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Real estate is one of the largest and most complex markets globally. Dynamic consumer behaviour, such as that which results in the rapid rate of urbanisation, has caused these complexities, and thus, understanding and predicting these market behavioural patterns has become a challenge. As a result, many countries have failed to develop adequate policies to mitigate the risk of market uncertainties and abnormal behaviours that result in issues such as the affordable housing crisis. However, many global institutions still struggle to understand the real estate market using only the currently available tools; thus, many researchers are now testing more innovative cutting-edge technologies to help manage this complex market. Therefore, this research explores how machine learning (ML) and artificial intelligence (AI) can produce relatively valuable and accurate insights into the problems of the market compared to the traditional methods of understanding the complex housing market in Australia. Just as many other industries are now deploying AI and ML in decision-making processes, the real estate industry is also embracing ML to improve the efficiency and effectiveness of many processes. Further, the inability of traditional analytical methodologies to deliver better insights into the ever-growing complexity of the housing markets has encouraged AI and ML to do the job. The development of big data technologies and the availability of massive data pools have enabled AI and ML to solve complicated problems while producing more accurate results. Thus, this research productively addresses the complexity of the Australian housing market using AI and ML and helps decision-makers manage associated issues. The research consists of three studies: the first focuses on overall Australia, and the other two focus on Queensland, Australia. [...], Thesis (PhD Doctorate), Doctor of Philosophy (PhD), Dept Account,Finance & Econ, Griffith Business School, Full Text

The importance of infrastructure to society cannot be over emphasised because it is needed by individuals, communities, and societies. For instance, communities cannot be classified as developed in the absence of infrastructure development. In real estate parlance, the provision of infrastructure is a necessary condition for residential (housing) growth and development. Conversely, there can be no infrastructure planning without incorporating the residential needs of the population. Adequate provision of infrastructure in the form of roads, bridges, energy, electricity, and utilities contributes to the quality of life or the improvement in the welfare of the residential population. Additionally, it is expected that when infrastructure is provided, there will be cash inflow or revenue to cover the cost of the infrastructure. This latter argument is important for the private sector’s involvement in major infrastructure, such as toll roads. Against this backdrop, infrastructure has the twin benefits of social welfare and profit generation. In this thesis, the values of infrastructure and housing in Australia are examined. These two assets have been considered in this study due to the argument that infrastructure and housing are complementary, and they may also belong to the same asset class under the following conditions: (1) Infrastructure and housing share common attributes (2) The investment outlay of the housing project is huge. (3) For residential (housing) development to take place, infrastructure development is always incorporated. This is because, residents need roads, bridges, among others for a better quality of life. The thesis argues that the value of an asset depends on the accuracy of the valuation method and other existing factors. The valuation method could be traditional or innovative, whereas the existing factors may be internal (inherent) such as the attributes of the asset or external such as a major sporting event. In this thesis, three studies hav, Thesis (PhD Doctorate), Doctor of Philosophy (PhD), Dept Account,Finance & Econ, Griffith Business School, Full Text

The dream of owning a home in Australia is far out of reach for many people. Australia needs more private investments to meet the estimated affordable housing demand as the conventional funding sources like bank loans become further restricted. Responsible investment is an emerging potential source of finance for the affordable housing sector. However, the shortage of information on the risks, returns, and impact evidence regarding the affordable housing submarket and the lack of dedicated investment models, make it difficult to attract investors to promote much needed affordable homeownership opportunities in Australia. Therefore, the overriding objectives of this thesis are to reduce the information gap of investors relating to the affordable housing submarkets, and to examine innovative financial models that connect investors with the affordable housing sector in Australia. The underlining hypothesis of this thesis is that the residential housing market in Australia has attributes that are attractive to responsible investors. With these objectives and hypothesis, the thesis examined the following overarching research questions (RQ) under three interrelated studies. RQ1: Why are there differences in risks and returns of residential housing assets in different price cohorts and regions? RQ2: What are the significant characteristics of the affordable housing markets in Australia that are attractive to responsible investors? RQ3: Is shared equity homeownership a viable mechanism to increase the homeownership rate among young and low-income people? Three empirical studies were conducted under each research question., Thesis (PhD Doctorate), Doctor of Philosophy (PhD), Dept Account,Finance & Econ, Griffith Business School, Full Text

Full Text, Thesis (PhD Doctorate), Doctor of Philosophy (PhD), Griffith Business School, Griffith Business School, The purpose of this thesis is to explore important determinants of the implied value inherited in a readily available durable commodity. Under the notion of convenience yield, such a value represents all the benefits that can be enjoyed by the owner of a physical asset. To disentangle the dynamic behaviour of this implied value embedded in the price of physical assets, various measures of scarceness of commodities are identified in this thesis and three interrelated studies are conducted to examine the lead-lag relationships between these measures and the convenience yield. In particular, I examine (1)how current geographical scarcity, represented by a regional supply/demand condition,affects the future convenience yield, (2) whether relative scarcity of a commodity contains valuable predictive information on its convenience yield, and (3) how the perceived level of a convenience yield is related to the second moment of futures price. Taking together, the results of these studies mostly support the presence of statistically significant relationships between the convenience yield and these measures, which can be used for constructing effective inventory and investment strategies.