Accelerating Pseudo-Marginal MCMC using Gaussian Processes

Pseudo-marginal methods such as the grouped independence Metropolis-Hastings (GIMH) and Markov chain within Metropolis (MCWM) algorithms have been introduced in the literature as an approach to perform Bayesian inference in latent variable models. These methods replace intractable likelihood calculations with unbiased estimates within Markov chain Monte Carlo algorithms. The GIMH method has the posterior of interest as its limiting distribution, but suffers from poor mixing if it is too computationally intensive to obtain high-precision likelihood estimates. The MCWM algorithm has better mixing properties, but less theoretical support. In this paper we propose to use Gaussian processes (GP) to accelerate the GIMH method, whilst using a short pilot run of MCWM to train the GP. Our new method, GP-GIMH, is illustrated on simulated data from a stochastic volatility and a gene network model.

New tools for management of phosphine resistance

Phosphine is the primary fumigant used to protect the majority of the world' s grain and a variety of other stored commodities from insect pests. Phosphine is playing an increasingly important role in the protection of commodities for two primary reasons. Firstly, use of the alternative fumigant, methyl bromide, has been sharply curtailed and is tightly regulated due to its role in ozone depletion, and secondly, consumers are becoming increasingly intolerant of contact pesticides. Niche alternatives to phosphine exist, but they suffer from a range of factors that limit their use, including: 1) Limited commercial adoption due to expense or slow mode of action; 2) Poor efficacy due to low toxicity, rapid sorption, limited volatility or high density; 3) Public health concerns due to toxicity to handlers or nearby residents, as well as risk of explosion; 4) Poor consumer acceptance due to toxic residues or smell. These same factors limit the prospects of quickly identifying and deploying a new fumigant. Given that resistance toward phosphine is increasing among insect pests, improved monitoring and management of resistance is a priority. Knowledge of the mode of action of phosphine as well as the mechanisms of resistance may also greatly reduce the effort and expense of identifying synergists or novel replacement compounds.

Convolution: A Woven Sculptural Installation. Catalogue essay

The catalogue essay contextualises the creative practices of Casselle Mountford and Anaheke Matua, in terms of their involvement with the Lines in the Sand Art and Environment festivals on Minjerribah, and in terms of their own operational and ethical processes and ethos. It seeks to express the intertwining and blurring of nature and culture in the traditional methods and idiosyncratic expression of these two artists.

Risk Minimizing Option Pricing in a Semi-Markov Modulated Market

We address risk minimizing option pricing in a semi-Markov modulated market where the floating interest rate depends on a finite state semi-Markov process. The growth rate and the volatility of the stock also depend on the semi-Markov process. Using the Föllmer–Schweizer decomposition we find the locally risk minimizing price for European options and the corresponding hedging strategy. We develop suitable numerical methods for computing option prices.

International Journal of Music Business Research. Special Issue on the Australasian Music Economy

The music business is one of the most international of all the cultural industries. Music, industry practices, and people travel easily across country borders and the major music companies are dominating national music markets across the globe. However, at the same time the music industries in different countries are very idiosyncratic. Music is an ingrained part of a country’s history, its culture and heritage. One aspect of this idiosyncrasy is related to how creatives, audiences and music organizations are affected by and is able to take advantage of the ongoing digitization of society.

Bioavailability aspects of hydrophobic contaminant degradation in soils

This thesis concentrates on bioavailability of organic soil contaminants in the context of bioremediation of soil contaminated with volatile or non-volatile hydrophobic pollutants. Bioavailability and biodegradation was studied from four viewpoints: (i) Improvement of bioavailability and biodegradation of volatile hydrocarbons in contained bioremediation systems at laboratory - and pilot-scale. (ii) Improvement of bioavailability of non-volatile, hydrophobic compounds in such systems. (iii) Biodegradation of a non-volatile hydrophobic compound in soil organic matter in microcosms. (iiii) Bioavailability of nitrogen in an open, full-scale bioremediation system. It was demonstrated that volatility of organic compounds can be controlled by amending the soil with adsorbents. The sorbed hydrocarbons were shown to be available to soil microbiota. As the result, biodegradation of the volatile hydrocarbons was greatly favored at the expense of volatilization. PAH compounds were shown to be mobilized and their bioavailability improved by a hydrophobic, non-toxic additive, vegetable oil. Bioavailability of the PAHs was recorded as an increased toxicity of the soil. In spite of the increased bioavailability, biodegradation of the PAHs decreased. In microcosms simulating boreal forest organic surface soil, PAH-compound (pyrene) was shown to be removed from soil biologically. Therefore hydrophobicity of the substrate does not necessarily mean low availability and biodegradation in organic soil. Finally, in this thesis it was demonstrated that an unsuitable source of nitrogen or its overdose resulted in wasteful spending of this nutrient and even harmful effects on soil microbes. Such events may inhibit rather than promote the bioremediation process in soil.

Mathematical Aspects of Financial Markets with Frictions

Frictions are factors that hinder trading of securities in financial markets. Typical frictions include limited market depth, transaction costs, lack of infinite divisibility of securities, and taxes. Conventional models used in mathematical finance often gloss over these issues, which affect almost all financial markets, by arguing that the impact of frictions is negligible and, consequently, the frictionless models are valid approximations. This dissertation consists of three research papers, which are related to the study of the validity of such approximations in two distinct modeling problems. Models of price dynamics that are based on diffusion processes, i.e., continuous strong Markov processes, are widely used in the frictionless scenario. The first paper establishes that diffusion models can indeed be understood as approximations of price dynamics in markets with frictions. This is achieved by introducing an agent-based model of a financial market where finitely many agents trade a financial security, the price of which evolves according to price impacts generated by trades. It is shown that, if the number of agents is large, then under certain assumptions the price process of security, which is a pure-jump process, can be approximated by a one-dimensional diffusion process. In a slightly extended model, in which agents may exhibit herd behavior, the approximating diffusion model turns out to be a stochastic volatility model. Finally, it is shown that when agents' tendency to herd is strong, logarithmic returns in the approximating stochastic volatility model are heavy-tailed. The remaining papers are related to no-arbitrage criteria and superhedging in continuous-time option pricing models under small-transaction-cost asymptotics. Guasoni, Rásonyi, and Schachermayer have recently shown that, in such a setting, any financial security admits no arbitrage opportunities and there exist no feasible superhedging strategies for European call and put options written on it, as long as its price process is continuous and has the so-called conditional full support (CFS) property. Motivated by this result, CFS is established for certain stochastic integrals and a subclass of Brownian semistationary processes in the two papers. As a consequence, a wide range of possibly non-Markovian local and stochastic volatility models have the CFS property.

Modeling Asymmetries in Financial Data with Multiplicative Error Models

This thesis addresses modeling of financial time series, especially stock market returns and daily price ranges. Modeling data of this kind can be approached with so-called multiplicative error models (MEM). These models nest several well known time series models such as GARCH, ACD and CARR models. They are able to capture many well established features of financial time series including volatility clustering and leptokurtosis. In contrast to these phenomena, different kinds of asymmetries have received relatively little attention in the existing literature. In this thesis asymmetries arise from various sources. They are observed in both conditional and unconditional distributions, for variables with non-negative values and for variables that have values on the real line. In the multivariate context asymmetries can be observed in the marginal distributions as well as in the relationships of the variables modeled. New methods for all these cases are proposed. Chapter 2 considers GARCH models and modeling of returns of two stock market indices. The chapter introduces the so-called generalized hyperbolic (GH) GARCH model to account for asymmetries in both conditional and unconditional distribution. In particular, two special cases of the GARCH-GH model which describe the data most accurately are proposed. They are found to improve the fit of the model when compared to symmetric GARCH models. The advantages of accounting for asymmetries are also observed through Value-at-Risk applications. Both theoretical and empirical contributions are provided in Chapter 3 of the thesis. In this chapter the so-called mixture conditional autoregressive range (MCARR) model is introduced, examined and applied to daily price ranges of the Hang Seng Index. The conditions for the strict and weak stationarity of the model as well as an expression for the autocorrelation function are obtained by writing the MCARR model as a first order autoregressive process with random coefficients. The chapter also introduces inverse gamma (IG) distribution to CARR models. The advantages of CARR-IG and MCARR-IG specifications over conventional CARR models are found in the empirical application both in- and out-of-sample. Chapter 4 discusses the simultaneous modeling of absolute returns and daily price ranges. In this part of the thesis a vector multiplicative error model (VMEM) with asymmetric Gumbel copula is found to provide substantial benefits over the existing VMEM models based on elliptical copulas. The proposed specification is able to capture the highly asymmetric dependence of the modeled variables thereby improving the performance of the model considerably. The economic significance of the results obtained is established when the information content of the volatility forecasts derived is examined.

Pairing technology and meals: A contextual enquiry in the family household

Recent research about technology during mealtime has been mostly concerned with developing technology rather than creating a deeper understanding of the context of family mealtimes and associated practices. In this paper, we present a two-phase study discussing how the temporal, social, and food related features are intertwined with technology use during mealtimes. Our findings show how people differentiate technology usage during weekday meals, weekend meals, and among different meals of the day. We identify and analyse prototypical situations ranging from the use of arbitrary technologies while eating solitary, to idiosyncratic family norms and practices associated with shared technologies. We discuss the use of mealtime technology to create appropriate ambience for meals with guests and demonstrate how technology can be used to complement food in everyday meals and special occasions. Our findings make recommendation about the need for HCI research to recognize the contextual nature of technology usage during family mealtimes and to adopt appropriate design strategies.

Funktionaalinen Transitioteoria : Hallinto, Instituutiot ja Oikeusjärjestys Venäjällä

Functional transition theory: administration, legal order and institutions in Russia This dissertation examines some of the salient characteristics of Russia that are deemed to have impeded the growth of its economy and investments in particular. These characteristics are the volatility of the administrative and legal systems, corruption, and the perceived irrationality and difference in the operating environment in comparison with European conditions. The dissertation is one of the first studies on Russia that approaches the subject from the perspective of comprehensive social scientific theories. The study is based on the structural functionalistic theory, which is widely used in the social sciences. Adopting a sufficiently ambitious theoretical examination will provide a systematic and logical explanation of the characteristics of Russian institutions and ways of operations, such as corruption, that are commonly perceived as inexplicable. The approach adopted in the dissertation sheds light on the history of Russia's development and provides a comparative view of other societies in transition. Furthermore, it suggests recommendations as to how the structures of Russian society could be comprehensively strengthened.

In pursuit of becoming a senior coach: The learning culture for Australian Football League coaches

- Background and Purpose Given the turbulent and highly contested environment in which professional coaches work, a prime concern to coach developers is how coaches learn their craft. Understanding the learning and development of senior coaches (SCs) and assistant coaches (ACs) in the Australian Football League (AFL – the peak organisation for Australian Rules Football) is important to better develop the next generation of performance coaches. Hence the focus of this research was to examine the learning of SC and AC in the AFL. Fundamental to this research was an understanding that the AFL and each club within the league be regarded as learning organisations and workplaces with their own learning cultures where learning takes place. The purpose of this paper was to examine the learning culture for AFL coaches. - Method Five SCs, 6 ACs, and 5 administrators (4 of whom were former coaches) at 11 of the 16 AFL clubs were recruited for the research project. First, demographic data were collected for each participant (e.g. age, playing and coaching experience, development and coach development activities). Second, all participants were involved in one semi-structured interview of between 45 and 90 minutes duration. An interpretative (hierarchical content) analysis of the interview data was conducted to identify key emergent themes. - Results Learning was central to AFL coaches becoming a SC. Nevertheless, coaches reported a sense of isolation and a lack of support in developing their craft within their particular learning culture. These coaches developed a unique dynamic social network (DSN) that involved episodic contact with a number of respected confidantes often from diverse fields (used here in the Bourdieuian sense) in developing their coaching craft. Although there were some opportunities in their workplace, much of their learning was unmediated by others, underscoring the importance of their agentic engagement in limited workplace affordances. - Conclusion The variety of people accessed for the purposes of learning (often beyond the immediate workplace) and the long time taken to establish networks of supporters meant that a new way of describing the social networks of AFL coaches was needed; DSN. However, despite the acknowledged utility of learning from others, all coaches reported some sense of isolation in their learning. The sense of isolation brought about by professional volatility in high-performance Australian Football offers an alternative view on Hodkinson, Biesta and James' attempt in overcoming dualisms in learning.

Asymptotic analysis of option pricing in a Markov modulated market

We address asymptotic analysis of option pricing in a regime switching market where the risk free interest rate, growth rate and the volatility of the stocks depend on a finite state Markov chain. We study two variations of the chain namely, when the chain is moving very fast compared to the underlying asset price and when it is moving very slow. Using quadratic hedging and asymptotic expansion, we derive corrections on the locally risk minimizing option price.

Observation of sea-salt fraction in sub-100 nm diameter particles at Cape Grim

Volatility-hygroscopicity tandem differential mobility analyzer measurements were used to infer the composition of sub-100 nm diameter Southern Ocean marine aerosols at Cape Grim in November and December 2007. This study focuses on a short-lived high sea spray aerosol (SSA) event on 7–8 December with two externally mixed modes in the Hygroscopic Growth Factor (HGF) distributions (90% relative humidity (RH)), one at HGF > 2 and another at HGF~1.5. The particles with HGF > 2 displayed a deliquescent transition at 73–75% RH and were nonvolatile up to 280°C, which identified them as SSA particles with a large inorganic sea-salt fraction. SSA HGFs were 3–13% below those for pure sea-salt particles, indicating an organic volume fraction (OVF) of up to 11–46%. Observed high inorganic fractions in sub-100 nm SSA is contrary to similar, earlier studies. HGFs increased with decreasing particle diameter over the range 16–97 nm, suggesting a decreased OVF, again contrary to earlier studies. SSA comprised up to 69% of the sub-100 nm particle number, corresponding to concentrations of 110–290 cm−3. Air mass back trajectories indicate that SSA particles were produced 1500 km, 20–40 h upwind of Cape Grim. Transmission electron microscopy (TEM) and X-ray spectrometry measurements of sub-100 nm aerosols collected from the same location, and at the same time, displayed a distinct lack of sea salt. Results herein highlight the potential for biases in TEM analysis of the chemical composition of marine aerosols.

The ambient aerosol characterization during the prescribed bushfire season in Brisbane 2013

Prescribed burnings are conducted in Queensland each year from August until November aiming to decrease the impact of bushfire hazards and maintain the health of vegetation. This study reports chemical characteristics of the ambient aerosol, with a focus on source apportionment of the organic aerosol (OA)fraction, during the prescribed biomass burning (BB) season in Brisbane 2013. All measurements were conducted within the International Laboratory for Air Quality and Health (ILAQH) located in Brisbane’s Central Business District. Chemical composition, degree of ageing and the influence of BB emission on the air quality of central Brisbane were characterized using a compact Time of Flight Aerosol Mass Spectrometer (cToF-AMS). AMS loadings were dominated by OA (64 %), followed by, sulfate (17 %), ammonium (14 %) and nitrates (5 %). Source apportionment was applied on the AMS OA mass spectra via the multilinear engine solver (ME-2) implementation within the recently developed Source Finder (SoFi) interface. Six factors were extracted including hydrocarbon-like OA (HOA), cooking-related OA (COA), biomass burning OA (BBOA), low-volatility oxygenated OA (LV-OOA), semivolatile oxygenated OA (SV-OOA), and nitrogen-enriched OA (NOA). The aerosol fraction that was attributed to BB factor was 9 %, on average over the sampling period. The high proportion of oxygenated OA (72 %), typically representing aged emissions, could possess a fraction of oxygenated species transformed from BB components on their way to the sampling site.

Testing against changing correlation

A test for time-varying correlation is developed within the framework of a dynamic conditional score (DCS) model for both Gaussian and Student t-distributions. The test may be interpreted as a Lagrange multiplier test and modified to allow for the estimation of models for time-varying volatility in the individual series. Unlike standard moment-based tests, the score-based test statistic includes information on the level of correlation under the null hypothesis and local power arguments indicate the benefits of doing so. A simulation study shows that the performance of the score-based test is strong relative to existing tests across a range of data generating processes. An application to the Hong Kong and South Korean equity markets shows that the new test reveals changes in correlation that are not detected by the standard moment-based test.