Stochastic modelling of financial time series with memory and multifractal scaling

Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

Structural and cellular features in metaphyseal and diaphyseal periosteum of osteoporotic rats

Despite the important physiological role of periosteum in the pathogenesis and treatment of osteoporosis, little is known about the structural and cellular characteristics of periosteum in osteoporosis. To study the structural and cellular differences in both diaphyseal and metaphyseal periosteum of osteoporotic rats, samples from the right femur of osteoporotic and normal female Lewis rats were collected and tissue sections were stained with hematoxylin and eosin, antibodies or staining kit against tartrate resistant acid phosphatase (TRAP), alkaline phosphatase (ALP), vascular endothelial growth factor (VEGF), von Willebrand (vWF), tyrosine hydroxylase (TH) and calcitonin gene-related peptide (CGRP). The results showed that the osteoporotic rats had much thicker and more cellular cambial layer of metaphyseal periosteum compared with other periosteal areas and normal rats (P\0.001). The number of TRAP? osteoclasts in bone resorption pits, VEGF? cells and the degree of vascularization were found to be greater in the cambial layer of metaphyseal periosteum of osteoporotic rats (P\0.05), while no significant difference was detected in the number of ALP? cells between the two groups. Sympathetic nerve fibers identified by TH staining were predominantly located in the cambial layer of metaphyseal periosteum of osteoporotic rats. No obvious difference in the expression of CGRP between the two groups was found. In conclusion, periosteum may play an important role in the cortical bone resorption in osteoporotic rats and this pathological process may be regulated by the sympathetic nervous system.

Performance measurement and continuous improvement : are they linked to manufacturing strategy?

To maintain or achieve competitiveness and profitability, a manufacturing firm or enterprise must respond to a range of challenges, including rapid improvements in technology; declining employment and output; globalisation of markets and environmental requirements. In addition, substantial changes in government policy have had important impacts in many countries, as have the increasing levels of global trade. Manufacturing enterprises need to have a clear understanding of what their customers want and why customers purchase their products rather than purchase from their competitors. They need to fully understand the aims of the business in terms of its customers, market segments, product attributes, geographical markets and performance. Continuous Improvement (CI) methods have become widely adopted and regarded as providing an important component of increased company competitiveness. This article examines the extent to which continuous improvement activities have contributed to the different areas of business performance.

Modelling the process of learning in economics

Student learning research literature has shown that students' learning approaches are influenced by the learning context (Evans, Kirby, & Fabrigar, 2003). Of the many contextual factors, assessment has been found to have the most important influence on the way students go about learning. For example, assessment that is perceived to required a low level of cognitive abilities will more likely elicit a learning approach that concentrate on reproductive learning activities. Moreover, assessment demand will also interact with learning approach to determine academic performance. In this paper an assessment specific model of learning comprising presage, process and product variables (Biggs, 2001) was proposed and tested against data obtained from a sample of introductory economics students (n=434). The model developed was used to empirically investigate the influence of learning inputs and learning approaches on academic performances across assessment types (essay assignment, multiple choice question exam and exam essay). By including learning approaches in the learning model, the mechanism through which learning inputs determine academic performance was examined. Methodological limitations of the study will also be discussed.

Narratives of mitigation : sentencing Indigenous criminal defendants in South Australia’s Higher Courts

In their statistical analyses of higher court sentencing in South Australia, Jeffries and Bond (2009) found evidence that Indigenous offenders were treated more leniently than non-Indigenous offenders, when they appeared before the court under similar numerical circumstances. Using a sample of narratives for criminal defendants convicted in South Australia’s higher courts, the current article extends Jeffries and Bond’s (2009) prior statistical work by drawing on the ‘focal concerns’ approach to establish whether, and in what ways, Indigeneity comes to exert a mitigating influence over sentencing. Results show that the sentencing stories of Indigenous and non-Indigenous offenders differed in ways that may have reduced assessments of blameworthiness and risk for Indigenous defendants. In addition, judges highlighted a number of Indigenous-specific constraints that potentially could result in imprisonment being construed as an overly harsh and costly sentence for Indigenous offenders.

Rethinking regional green space networks in China

Ecological networks are often represented as utopian webs of green meandering through cities, across states, through regions and even across a country (Erickson, 2006, p.28; Fabos, 2004, p.326; Walmsley, 2006). While this may be an inspiring goal for some in developed countries, the reality may be somewhat different in developing countries. China, in its shift to urbanisation and suburbanisation, is also being persuaded to adjust its planning schemes according to these aspirational representations of green spaces (Yu et al, 2006, p.237; Zhang and Wang, 2006, p.455). The failure of other countries to achieve regional goals of natural and cultural heritage protection on the ground in this way (Peterson et al, 2007; Ryan et al, 2006; von Haaren and Reich, 2006) suggests that there may be flaws in the underpinning concepts that are widely circulated in North American and Western European literature (Jongman et al, 2004; Walmsley, 2006). In China, regional open space networks, regional green infrastructure or regional ecological corridors as we know them in the West, are also likely to be problematic, at least in the foreseeable future. Reasons supporting this view can be drawn from lessons learned from project experience in landscape planning and related fields of study in China and overseas. Implementation of valuable regional green space networks is problematic because: • the concept of region as a spatial unit for planning green space networks is ambiguous and undefinable for practical purposes; • regional green space networks traditionally require top down inter-governmental cooperation and coordination which are generally hampered by inequalities of influence between and within government agencies; • no coordinating body with funding powers exists for regional green space development and infrastructure authorities are still in transition from engineering authorities; • like other infrastructure projects, green space is likely to become a competitive rather than a complementary resource for city governments; • stable long-term management, maintenance and uses of green space networks must fit into a ‘family’ social structure rather than a ‘public good’ social structure, particularly as rural and urban property rights are being re-negotiated with city governments; and • green space provision is a performance indicator of urban improvement in cities within the city hierarchy and remains quantitatively-based (land area, tree number and per capita share) rather than qualitatively-based with local people as the focus.

Interleaved PC-OFDM to reduce peak-to-average power ratio

Parallel combinatory orthogonal frequency division multiplexing (PC-OFDM yields lower maximum peak-to-average power ratio (PAR), high bandwidth efficiency and lower bit error rate (BER) on Gaussian channels compared to OFDM systems. However, PC-OFDM does not improve the statistics of PAR significantly. In this chapter, the use of a set of fixed permutations to improve the statistics of the PAR of a PC-OFDM signal is presented. For this technique, interleavers are used to produce K-1 permuted sequences from the same information sequence. The sequence with the lowest PAR, among K sequences is chosen for the transmission. The PAR of a PC-OFDM signal can be further reduced by 3-4 dB by this technique. Mathematical expressions for the complementary cumulative density function (CCDF)of PAR of PC-OFDM signal and interleaved PC-OFDM signal are also presented.

Exercise-induced energy expenditure : implications for exercise prescription and obesity

Objective: Walking is commonly recommended to help with weight management. We measured total energy expenditure (TEE) and its components to quantify the impact of increasing exercise-induced energy expenditure (ExEE) on other components of TEE. Methods: Thirteen obese women underwent an 8-week walking group intervention. TEE was quantified using doubly labeled water, ExEE was quantified using heart rate monitors, daily movement was assessed by accelerometry and resting metabolic rate was measured using indirect calorimetry. Results: Four of the 13 participants achieved the target of 1500 kcal wk−1 of ExEE and all achieved 1000 kcal wk−1. The average ExEE achieved by the group across the 8 weeks was 1434 ± 237 kcal wk−1. Vigorous physical activity, as assessed by accelerometry, increased during the intervention by an average of 30 min per day. Non-exercise activity thermogenesis (NEAT) decreased, on average, by 175 kcal d−1 (−22%) from baseline to the intervention and baseline fitness was correlated with change in NEAT. Conclusions: Potential alterations in non-exercise activity should be considered when exercise is prescribed. The provision of appropriate education on how to self-monitor daily activity levels may improve intervention outcomes in groups who are new to exercise. Practice implications: Strategies to sustain incidental and light physical activity should be offered to help empower individuals as they develop and maintain healthy and long-lasting lifestyle habits.

Developing a hybrid expert system program to aid in the design of plastic injection molding process

Experts in injection molding often refer to previous solutions to find a mold design similar to the current mold and use previous successful molding process parameters with intuitive adjustment and modification as a start for the new molding application. This approach saves a substantial amount of time and cost in experimental based corrective actions which are required in order to reach optimum molding conditions. A Case-Based Reasoning (CBR) System can perform the same task by retrieving a similar case which is applied to the new case from the case library and uses the modification rules to adapt a solution to the new case. Therefore, a CBR System can simulate human e~pertise in injection molding process design. This research is aimed at developing an interactive Hybrid Expert System to reduce expert dependency needed on the production floor. The Hybrid Expert System (HES) is comprised of CBR, flow analysis, post-processor and trouble shooting systems. The HES can provide the first set of operating parameters in order to achieve moldability condition and producing moldings free of stress cracks and warpage. In this work C++ programming language is used to implement the expert system. The Case-Based Reasoning sub-system is constructed to derive the optimum magnitude of process parameters in the cavity. Toward this end the Flow Analysis sub-system is employed to calculate the pressure drop and temperature difference in the feed system to determine the required magnitude of parameters at the nozzle. The Post-Processor is implemented to convert the molding parameters to machine setting parameters. The parameters designed by HES are implemented using the injection molding machine. In the presence of any molding defect, a trouble shooting subsystem can determine which combination of process parameters must be changed iii during the process to deal with possible variations. Constraints in relation to the application of this HES are as follows. - flow length (L) constraint: 40 mm < L < I 00 mm, - flow thickness (Th) constraint: -flow type: - material types: I mm < Th < 4 mm, unidirectional flow, High Impact Polystyrene (HIPS) and Acrylic. In order to test the HES, experiments were conducted and satisfactory results were obtained.

Pretreatment malnutrition and quality of life - association with prolonged length of hospital stay among patients with gynecological cancer: A cohort study

Background Length of hospital stay (LOS) is a surrogate marker for patients' well-being during hospital treatment and is associated with health care costs. Identifying pretreatment factors associated with LOS in surgical patients may enable early intervention in order to reduce postoperative LOS. Methods This cohort study enrolled 157 patients with suspected or proven gynecological cancer at a tertiary cancer centre (2004-2006). Before commencing treatment, the scored Patient Generated - Subjective Global Assessment (PG-SGA) measuring nutritional status and the Functional Assessment of Cancer Therapy-General (FACT-G) scale measuring quality of life (QOL) were completed. Clinical and demographic patient characteristics were prospectively obtained. Patients were grouped into those with prolonged LOS if their hospital stay was greater than the median LOS and those with average or below average LOS. Results Patients' mean age was 58 years (SD 14 years). Preoperatively, 81 (52%) patients presented with suspected benign disease/pelvic mass, 23 (15%) with suspected advanced ovarian cancer, 36 (23%) patients with suspected endometrial and 17 (11%) with cervical cancer, respectively. In univariate models prolonged LOS was associated with low serum albumin or hemoglobin, malnutrition (PG-SGA score and PG-SGA group B or C), low pretreatment FACT-G score, and suspected diagnosis of cancer. In multivariable models, PG-SGA group B or C, FACT-G score and suspected diagnosis of advanced ovarian cancer independently predicted LOS. Conclusions Malnutrition, low quality of life scores and being diagnosed with advanced ovarian cancer are the major determinants of prolonged LOS amongst gynecological cancer patients. Interventions addressing malnutrition and poor QOL may decrease LOS in gynecological cancer patients.

Examination of the latent structure of the psychological sense of school membership scale

Despite its widespread use, there has been limited examination of the underlying factor structure of the Psychological Sense of School Membership (PSSM) scale. The current study examined the psychometric properties of the PSSM to refine its utility for researchers and practitioners using a sample of 504 Australian high school students. Results from exploratory and confirmatory factor analyses indicated that the PSSM is a multidimensional instrument. Factor analysis procedures identified three factors representing related aspects of students’ perceptions of their school membership: caring relationships, acceptance, and rejection

Creative cities : clash and emergence

the creative city is one that builds ‘clusters of clusters’ to enable the self-management of complexity, the emergence of new ideas, and the growth of knowledge. Clash and difference is what allows for change and innovation.