Selected elements of housing affordability impacting otherwise potentially sustainable communities

It is widely held that strong relationships exist between housing, economic status, and well being. Therefore, recent events emerging from the United States, culminating in widespread housing stock surpluses in that country and others, threaten to destabilise many aspects related to individuals and community. However, despite global impact, the position of housing demand and supply is not consistent. The Australian position provides a strong contrast whereby continued strong housing demand generally remains a critical issue affecting the socio-economic landscape. Underpinned by strong levels of immigration, and further buoyed by sustained historically low interest rates, increasing income levels, and increased government assistance for first home buyers, this strong housing demand ensures elements related to housing affordability continue to gain prominence. A significant, but less visible factor impacting housing affordability – particularly new housing development – relates to holding costs. These costs are in many ways “hidden” and cannot always be easily identified. Although it is only one contributor, the nature and extent of its impact requires elucidation. In its simplest form, it commences with a calculation of the interest or opportunity cost of land holding. However, there is significantly more complexity for major new developments - particularly greenfield development. Analysis suggests that even small shifts in primary factors impacting holding costs can appreciably affect housing affordability. Those factors of greatest significance not only include interest rates and the rate of inflation, but even less apparent factors such as the regulatory assessment period. These are not just theoretical concepts but real, measurable price drivers. Ultimately, the real impact is felt by the one market segment whom can typically least afford it – new home, first home buyers. They can be easily pushed out of affordability. This paper suggests the stability and sustainability of growing, new communities require this problem to be acknowledged and accurately identified if the well being of such communities is to be achieved.

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.

Role of corporate governance in mitigating the selective disclosure of executive stock option information

We examine the nature and extent of statutory executive stock option (ESO) disclosures by Australian listed companies over the 2001 to 2004 period, and the influence of corporate governance mechanisms on these disclosures. Our results show a progressive increase in overall compliance from 2001 to 2004. However, despite the improved compliance, the results reveal managements’ continued reluctance to disclose more sensitive ESO information. Factors associated with good internal governance, including board independence, audit committee independence and effectiveness, and compensation committee independence and effectiveness are found to contribute to improved compliance. Similarly, certain external governance factors are associated with improved disclosure, including external auditor quality, shareholder activism (as proxied by companies identified as poor performers by the Australian Shareholders’ Association), and regulatory intervention.

The relationship between implied and realized volatility : evidence from the Australian stock index option market

This paper examines the relationship between the volatility implied in option prices and the subsequently realized volatility by using the S&P/ASX 200 index options (XJO) traded on the Australian Stock Exchange (ASX) during a period of 5 years. Unlike stock index options such as the S&P 100 index options in the US market, the S&P/ASX 200 index options are traded infrequently and in low volumes, and have a long maturity cycle. Thus an errors-in-variables problem for measurement of implied volatility is more likely to exist. After accounting for this problem by instrumental variable method, it is found that both call and put implied volatilities are superior to historical volatility in forecasting future realized volatility. Moreover, implied call volatility is nearly an unbiased forecast of future volatility.

Effects of transportation accessibility on residential property values: Application of spatial hedonic price model in Seoul, South Korea, metropolitan area

A number of studies have focused on estimating the effects of accessibility on housing values by using the hedonic price model. In the majority of studies, estimation results have revealed that housing values increase as accessibility improves, although the magnitude of estimates has varied across studies. Adequately estimating the relationship between transportation accessibility and housing values is challenging for at least two reasons. First, the monocentric city assumption applied in location theory is no longer valid for many large or growing cities. Second, rather than being randomly distributed in space, housing values are clustered in space—often exhibiting spatial dependence. Recognizing these challenges, a study was undertaken to develop a spatial lag hedonic price model in the Seoul, South Korea, metropolitan region, which includes a measure of local accessibility as well as systemwide accessibility, in addition to other model covariates. Although the accessibility measures can be improved, the modeling results suggest that the spatial interactions of apartment sales prices occur across and within traffic analysis zones, and the sales prices for apartment communities are devalued as accessibility deteriorates. Consistent with findings in other cities, this study revealed that the distance to the central business district is still a significant determinant of sales price.

Application of reinforcement learning in an open railway access market price negotiation

In an open railway access market price negotiation, it is feasible to achieve higher cost recovery by applying the principles of price discrimination. The price negotiation can be modeled as an optimization problem of revenue intake. In this paper, we present the pricing negotiation based on reinforcement learning model. A negotiated-price setting technique based on agent learning is introduced, and the feasible applications of the proposed method for open railway access market simulation are discussed.

Momentum and seasonality in Chinese stock markets

In this paper, we follow Jegadeesh and Titman's (1993, Journal of Finance) approach to examine 25 momentum/contrarian trading strategies using monthly stock returns in China for the period from 1994 to 2007. Our results suggest that there is no momentum profitability in any of the 25 strategies. In contrast, there is some evidence of reversal effects where the past winners become losers and past losers become winners afterward. The contrarian profit is statistically significant for the strategies using short formation and holding periods, especially for the formation periods of 1 to 3 months and the holding periods of 1 to 3 months. The contrarian strategies can generate about 12% per annum on average. Moreover, we follow Heston and Sadka (2008, Journal of Financial Economics) to investigate where there is any seasonal pattern in the cross-sectional variation of average stock returns in our momentum/contrarian strategies. There is no evidence of any seasonal pattern, and the results are robust to different formation and holding periods.

Assessing genetic diversity in cultured aquatic species : the Sydney Rock Oyster (Saccostrea glomerata) stock improvement program as a model

Genetic variation is the resource animal breeders exploit in stock improvement programs. Both the process of selection and husbandry practices employed in aquaculture will erode genetic variation levels overtime, hence the critical resource can be lost and this may compromise future genetic gains in breeding programs. The amount of genetic variation in five lines of Sydney Rock Oyster (SRO) that had been selected for QX (Queensland unknown) disease resistance were examined and compared with that in a wild reference population using seven specific SRO microsatellite loci. The five selected lines had significantly lower levels of genetic diversity than did the wild reference population with allelic diversity declining approximately 80%, but impacts on heterozygosity per locus were less severe. Significant deficiencies in heterozygotes were detected at six of the seven loci in both mass selected lines and the wild reference population. Against this trend however, a significant excess of heterozygotes was recorded at three loci Sgo9, Sgo14 and Sgo21 in three QX disease resistant lines (#2, #5 and #13). All populations were significantly genetic differentiated from each other based on pairwise FST values. A neighbour joining tree based on DA genetic distances showed a clear separation between all culture and wild populations. Results of this study show clearly, that the impacts of the stock improvement program for SRO has significantly eroded natural levels of genetic variation in the culture lines. This could compromise long-term genetic gains and affect sustainability of the SRO breeding program over the long-term.