Separation and hedging results with state-contingent production

A state-contingent model of production under uncertainty is developed and compared with more traditional models of production under uncertainty. Producer behaviour with both production and price risk, in the presence and in the absence of futures and forward markets, is analysed in this state-contingent framework. Conditions for the optimal hedge to be positive or negative are derived. We also show that, under plausible conditions, a risk-averse producer facing price uncertainty and the ability to hedge price risk will never willingly adopt a nonstochastic technology. New separation results, which hold in the presence of both price and production risk, are then developed. These separation results generalize Townsend's spanning results by reducing the number of necessary forward markets by one.

Potential demand for hedging by Australian wheat producers

The potential for hedging Australian wheat with the new Sydney Futures Exchange wheat contract is examined using a theoretical hedging model parametised from previous studies. The optimal hedging ratio for an 'average' wheat farmer was found to be zero under reasonable assumptions about transaction costs and based on previously published measures of risk aversion. The estimated optimal hedging ratios were found by simulation to be quite sensitive to assumptions about the degree of risk aversion. If farmers are significantly more risk averse than is currently believed, then there is likely to be an active interest in the new futures market.

A hedging point strategy - balancing effluent quality, economy and robustness in the control of wastewater treatment plants

An operational space map is an efficient tool to compare a large number of operational strategies to find an optimal choice of setpoints based on a multicriterion. Typically, such a multicriterion includes a weighted sum of cost of operation and effluent quality. Due to the relative high cost of aeration such a definition of optimality result in a relatively high fraction of the effluent total nitrogen in the form of ammonium. Such a strategy may however introduce a risk into operation because a low degree of ammonium removal leads to a low amount of nitrifiers. This in turn leads to a reduced ability to reject event disturbances, such as large variations in the ammonium load, drop in temperature, the presence of toxic/inhibitory compounds in the influent etc. Hedging is a risk minimisation tool, with the aim to "reduce one's risk of loss on a bet or speculation by compensating transactions on the other side" (The Concise Oxford Dictionary (1995)). In wastewater treatment plant operation hedging can be applied by choosing a higher level of ammonium removal to increase the amount of nitrifiers. This is a sensible way to introduce disturbance rejection ability into the multi criterion. In practice, this is done by deciding upon an internal effluent ammonium criterion. In some countries such as Germany, a separate criterion already applies to the level of ammonium in the effluent. However, in most countries the effluent criterion applies to total nitrogen only. In these cases, an internal effluent ammonium criterion should be selected in order to secure proper disturbance rejection ability.

Approximate processing of massive continuous quantile queries over high-speed data streams

Quantile computation has many applications including data mining and financial data analysis. It has been shown that an is an element of-approximate summary can be maintained so that, given a quantile query d (phi, is an element of), the data item at rank [phi N] may be approximately obtained within the rank error precision is an element of N over all N data items in a data stream or in a sliding window. However, scalable online processing of massive continuous quantile queries with different phi and is an element of poses a new challenge because the summary is continuously updated with new arrivals of data items. In this paper, first we aim to dramatically reduce the number of distinct query results by grouping a set of different queries into a cluster so that they can be processed virtually as a single query while the precision requirements from users can be retained. Second, we aim to minimize the total query processing costs. Efficient algorithms are developed to minimize the total number of times for reprocessing clusters and to produce the minimum number of clusters, respectively. The techniques are extended to maintain near-optimal clustering when queries are registered and removed in an arbitrary fashion against whole data streams or sliding windows. In addition to theoretical analysis, our performance study indicates that the proposed techniques are indeed scalable with respect to the number of input queries as well as the number of items and the item arrival rate in a data stream.

Space efficient quantile summary for constrained sliding windows on a data stream

In many online applications, we need to maintain quantile statistics for a sliding window on a data stream. The sliding windows in natural form are defined as the most recent N data items. In this paper, we study the problem of estimating quantiles over other types of sliding windows. We present a uniform framework to process quantile queries for time constrained and filter based sliding windows. Our algorithm makes one pass on the data stream and maintains an E-approximate summary. It uses O((1)/(epsilon2) log(2) epsilonN) space where N is the number of data items in the window. We extend this framework to further process generalized constrained sliding window queries and proved that our technique is applicable for flexible window settings. Our performance study indicates that the space required in practice is much less than the given theoretical bound and the algorithm supports high speed data streams.

Post-fledging care, philopatry and recruitment in brown thornbills

1. We describe patterns of post-fledging care, dispersal and recruitment in four cohorts of brown thornbills Acanthiza pusilla. We examine what factors influence post-fledging survival and determine how post-hedging care and the timing of dispersal influence the probability of recruitment in this small, pair breeding, Australian passerine. 2. Fledgling thornbills were dependent on their parents for approximately 6 weeks. Male fledglings were more likely than female fledglings to survive until independence. For both sexes, the probability of reaching independence increased as nestling weight increased and was higher for nestlings that fledged later in the season. 3. The timing of dispersal by juvenile thornbills was bimodal. Juveniles either dispersed by the end of the breeding season or remained on their natal territory into the autumn and winter. Juveniles that delayed dispersal were four times more likely to recruit into the local breeding population than juveniles that dispersed early. 4. Delayed dispersal was advantageous because individuals that remained on their natal territory suffered little mortality and tended to disperse only when a local vacancy was available. Consequently, the risk of mortality associated with obtaining a breeding vacancy using this dispersal strategy was low. 5. Males, the more philopatric sex, were far more likely than females to delay dispersal. Despite the apparent advantages of prolonged natal philopatry, however, only 54% of pairs that raised male fledglings to independence had sons that postponed dispersal, and most of these philopatric sons gained vacancies before their parents bred again. Consequently, few sons have the opportunity to help their parents. Constraints on delayed dispersal therefore appear to play a major role in the evolution of pair-breeding in the brown thornbill.

Practices and attitudes to derivatives use in Australian commonwealth organisations

Little is known about risk management in the public sector This study reports on a survey of senior officers in Australian Commonwealth companies and statutory authorities concerning their practice and attitudes towards the use of derivative instruments for risk management. Using a variety of tests, the most important issue identified by respondents concerning the use of derivatives is for budgeting purposes. Of note, respondents rank commonly cited reasons advanced in the private sector such as reduced bankruptcy costs and taxation, as being relatively unimportant, which is consistent with arguments advanced in the paper The results also indicate that there are significant differences in the level of importance in some issues regarding derivatives use across public sector organisations, particularly those differentiated by a documented risk management plan. The study also documents for the first time the extent of derivatives use in the Australian public sector.

The geometric meaning of macroevolution

Although the concept of bet-hedging has been useful in microevolutionary studies for over 25 years, a recent paper by Andrew Simons suggests that it is also applicable to macroevolutionary events, with the same fundamental process of selection working at all temporal scales.

Management motivation for using financial derivatives in Australia

This study takes a direct approach to determine management motivation for the use of financial derivatives. We survey a sample of Australian firms on attitudes to derivative use and financial risk management. Management views are sought on the importance of a series of theoretical reasons for using derivatives. Generally, we find that managers are focused on the broad reduction of risk and volatility of cash flows and earnings in using derivatives. Specific issues such as reducing bankruptcy costs, debt levels and taxation are not considered as important. A further interesting result from this research is that even though firms may use derivatives they may not necessarily hedge all of their annual exposures across different financial risks. This helps explain the inconsistency of results in many empirical studies on the determinants of derivative use.

Bayesian estimation of g-and-k distributions using MCMC

In this paper we investigate a Bayesian procedure for the estimation of a flexible generalised distribution, notably the MacGillivray adaptation of the g-and-κ distribution. This distribution, described through its inverse cdf or quantile function, generalises the standard normal through extra parameters which together describe skewness and kurtosis. The standard quantile-based methods for estimating the parameters of generalised distributions are often arbitrary and do not rely on computation of the likelihood. MCMC, however, provides a simulation-based alternative for obtaining the maximum likelihood estimates of parameters of these distributions or for deriving posterior estimates of the parameters through a Bayesian framework. In this paper we adopt the latter approach, The proposed methodology is illustrated through an application in which the parameter of interest is slightly skewed.