Spread ALOHA has become one of the advanced multiple access techniques promising several advantages over existing conventional and spread spectrum based wireless systems. Spread ALOHA is currently recognised as a simplified wireless multiple access system which provides a higher bandwidth and may accommodate high number of users. This thesis investigates the employment of a unique spreading code in conjunction with Spread ALOHA as opposed to the common method of employing distinct spreading codes for all users on the communication channel. This feature of Spread ALOHA would eliminate the limitation on the number of users imposed by finding sufficient orthogonal spreading codes, and moreover it would simplify the system and reduce the receiver complexity. In this research I have investigated the state of the art on this topic, and I have modelled and simulated a Single Code Spread ALOHA system together with a conventional CDMA ALOHA system in order to analyse and compare the performance of both systems. This study has shown the viability of employing single code in Spread ALOHA systems, and hence eliminating what is considered a limiting factor in other systems such as CDMA. The performance of this proposed system is comparable with that of CDMA; however the selection of suitable PN codes is essential. The parametric study in this work was aimed to find optimum performance criteria for the Spread ALOHA system. all users on the spread spectrum system to have equal average; received power levels. / Master of Engineering (Hons)

The goal of this study is to assess the potential of using bench-scale fire testing to screen materials for the Steiner tunnel fire test. It is hypothesized that the chemical and physical changes made to a material to improve its fire performance in small scale fire tests will have a predictable response in the Steiner tunnel. This hypothesis is based on the observation that fire test results can, in some cases, provide insight on a material's relative fire hazard, and the assumption that the relative hazard should be consistent across scale. The ASTM E84 Steiner tunnel test provides a relative ranking of material hazard in two categories. The horizontal Flame Spread Index (FSI) is used to rank the flame hazard of a material, and the Smoke Developed Index (SDI) is used to rank the smoke hazard of a material. Two fire tests are proposed to independently assess each hazard at the bench-scale. The ASTM E1354 cone calorimeter test measures a material's open-flaming heat release rate; it is proposed that the cone calorimeter test can be used to assess a material's relative flame hazard. The ISO 5659-2 smoke density chamber test measures a material's closed-environment smoke development; it is proposed that the smoke density chamber test can be used to assess a material's relative smoke hazard. The material selected for this study is fire-retarded sprayed polyurethane foam (FRSPF) insulation. Specific details of the foam chemistry, fire retardants, and the manufacturer are confidential. Generally, the foam can be described as medium-density (approximately 2 lbs/ft³), closed-celled, and semi-rigid. The fire retardant additives are comprised of differing ratios and concentrations of phosphorous- and halogen-containing compounds. A series of 30 Steiner tunnel tests is conducted on 20 different formulations. Repeated testing is conducted on several formulations in order to assess variability in the Steiner tunnel test results. Cone calorimeter and smoke density chamber tests are conducted on a subset of those formulations, in sets of 3-5 tests per formulation. Key performance indicators are identified from each fire test, relationships between those indicators are examined, and correlations are presented where strong relationships are apparent. Empirical prediction models are proposed for FSI and SDI based on the success rate of prediction, and minimization of error between experimental (measured) and modelled (predicted) results. It is concluded that for the materials tested in this study, there is sufficient evidence of consistency in relative performance to recommend bench-scale screening tests as a cost-effective alternative to repeated Steiner tunnel testing.

Previous studies (e.g. Benston and Hagerman, 1974, Bagehot, 1971 and Stoll, 1978) suggest that the bid-ask spread consists of three components: asymmetric information cost, inventory holding cost, and order processing cost. Other literature (e.g. Brock and Kleidon, 1992, Hef-lin et al, 2007, and McInish and Van Ness, 2002) reports that the bid-ask spread varies during a trading day following a U-shaped pattern. One explanation for this observation is that it is the result of changes in information asymmetry costs over the trading hours, assuming the other costs are fixed. However, no empirical study directly measures how information asym-metry changes over the trading day. We explore how this measure relates to the spread as well as the quote depth.<p> Our research divides a trading day into 13 half-hour trading intervals and measures in-formation asymmetry during each interval following the model developed by Madhavan and Smidt (1991) and Noronha et al (1996). Their model can directly estimate the level of infor-mation asymmetry in each interval. This enables us to observe the intraday pattern of infor-mation asymmetry directly and compare it to the patterns of the spread and the quote depth. Furthermore, we test the relationship between the spread and the information asymmetry and the relationship between the depth and the information asymmetry in a dynamic context to see how market makers manage information risk over trading hours.<p> We find that the risk of information asymmetry varies significantly during the trading day. There is a large drop over the first interval, and another large drop over the last interval, with smaller fluctuations over the remaining intervals. Moreover, we show that the spread is consistent with an L-shaped pattern as opposed to the U-shaped pattern proposed by previous studies while the depth is increasing throughout the 13 trading intervals. Furthermore, we ob-serve that the variations of the spread and the depth are respectively positively and negatively related to the intraday variations in the degree of information asymmetry across the trading intervals. In particular, a large decline in information asymmetry at the beginning of the day is associated with a large reduction in the spread, whereas a large decline in information asymmetry at the end of the day is associated with a large increase in the quote depth. This emphasises the importance of studying both measures of liquidity simultaneously.

This thesis includes three chapters on electricity and natural gas prices. In the first chapter, we give a brief introduction to the characteristics of power prices and propose a mean reversion jump diffusion model, in which jump intensity depends on temperature data and overall system load, to model electricity prices. Compared to the models used in the literature, we find the model proposed in this chapter is better to capture the tail behavior in the electricity prices. In the second chapter, we use the model proposed in the first chapter to simulate the spark spread option and value the power generations. In order to simulate power generation, we first propose and estimate mean reversion jump diffusion model for natural gas prices, in which jump intensity is defined as a function of temperature and storage. Combing the model with the electricity models in chapter 1, we find that the value of power generation is closer to the real value of the power plants as reflected in the recent market transaction than one obtains from many other models used in literature. The third chapter investigates extremal dependence among the energy market. We find a tail dependence that exceeds the Pearson correlation ρ, which means the traditional Pearson correlation is not appropriate to model tail behavior of oil, natural gas and electricity prices. However, asymptotic dependence is rejected in all pairs except Henry Hub gas return and Houston Ship Channel gas return. We also find that extreme value dependence in energy market is stronger in bull market than that in bear market due to the special characteristics in energy market, which conflicts the accepted wisdom in equity market that tail correlation is much higher in periods of volatile markets from previous literature.

Previous studies (e.g. Benston and Hagerman, 1974, Bagehot, 1971 and Stoll, 1978) suggest that the bid-ask spread consists of three components: asymmetric information cost, inventory holding cost, and order processing cost. Other literature (e.g. Brock and Kleidon, 1992, Hef-lin et al, 2007, and McInish and Van Ness, 2002) reports that the bid-ask spread varies during a trading day following a U-shaped pattern. One explanation for this observation is that it is the result of changes in information asymmetry costs over the trading hours, assuming the other costs are fixed. However, no empirical study directly measures how information asym-metry changes over the trading day. We explore how this measure relates to the spread as well as the quote depth.<p> Our research divides a trading day into 13 half-hour trading intervals and measures in-formation asymmetry during each interval following the model developed by Madhavan and Smidt (1991) and Noronha et al (1996). Their model can directly estimate the level of infor-mation asymmetry in each interval. This enables us to observe the intraday pattern of infor-mation asymmetry directly and compare it to the patterns of the spread and the quote depth. Furthermore, we test the relationship between the spread and the information asymmetry and the relationship between the depth and the information asymmetry in a dynamic context to see how market makers manage information risk over trading hours.<p> We find that the risk of information asymmetry varies significantly during the trading day. There is a large drop over the first interval, and another large drop over the last interval, with smaller fluctuations over the remaining intervals. Moreover, we show that the spread is consistent with an L-shaped pattern as opposed to the U-shaped pattern proposed by previous studies while the depth is increasing throughout the 13 trading intervals. Furthermore, we ob-serve that the variations of the spread and the depth are respectively positively and negatively related to the intraday variations in the degree of information asymmetry across the trading intervals. In particular, a large decline in information asymmetry at the beginning of the day is associated with a large reduction in the spread, whereas a large decline in information asymmetry at the end of the day is associated with a large increase in the quote depth. This emphasises the importance of studying both measures of liquidity simultaneously.

The issue of depositary receipt gets more attention in investors in recent year because of the explosion of Taiwan Depositary Receipt (hereafter, TDR) in Taiwan. The depositary receipts should equal to the value of primary listing stocks because they are represent the same value to a company. Therefore, we would discuss the price relationship between TDR and the primary listing stock it represents at first. In addition, because all the TDRs in Taiwan have the price spread (i.e. the price difference between TDRs and the primary listing stocks) with its original stocks, we discuss what the reasons to cause the price spread from a point of market segment. And we find it is because of liquidity, demand, information asymmetry, and stock price manipulation to lead to the price spread. After we takes market emotion into account, the market index has significant influence on price spread and individual investors also have a large influence on price spread. Finally, we try to find that whether the market has the arbitrage opportunity from the price spread after we consider the transaction cost. And the result shows that when TDR is in discount, it really has the arbitrage opportunity in market after we use the close price as the transaction price. Furthermore, if we use the open price in the next day as the transaction price, it still has excess return in market, but the profit will be lower than the strategy using the close price as the transaction price.

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The bid-ask spread costs consist of three components, which include order processing costs, inventory-holding costs, and adverse selection costs. In this paper, we model the inventory-holding costs of the bid-ask spread by option hedging. Theinventory-holding costs are hedged by call or put option positions. Since trades deal with the adverse selection traders are unobservable. We treat it as a latent variable, and Expected-Maximization (EM) algorithm are applied to estimate the related parameters of the model. Simulation studies are performed for several different models. Empirical results of NYSE high frequency data show that the proposed model are obtain appropriate parameter estimation when the returns satisfied normality assumption.

The asset combination of the multi-target credit derivatives and the pricing model of credit risk, the dependence in credit default in credit derivatives is an important connection factor. Copula functions represent a methodology which has recently become the most significant new tool to handle in a flexible way the comovement between markets, risk factors and other relevant variables studied in finance. Besides, Copula functions have been applied to the solution of the need to reach effective diversification has led to new investment products, bound to exploit the credit risk features of the assets. It is particularly for the evaluation of these new products, such as securitized assets (asset-backed securities, such as CDO and the like) and basked credit derivatives (nth to default options) that the need to account for comovement among non-normally distributed variabes has become an unavoidable task. This article attempts utilizes the credit yield spread between the non-risk bond and the common corporation bond in the market and using Copula functions to make up the relation composition of asset combination. Then, penetrates through the Monte-Carlo Simulation to estimated the default time of asset combination and princing the credit risk spread in the tranche of the Collateralized Debt Obligation (CDO). Besides, this article aims at the asset default recovery rate, the discount rate and the correlation coefficient of asset combination and so on three factors makes the sensitivity analysis, we find that the most effect of the credit default spread in the Collateralized Debt Obligation is asset default recovery rate, next is the correlation coefficient of asset combination, the influence of discount rate is not obvious.

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