title: Evolutionary data selection for enhancing models of intraday forex time series

authors: Mayo, Michael

subjects: intraday

abstract: The hypothesis in this paper is that a significant amount of intraday market data is either noise or redundant, and that if it is eliminated, then predictive models built using the remaining intraday data will be more accurate. To test this hypothesis, we use an evolutionary method (called Evolutionary Data Selection, EDS) to selectively remove out portions of training data that is to be made available to an intraday market predictor. After performing experiments in which data-selected and non-data-selected versions of the same predictive models are compared, it is shown that EDS is effective and does indeed boost predictor accuracy. It is also shown in the paper that building multiple models using EDS and placing them into an ensemble further increases performance. The datasets for evaluation are large intraday forex time series, specifically series from the EUR/USD, the USD/JPY and the EUR/JPY markets, and predictive models for two primary tasks per market are built: intraday return prediction and intraday volatility prediction.

text: Evolutionary data selection for enhancing models of intraday forex time series The hypothesis in this paper is that a significant amount of intraday market data is either noise or redundant, and that if it is eliminated, then predictive models built using the remaining intraday data will be more accurate. To test this hypothesis, we use an evolutionary method (called Evolutionary Data Selection, EDS) to selectively remove out portions of training data that is to be made available to an intraday market predictor. After performing experiments in which data-selected and non-data-selected versions of the same predictive models are compared, it is shown that EDS is effective and does indeed boost predictor accuracy. It is also shown in the paper that building multiple models using EDS and placing them into an ensemble further increases performance. The datasets for evaluation are large intraday forex time series, specifically series from the EUR/USD, the USD/JPY and the EUR/JPY markets, and predictive models for two primary tasks per market are built: intraday return prediction and intraday volatility prediction.

year: 2012

title: Editorial: Organisational Behaviour

authors: Haar, Jarrod M.

subjects: human resource management

abstract: Welcome to the first of our set of Special Editions of the New Zealand Journal of Human Resource Management (NZJHRM). The idea behind the current set of Special Issue’s was trying to promote emerging research and researchers from New Zealand and Australasia undertaking research of interest to Human Resource Management professionals, academics, and researchers. A number of these papers were presented at the Australian and New Zealand Academy of Management (ANZAM) Conference in Auckland 2008 and as such, I would like to acknowledge the initial work of reviewers from the conference through the various HRM-related streams. The new focus of the NZJHRM has been broadened to encompass the wider settings of other Australasian countries because often the lessons these studies provide are as applicable to New Zealand as they are to their specific local setting. The present Special Issue covers a wide variety of cultural settings including Australia, Malaysian, and India. Given the growth of globalization and the cultural diversity found in New Zealand, I believe the lessons found here are likely to be at least somewhat transferable to our New Zealand setting and should provide greater understanding of commonalities in HRM within our Australasian region.

text: Editorial: Organisational Behaviour Welcome to the first of our set of Special Editions of the New Zealand Journal of Human Resource Management (NZJHRM). The idea behind the current set of Special Issue’s was trying to promote emerging research and researchers from New Zealand and Australasia undertaking research of interest to Human Resource Management professionals, academics, and researchers. A number of these papers were presented at the Australian and New Zealand Academy of Management (ANZAM) Conference in Auckland 2008 and as such, I would like to acknowledge the initial work of reviewers from the conference through the various HRM-related streams. The new focus of the NZJHRM has been broadened to encompass the wider settings of other Australasian countries because often the lessons these studies provide are as applicable to New Zealand as they are to their specific local setting. The present Special Issue covers a wide variety of cultural settings including Australia, Malaysian, and India. Given the growth of globalization and the cultural diversity found in New Zealand, I believe the lessons found here are likely to be at least somewhat transferable to our New Zealand setting and should provide greater understanding of commonalities in HRM within our Australasian region.

year: 2009

title: PIWeCS: enhancing human/machine agency in an interactive composition system

authors: Whalley, Ian

abstract: This paper focuses on the infrastructure and aesthetic approach used in PIWeCS: a Public Space Interactive Web-based Composition System. The concern was to increase the sense of dialogue between human and machine agency in an interactive work by adapting Paine's (2002) notion of a conversational model of interaction as a ‘complex system’. The machine implementation of PIWeCS is achieved through integrating intelligent agent programming with MAX/MSP. Human input is through a web infrastructure. The conversation is initiated and continued by participants through arrangements and composition based on short performed samples of traditional New Zealand Maori instruments. The system allows the extension of a composition through the electroacoustic manipulation of the source material.

text: PIWeCS: enhancing human/machine agency in an interactive composition system This paper focuses on the infrastructure and aesthetic approach used in PIWeCS: a Public Space Interactive Web-based Composition System. The concern was to increase the sense of dialogue between human and machine agency in an interactive work by adapting Paine's (2002) notion of a conversational model of interaction as a ‘complex system’. The machine implementation of PIWeCS is achieved through integrating intelligent agent programming with MAX/MSP. Human input is through a web infrastructure. The conversation is initiated and continued by participants through arrangements and composition based on short performed samples of traditional New Zealand Maori instruments. The system allows the extension of a composition through the electroacoustic manipulation of the source material.

year: 2004