A space-time analysis of reported shigellosis and salmonellosis cases in Texas from 2000 to 2004

Background. The purpose of this study was to describe the risk factors and demographics of persons with salmonellosis and shigellosis and to investigate both seasonal and spatial variations in the occurrence of these infections in Texas from 2000 to 2004, utilizing time series analyses and the geographic information system digital mapping methods. ^ Methods. Spatial Analysis: MapInfo software was used to map the distribution of age-adjusted rates of reported shigellosis and salmonellosis in Texas from 2000–2004 by zip codes. Census data on above or below poverty level, household income, highest level of educational attainment, race, ethnicity, and urban/rural community status was obtained from the 2000 Decennial Census for each zip code. The zip codes with the upper 10% and lower 10% were compared using t-tests and logistic regression to determine whether there were any potential risk factors. ^ Temporal analysis. Seasonal patterns in the prevalence of infections in Texas from 2000 to 2003 were determined by performing time-series analysis on the numbers of cases of salmonellosis and shigellosis. A linear regression was also performed to assess for trends in the incidence of each disease, along with auto-correlation and multi-component cosinor analysis. ^ Results. Spatial analysis: Analysis by general linear model showed a significant association between infection rates and age, with young children aged less than 5 and those aged 5–9 years having increased risk of infection for both disease conditions. The data demonstrated that those populations with high percentages of people who attained a higher than high school education were less likely to be represented in zip codes with high rates of shigellosis. However, for salmonellosis, logistic regression models indicated that when compared to populations with high percentages of non-high school graduates, having a high school diploma or equivalent increased the odds of having a high rate of infection. ^ Temporal analysis. For shigellosis, multi-component cosinor analyses were used to determine the approximated cosine curve which represented a statistically significant representation of the time series data for all age groups by sex. The shigellosis results show 2 peaks, with a major peak occurring in June and a secondary peak appearing around October. Salmonellosis results showed a single peak and trough in all age groups with the peak occurring in August and the trough occurring in February. ^ Conclusion. The results from this study can be used by public health agencies to determine the timing of public health awareness programs and interventions in order to prevent salmonellosis and shigellosis from occurring. Because young children depend on adults for their meals, it is important to increase the awareness of day-care workers and new parents about modes of transmission and hygienic methods of food preparation and storage. ^

Lifetime changes in body mass index and risk of breast cancer in minority women

Introduction: Obesity is an epidemic in the United States, especially among Hispanics and African-Americans. Studies of obesity and breast cancer risk and subtype have been conducted primarily in non-Hispanic whites. Obesity is inversely associated with premenopausal breast cancer, but both obesity and weight gain increase the risk of postmenopausal disease. Obesity has been associated with breast cancer subtype in many studies. Methods: To assess the association between changes in body mass index (BMI) over the lifetime, weight gain, and breast cancer in Mexican-American women, we conducted a case-control study using 149 cases and 330 age-matched controls. In a second study, we identified 212 African-American and 167 Mexican-American women with breast cancer in the ongoing ELLA Bi-National Breast Cancer Study, abstracted medical charts to classify tumors as ER+/PR+, HER2+, or ER-/PR-/HER2-, and assessed the association between lifetime changes in body mass index, weight gain, and breast cancer subtype. In both studies, growth mixture modeling was use to identify trajectories of change in BMI over the lifetime, and these trajectories were used as exposures in a logistic regression model to calculate odds ratios (OR). Results: There was no association between trajectories of change in BMI and breast cancer risk in Mexican-American women. In addition, BMI at ages 15 and 30 and at diagnosis was not associated with breast cancer. However, adult weight gain was inversely associated with breast cancer risk (per 5kg, OR=0.92, 95% CI: 0.85-0.99). The case-only analysis found no association between obesity at ages 15 and 30 and at diagnosis and breast cancer subtype. Further, there was no association between adult weight gain (defined as weight change from age 15 to time of diagnosis) and breast cancer subtype. Conclusions: Obesity was not associated with breast cancer risk in Mexican-American women, while adult weight gain reduced the risk independently of menopausal status. These results are contradictory of those in non-Hispanic white women and suggest that the etiology of breast cancer may differ by race/ethnicity. Further, obesity was not associated with breast cancer subtype in African-American and Mexican-American women, contrary to results in non-Hispanic white women. ^

Expanding Learning Time in Schools: Considering the Challenges of Implementation and the Potential Impact

Considering the broader context of school reform that is seeking education strategies that might deliver substantial impact, this article examines four questions related to the policy and practice of expanding learning time: (a) why do educators find the standard American school calendar insufficient to meet students’ educational needs, especially those of disadvantaged students? (b) how do educators implement a longer day and/or year, addressing concerns about both educational quality and costs? (c) what does research report about outcomes of expanding time in schools? and (d) what are the future prospects for increasing the number of expanded-time schools? The paper examines these questions by considering research, policy, and practice at the national level and, throughout, by drawing upon additional evidence from Massachusetts, one of the leading states in the expanded-time movement. In considering the latter two questions, the article explores the knowns and unknowns related to expanded learning time and offers suggestions for further research.

Environmental variables modeling based on remote sensing data using time series analysis: forestry and agricultural applications

En la actualidad, el seguimiento de la dinámica de los procesos medio ambientales está considerado como un punto de gran interés en el campo medioambiental. La cobertura espacio temporal de los datos de teledetección proporciona información continua con una alta frecuencia temporal, permitiendo el análisis de la evolución de los ecosistemas desde diferentes escalas espacio-temporales. Aunque el valor de la teledetección ha sido ampliamente probado, en la actualidad solo existe un número reducido de metodologías que permiten su análisis de una forma cuantitativa. En la presente tesis se propone un esquema de trabajo para explotar las series temporales de datos de teledetección, basado en la combinación del análisis estadístico de series de tiempo y la fenometría. El objetivo principal es demostrar el uso de las series temporales de datos de teledetección para analizar la dinámica de variables medio ambientales de una forma cuantitativa. Los objetivos específicos son: (1) evaluar dichas variables medio ambientales y (2) desarrollar modelos empíricos para predecir su comportamiento futuro. Estos objetivos se materializan en cuatro aplicaciones cuyos objetivos específicos son: (1) evaluar y cartografiar estados fenológicos del cultivo del algodón mediante análisis espectral y fenometría, (2) evaluar y modelizar la estacionalidad de incendios forestales en dos regiones bioclimáticas mediante modelos dinámicos, (3) predecir el riesgo de incendios forestales a nivel pixel utilizando modelos dinámicos y (4) evaluar el funcionamiento de la vegetación en base a la autocorrelación temporal y la fenometría. Los resultados de esta tesis muestran la utilidad del ajuste de funciones para modelizar los índices espectrales AS1 y AS2. Los parámetros fenológicos derivados del ajuste de funciones permiten la identificación de distintos estados fenológicos del cultivo del algodón. El análisis espectral ha demostrado, de una forma cuantitativa, la presencia de un ciclo en el índice AS2 y de dos ciclos en el AS1 así como el comportamiento unimodal y bimodal de la estacionalidad de incendios en las regiones mediterránea y templada respectivamente. Modelos autorregresivos han sido utilizados para caracterizar la dinámica de la estacionalidad de incendios y para predecir de una forma muy precisa el riesgo de incendios forestales a nivel pixel. Ha sido demostrada la utilidad de la autocorrelación temporal para definir y caracterizar el funcionamiento de la vegetación a nivel pixel. Finalmente el concepto “Optical Functional Type” ha sido definido, donde se propone que los pixeles deberían ser considerados como unidades temporales y analizados en función de su dinámica temporal. ix SUMMARY A good understanding of land surface processes is considered as a key subject in environmental sciences. The spatial-temporal coverage of remote sensing data provides continuous observations with a high temporal frequency allowing the assessment of ecosystem evolution at different temporal and spatial scales. Although the value of remote sensing time series has been firmly proved, only few time series methods have been developed for analyzing this data in a quantitative and continuous manner. In the present dissertation a working framework to exploit Remote Sensing time series is proposed based on the combination of Time Series Analysis and phenometric approach. The main goal is to demonstrate the use of remote sensing time series to analyze quantitatively environmental variable dynamics. The specific objectives are (1) to assess environmental variables based on remote sensing time series and (2) to develop empirical models to forecast environmental variables. These objectives have been achieved in four applications which specific objectives are (1) assessing and mapping cotton crop phenological stages using spectral and phenometric analyses, (2) assessing and modeling fire seasonality in two different ecoregions by dynamic models, (3) forecasting forest fire risk on a pixel basis by dynamic models, and (4) assessing vegetation functioning based on temporal autocorrelation and phenometric analysis. The results of this dissertation show the usefulness of function fitting procedures to model AS1 and AS2. Phenometrics derived from function fitting procedure makes it possible to identify cotton crop phenological stages. Spectral analysis has demonstrated quantitatively the presence of one cycle in AS2 and two in AS1 and the unimodal and bimodal behaviour of fire seasonality in the Mediterranean and temperate ecoregions respectively. Autoregressive models has been used to characterize the dynamics of fire seasonality in two ecoregions and to forecasts accurately fire risk on a pixel basis. The usefulness of temporal autocorrelation to define and characterized land surface functioning has been demonstrated. And finally the “Optical Functional Types” concept has been proposed, in this approach pixels could be as temporal unities based on its temporal dynamics or functioning.

Temperature, ordering, and equilibrium with time-dependent confining forces

The concepts of temperature and equilibrium are not well defined in systems of particles with time-varying external forces. An example is a radio frequency ion trap, with the ions laser cooled into an ordered solid, characteristic of sub-mK temperatures, whereas the kinetic energies associated with the fast coherent motion in the trap are up to 7 orders of magnitude higher. Simulations with 1,000 ions reach equilibrium between the degrees of freedom when only aperiodic displacements (secular motion) are considered. The coupling of the periodic driven motion associated with the confinement to the nonperiodic random motion of the ions is very small at low temperatures and increases quadratically with temperature.

Human Motion Analysis Based on Sequential Modeling of Radar Signal and Stereo Image Features

Falls are one of the greatest threats to elderly health in their daily living routines and activities. Therefore, it is very important to detect falls of an elderly in a timely and accurate manner, so that immediate response and proper care can be provided, by sending fall alarms to caregivers. Radar is an effective non-intrusive sensing modality which is well suited for this purpose, which can detect human motions in all types of environments, penetrate walls and fabrics, preserve privacy, and is insensitive to lighting conditions. Micro-Doppler features are utilized in radar signal corresponding to human body motions and gait to detect falls using a narrowband pulse-Doppler radar. Human motions cause time-varying Doppler signatures, which are analyzed using time-frequency representations and matching pursuit decomposition (MPD) for feature extraction and fall detection. The extracted features include MPD features and the principal components of the time-frequency signal representations. To analyze the sequential characteristics of typical falls, the extracted features are used for training and testing hidden Markov models (HMM) in different falling scenarios. Experimental results demonstrate that the proposed algorithm and method achieve fast and accurate fall detections. The risk of falls increases sharply when the elderly or patients try to exit beds. Thus, if a bed exit can be detected at an early stage of this motion, the related injuries can be prevented with a high probability. To detect bed exit for fall prevention, the trajectory of head movements is used for recognize such human motion. A head detector is trained using the histogram of oriented gradient (HOG) features of the head and shoulder areas from recorded bed exit images. A data association algorithm is applied on the head detection results to eliminate head detection false alarms. Then the three dimensional (3D) head trajectories are constructed by matching scale-invariant feature transform (SIFT) keypoints in the detected head areas from both the left and right stereo images. The extracted 3D head trajectories are used for training and testing an HMM based classifier for recognizing bed exit activities. The results of the classifier are presented and discussed in the thesis, which demonstrates the effectiveness of the proposed stereo vision based bed exit detection approach.

Dynamic D-Vine copula model with applications to Value-at-Risk (VaR)

Regular vine copulas are multivariate dependence models constructed from pair-copulas (bivariate copulas). In this paper, we allow the dependence parameters of the pair-copulas in a D-vine decomposition to be potentially time-varying, following a nonlinear restricted ARMA(1,m) process, in order to obtain a very flexible dependence model for applications to multivariate financial return data. We investigate the dependence among the broad stock market indexes from Germany (DAX), France (CAC 40), Britain (FTSE 100), the United States (S&P 500) and Brazil (IBOVESPA) both in a crisis and in a non-crisis period. We find evidence of stronger dependence among the indexes in bear markets. Surprisingly, though, the dynamic D-vine copula indicates the occurrence of a sharp decrease in dependence between the indexes FTSE and CAC in the beginning of 2011, and also between CAC and DAX during mid-2011 and in the beginning of 2008, suggesting the absence of contagion in these cases. We also evaluate the dynamic D-vine copula with respect to Value-at-Risk (VaR) forecasting accuracy in crisis periods. The dynamic D-vine outperforms the static D-vine in terms of predictive accuracy for our real data sets.

Occupational sitting time and overweight and obesity in Australian workers

Background: One of the major immediate and long-term health issues in modern society is the problem of overweight and obesity. This paper examines the role of the workplace in the problem by studying the association between occupational sitting time and overweight and obesity (body mass index [BMI] >= 25) in a sample of adult Australians in full-time employment. Methods: Data on age, gender, occupation, physical activity, occupational sitting time, and BMI were collected in September 2003 from a sample of 1579 adult men and women in full-time employment at the time of the survey. Logistic regression was used to examine the association between occupational sitting time and overweight and obesity. Results: Mean occupational sitting time was > 3 hours/day, and significantly higher in men (209 minutes) than in women (189 minutes, p =0.026). Univariate analyses showed significant associations between occupational sitting time and BMI of >= 25 in men but not in women. After adjusting for age, occupation, and physical activity, the odds ratio for BMI >= 25 was 1.92 (confidence interval: 1.17-3.17) in men who reported sitting for > 6 hours/day, compared with those who sat for < 45 minutes/day. Conclusions: Occupational sitting time was independently associated with overweight and obesity in men who were in full-time paid work. These results suggest that the workplace may play an important role in the growing problem of overweight and obesity. Further research is needed to clearly understand the association between sitting time at work and over-weight and obesity in women.

Conditional risk, return and contagion in the banking sector in Asia

This paper investigates risk and return in the banking sector in three Asian markets of Taiwan, China and Hong Kong. The study focuses on the risk-return relation in a conditional factor GARCH-M framework that controls for time-series effects. The factor approach is adopted to incorporate intra-industry contagion and an analysis of spillovers between large banks and small banks. Finally, the study provides evidence on these relations before and after the Asian financial crisis of 1997. The results are generally consistent across the markets and with expectations.

Quantitative risk assessment of groundwater quality utilizing GIS technology and coupled groundwater models

The thesis presents a two-dimensional Risk Assessment Method (RAM) where the assessment of risk to the groundwater resources incorporates both the quantification of the probability of the occurrence of contaminant source terms, as well as the assessment of the resultant impacts. The approach emphasizes the need for a greater dependency on the potential pollution sources, rather than the traditional approach where assessment is based mainly on the intrinsic geo-hydrologic parameters. The risk is calculated using Monte Carlo simulation methods whereby random pollution events were generated to the same distribution as historically occurring events or a priori potential probability distribution. Integrated mathematical models then simulate contaminant concentrations at the predefined monitoring points within the aquifer. The spatial and temporal distributions of the concentrations were calculated from repeated realisations, and the number of times when a user defined concentration magnitude was exceeded is quantified as a risk. The method was setup by integrating MODFLOW-2000, MT3DMS and a FORTRAN coded risk model, and automated, using a DOS batch processing file. GIS software was employed in producing the input files and for the presentation of the results. The functionalities of the method, as well as its sensitivities to the model grid sizes, contaminant loading rates, length of stress periods, and the historical frequencies of occurrence of pollution events were evaluated using hypothetical scenarios and a case study. Chloride-related pollution sources were compiled and used as indicative potential contaminant sources for the case study. At any active model cell, if a random generated number is less than the probability of pollution occurrence, then the risk model will generate synthetic contaminant source term as an input into the transport model. The results of the applications of the method are presented in the form of tables, graphs and spatial maps. Varying the model grid sizes indicates no significant effects on the simulated groundwater head. The simulated frequency of daily occurrence of pollution incidents is also independent of the model dimensions. However, the simulated total contaminant mass generated within the aquifer, and the associated volumetric numerical error appear to increase with the increasing grid sizes. Also, the migration of contaminant plume advances faster with the coarse grid sizes as compared to the finer grid sizes. The number of daily contaminant source terms generated and consequently the total mass of contaminant within the aquifer increases in a non linear proportion to the increasing frequency of occurrence of pollution events. The risk of pollution from a number of sources all occurring by chance together was evaluated, and quantitatively presented as risk maps. This capability to combine the risk to a groundwater feature from numerous potential sources of pollution proved to be a great asset to the method, and a large benefit over the contemporary risk and vulnerability methods.

Ocular and systemic markers for vascular function in those at risk of type 2 diabetes mellitus and cardiovascular disease

The devastating impact of Type 2 Diabetes Mellitus (T2DM) -related morbidity and mortality on global healthcare is escalating with higher prevalences of obesity, poor diet, and sedentary lifestyles. Therefore, the clinical need for early diagnosis and prevention in groups of high-risk individuals is necessary. The purpose of this thesis was to investigate the use of surrogate markers, namely retinal vascular function, to determine future vascular endothelial dysfunction, atherosclerosis, large vessel disease and cardiovascular risk in certain groups. This namely covered normoglycaemic and normotensive South Asians (SAs), those with Impaired-Glucose Tolerance (IGT) and individuals with a familial history (FH) of T2DM. Additionally the effect of overweight and obesity was studied. The techniques and modified protocols adopted for this thesis involved the investigation of endothelial function by means of vascular reactivity at the ocular and systemic level. Furthermore, the relationships between retinal and systemic function with circulating markers for endothelial cell function and cardiovascular risk markers were explored. The principal studies and findings of the research were: Vascular Function in Normoglycaemic Individuals with and without a FH of T2DM WE FH individuals exhibited higher levels of total cholesterol levels that correlated well with the retinal arterial dilation amplitude to flicker light stimulus. However this did not extend to noticeable differences in markers for endothelial cell damage and impaired retinal and systemic function. Vascular Function in Normoglycaemic South-Asians vs. White-Europeans without a FH and Vascular Disturbances Compared to healthy WEs (normo -glycaemic and -tensive), SA participants exhibited levels of dyslipidaemia and a state of oxidative stress that extended to impaired vascular function as detected by reduced brachial artery flow-mediated dilation, slower retinal arterial vessel dilation reaction times (Appendix 3) and steeper constriction profiles. Furthermore, gender sub-group analysis presented in a sub-chapter shows that SA males demonstrated 24-hour systemic blood pressure (BP) and heart rate variability (HRV) abnormalities and heightened cardiovascular disease (CVD) risk. Vascular Function in Individuals Newly Diagnosed with IGT as compared to Normoglycaemic Healthy Controls Newly-diagnosed WE and SA IGT patients showed a greater risk for CVD and T2DM progression by means of 24-hour BP abnormalities, dyslipidaemia, increased carotid artery intimal-media thickness (c-IMT), Framingham scores and cholesterol ratios. Additionally, pre-clinical markers for oxidative stress and endothelial dysfunction, as evident by significantly lower levels of plasma glutathione and increased levels of von-Willebrand factor in IGT individuals, extended to impaired vascular systemic and retinal function compared to normal controls. This originally shows retinal, systemic and biochemical disturbances in newly-diagnosed IGT not previously reported before. Vascular Function in Normal, Overweight and Obese Individuals of SA and WE Ethnicity In addition to the intended study chapters, the thesis also investigated the influence of obesity and overweight on vascular function. Most importantly, it was found for the first time that compared to lean individuals it was overweight and not obese individuals that exhibited signs of vascular systemic and ocular dysfunction that was evident alongside markers of atherosclerosis, CVD risk and endothelial damage.

Serial correlation in the returns of UK capitalization based portfolios

This article examines whether UK portfolio returns are time varying so that expected returns follow an AR(1) process as proposed by Conrad and Kaul for the USA. It explores this hypothesis for four portfolios that have been formed on the basis of market capitalization. The portfolio returns are modelled using a kalman filter signal extraction model in which the unobservable expected return is the state variable and is allowed to evolve as a stationary first order autoregressive process. It finds that this model is a good representation of returns and can account for most of the autocorrelation present in observed portfolio returns. This study concludes that UK portfolio returns are time varying and the nature of the time variation appears to introduce a substantial amount of autocorrelation to portfolio returns. Like Conrad and Kaul if finds a link between the extent to which portfolio returns are time varying and the size of firms within a portfolio but not the monotonic one found for the USA.

Real options and multinational investments : an empirical study of risk, performance and organisational awareness

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT This thesis is a cross-disciplinary study of the empirical impact of real options theory in the fields of decision sciences and performance management. Borrowing from the economics, strategy and operations research literature, the research examines the risk and performance implications of real options in firms’ strategic investments and multinational operations. An emphasis is placed on the flexibility potential and competitive advantage of multinational corporations to explore the extent to which real options analysis can be classified as best practice in management research. Using a combination of qualitative and quantitative techniques the evidence suggests that, if real options are explored and exploited appropriately, real options management can result in superior performance for multinational companies. The qualitative findings give an overview of the practical advantages and disadvantages of real options and the statistical results reveal that firms which have developed a high awareness of their real options are, as predicted by the theory, able to reduce their downside risk and increase profits through flexibility, organisational slack and multinationality. Although real options awareness does not systematically guarantee higher returns from operations, supplementary findings indicate that firms with evidence of significant investments in the acquisition of real options knowledge tend to outperform competitors which are unaware of their real options. There are three contributions of this research. First, it extends the real options and capacity planning literature to path-dependent contingent-claims analysis to underline the benefits of average type options in capacity allocation. Second, it is thought to be the first to explicitly examine the performance effects of real options on a sample of firms which have developed partial capabilities in real options analysis suggesting that real options diffusion can be key to value creation. Third, it builds a new decision-aiding framework to facilitate the use of real options in projects appraisal and strategic planning.

Corporate restructuring: empirical evidence from the UK

Corporate restructuring is perceived as a challenge to research. Prior studies do not provide conclusive evidence regarding the effects of restructuring. Since there are discernible findings, this research attempts to examine the effects of restructuring events amongst the UK listed firms. The sample firms are listed in the LSE and London AIM stock exchange. Only completed restructuring transactions are included in the study. The time horizon extends from year 1999 to 2003. A three-year floating window is assigned to examine the sample firms. The key enquiry is to scrutinise the ex post effects of restructuring on performance and value measures of firms with contrast to a matched criteria non-restructured sample. A cross sectional study employing logit estimate is undertaken to examine firm characteristics of restructuring samples. Further, additional parameters, i.e. Conditional Volatility and Asymmetry are generated under the GJR-GARCH estimate and reiterated in logit models to capture time-varying heteroscedasticity of the samples. This research incorporates most forms of restructurings, while prior studies have examined certain forms of restructuring. Particularly, these studies have made limited attempts to examine different restructuring events simultaneously. In addition to logit analysis, an event study is adopted to evaluate the announcement effect of restructuring under both the OLS and GJR-GARCH estimate supplementing our prior results. By engaging a composite empirical framework, our estimation method validates a full appreciation of restructuring effect. The study provides evidence that restructurings indicate non-trivial significant positive effect. There are some evidences that the response differs because of the types of restructuring, particularly while event study is applied. The results establish that performance measures, i.e. Operating Profit Margin, Return on Equity, Return on Assets, Growth, Size, Profit Margin and Shareholders' Ownership indicate consistent and significant increase. However, Leverage and Asset Turn Over suggest reasonable influence on restructuring across the sample period. Similarly, value measures, i.e. Abnormal Returns, Return on Equity and Cash Flow Margin suggest sizeable improvement. A notable characteristic seen coherently throughout the analysis is the decreasing proportion of Systematic Risk. Consistent with these findings, Conditional Volatility and Asymmetry exhibit similar trend. The event study analysis suggests that on an average market perceives restructuring favourably and shareholders experience significant and systematic positive gain.

Liquidity and portfolio optimisation

This thesis presents research within empirical financial economics with focus on liquidity and portfolio optimisation in the stock market. The discussion on liquidity is focused on measurement issues, including TAQ data processing and measurement of systematic liquidity factors (FSO). Furthermore, a framework for treatment of the two topics in combination is provided. The liquidity part of the thesis gives a conceptual background to liquidity and discusses several different approaches to liquidity measurement. It contributes to liquidity measurement by providing detailed guidelines on the data processing needed for applying TAQ data to liquidity research. The main focus, however, is the derivation of systematic liquidity factors. The principal component approach to systematic liquidity measurement is refined by the introduction of moving and expanding estimation windows, allowing for time-varying liquidity co-variances between stocks. Under several liability specifications, this improves the ability to explain stock liquidity and returns, as compared to static window PCA and market average approximations of systematic liquidity. The highest ability to explain stock returns is obtained when using inventory cost as a liquidity measure and a moving window PCA as the systematic liquidity derivation technique. Systematic factors of this setting also have a strong ability in explaining a cross-sectional liquidity variation. Portfolio optimisation in the FSO framework is tested in two empirical studies. These contribute to the assessment of FSO by expanding the applicability to stock indexes and individual stocks, by considering a wide selection of utility function specifications, and by showing explicitly how the full-scale optimum can be identified using either grid search or the heuristic search algorithm of differential evolution. The studies show that relative to mean-variance portfolios, FSO performs well in these settings and that the computational expense can be mitigated dramatically by application of differential evolution.