and analysis of variance (ANOVA) were then utilized to determine the ideal combination of parameters. The analysis identified the significant contribution of each parameter to the efficiency of perovskite cells. Among these parameters, the type of perovskite (used in the synthesis process) was found to impact the fabrication and performance of the cells significantly. Furthermore, it was observed that the type of hole transport layer (HTL) employed in the device significantly influences its performance. The best combination for our experiment is found to have FA0.55MA0.25Cs0.20PbI3 as the perovskite-type, an annealing temperature of 120˚C, a double layer of perovskite coating and Spiro-OMeTAD as the HTL. The solar cell is developed for each experiment as well as the validation test.

Microstructural evaluation and optimization of wear behaviour of vacuum arc melted AlFeCrNiSi high entropy alloy

High-entropy alloys (HEA) are equiatomic, multi-element systems that, while having several elements with various crystal geometries to form a single phase. In this study, a novel equiatomic AlFeCrNiSi HEA is prepared using the vacuum arc melting process. The resulting microstructure featured dendritic and inter-dendritic structures with formations of intermetallic compounds such as Al₃Fe₂Si, NiAl, and AlCrNi phases. EDS analysis confirmed the presence of alloying elements and EBSD analysis revealed refined grains with an average size of 1 ± 0.15 µm size. Pin-on-Disc wear test with varying test parameters is conducted to optimize the wear parameters. Signal-to-noise ratio and analysis of variance identified the most significant wear parameters, with load being the most influential, followed by sliding distance and velocity. The wear rate is minimum at the lowest conditions of applied load, sliding distance, and sliding velocity. The improved microhardness also contributed to the improved wear resistance of the cast alloy. The subsequent worn morphology revealed the formation of grooves, microcracks, and oxide layers on the worn surface.

The Effect of Sample Weighting on Hierarchical Linear Modeling in the Large-Scale Assessment Data

This study examines how the different uses of sampling weights in the analysis of TIMSS 2019 data affect the ratio of variance in student achievement explained by schools and the estimation of standard errors. The research sample comprises 227,345 8th grade students from 7,636 schools in 39 countries. Mathematics achievement and science achievement are considered separately as dependent variables in all 39 countries. All plausible values are included in the analysis. Four weighting scenarios are examined: no weighting, weighting at only level 1, weighting at only level 2, and weighting at both levels. In total, 312 models are established and examined. According to the research results, the coefficients, standard errors, reliabilities, and χ^2 estimations change depending on how the weighting variable is handled in the models, and as a result, the ratio of variance in the dependent variable arising from the differences between schools also changes. The ratio attributable to between-school differences can reach up to 20% in some countries. Therefore, researchers modeling hierarchical data using HLM are suggested to plan how they handle the weighting variable prior to conducting the study.

Elimination of phenol by sonoelctrochemical process utilizing graphite, stainless steel, and titanium anodes: optimization by taguchi approach

Phenol is one of the worst-damaging organic pollutants, and it produces a variety of very poisonous organic intermediates, thus it is important to find efficient ways to eliminate it. One of the promising techniques is sonoelectrochemical processing. However, the type of electrodes, removal efficiency, and process cost are the biggest challenges. The main goal of the present study is to investigate the removal of phenol by a sonoelectrochemical process with different anodes, such as graphite, stainless steel, and titanium. The best anode performance was optimized by using the Taguchi approach with an L16 orthogonal array. the degradation of phenol sonoelectrochemically was investigated with three process parameters: current density (CD) (25, 50, 75, and 100 mA/cm2), time (1, 2, 3, 4 h), and phenol concentration (100, and 200 mg/l). Signal-to-noise (S/N) ratio and analysis of variance (ANOVA) were utilized to examine the impact of each factor. The optimal conditions for phenol removal were 100 mA/cm2, 100 mg/l of phenol, and 4 hours of electrolysis. Under optimal operating conditions, the phenol removal efficiency was 80.99%. The CD was the most influential factor on phenol elimination effectiveness, while the phenol concentration had the least impact.

Quantification of tungsten in real samples spectrophotometrically using optical sensor

A new methodology was devised to detect tungsten in aqueous samples, employing a sensor membrane crafted by physically incorporating a tungsten-selective compound, 5-(2 -bromophenylazo)-6-hydroxypyrimidine-2,4-dione (BPAHPD), into a plasticized poly(vinyl chloride). The addition of Triton X-114 was observed to be advantageous in augmenting the absorption of HWO4− ions from the liquid phase into the membrane phase, thereby amplifying sensor absorption intensity. The method established a linear dynamic span of 15–350 ng mL−1 for W(VI), exhibiting a notable correlation coefficient of 0.9992. Quantification and detection limits were determined to be 14.85 and 4.45 ng mL−1, correspondingly, under optimized conditions. The Sandell responsiveness and molar absorptivity were calculated at 0.0455 ng cm−2 and 4.04 × 108 L/mol cm−1, respectively. The sensor demonstrated superb selectivity, as demonstrated by the negligible influence of potential interfering species. Statistical analyses, encompassing variance ratio F-tests and Student’s t-tests, indicated no substantial differences. The efficacy of the methodology was authenticated through the scrutiny of genuine samples, with statistical comparison to the ICP-AES method.

Value Relevance of Key Accounting Information in Predicting Market Performance: A Machine Learning Approach

This study aims to examine the value relevance of key accounting information in predicting market performance and to explore which accounting information has the most value relevance in predicting market performance. The dataset is comprised of a total of 1401 observations from 117 companies over a period of 2010 to 2021. To conduct the study, total 12 indicators were taken from financial statements to represent the major accounting information (AI) and year-end market price and Tobin’s Q were taken as a proxy for market performance. Under the principal component analysis (PCA), it was found that only 3 AIs namely earnings per share (EPS), book value per share (BVPS) and cash flow per share (CFPS) could contribute to the whole explained variance ratio of market performance. The study employs several machine learning approaches: random forest regression (RFR) was chosen as the base line model and the result was compared with decision tree regression (DTR), long short term memory (LSTM), neural network model and multivariate regression model. After splitting the total observation into a 70:30 training-testing dataset and controlling for noise reduction, it was found that over any other models, LSTM and RFR models can predict the market performance with higher R-square value of 62% and 65% respectively along with the lowest MSE of all other models. It was found that EPS has the highest value relevance (factor importance) in predicting market profitability whereas BVPS and CFPS were found to have less than 10% factor importance in predicting market profitability.

New Techniques for Estimating Finite Population Variance Using Ranks of Auxiliary Variable in Two-Stage Sampling

This article presents a new set of estimators designed to estimate the finite population variance of a study variable in two-phase sampling. These estimators utilize the information about extreme values and ranks of an auxiliary variable. Through a first-order approximation, we investigate the properties of these estimators, including biases and mean squared errors (MSEs). Furthermore, a comprehensive simulation study is conducted to assess their performance and validate our theoretical insights. Results demonstrate that our proposed class of estimators performs better in terms of percent relative efficiency (PRE) across various simulation scenarios compared to existing estimators. In addition, in the application section, we utilize three data sets to further validate the performance of our proposed estimators against conventional unbiased variance estimators, ratio and regression estimators, as well as other existing methods.

Does speculation impair informational efficiency? New evidence from the Indian agricultural commodity market

Purpose This study explores the association between market efficiency and speculation. The government of India temporarily banned the futures trading of various commodities several times citing the presence of speculation. Many controversies exist about this topic; thus, this study clarifies the association between market efficiency and speculation and investigates whether market reforms altered this association.Design/methodology/approach The data for nine commodities is collected from the National Commodity and Derivative Exchange (NCDEX) for 2005–2022. Regression analysis and Automatic Variance Ratio (AVR) were adopted to inspect the informational efficiency and influence of speculation in the commodity market. Furthermore, this study uses different sub-samples to understand the changes in the market microstructure and its effects on market quality.Findings The results confirm an inverse and significant relationship between information efficiency and speculation and a deviation from the random walk process observed. Therefore, return predictability exists in the market. This study confirms that market reforms do not reduce the influence of speculation on market efficiency. The study concludes that the market is not weak-form efficient.Research limitations/implications This study has certain limitations, since this study is empirical in nature, it may possess the limitations of empirical research.Originality/value This paper has dual novelty. First, this study investigates the effects of market reforms. Second, this study captures the influence of speculation in the Indian agricultural commodity market by considering the market microstructure aspects.

Estimation of Combining Ability Effect for Hybrid Breeding in Bottle Gourd [Lagenaria siceraria (Molina) Standl.] Using Diallel Mating Design

A half diallel mating design was employed to cross eight parental lines of bottle gourd, resulting in 28 F1 hybrids (excluding reciprocals). These F1 hybrids, along with the parental lines and a commercial check (Pant Lauki-3), were evaluated during the summer of 2024 at Govind Ballabh Pant University of Agriculture and Technology, Pantnagar. The study aimed to assess the combining ability for yield and yield-related traits using a randomized complete block design with three replications. The genetic variance ratio being less than unity suggested that non-additive gene action was dominant for all the characters. The analysis indicated that none of the parents consistently exhibited good general combining ability across all traits. However, the cross combination NDBG-104 × Pusa Sandesh followed by Pant Lauki-4 × Kashi Kirti emerged as the best for most of the traits analyzed. The results suggest that it may be possible to further enhance fruit yield and earliness through hybridization and selection in transgressive segregants.

Understanding variability: the role of meta-analysis of variance.

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.