The improvement of investment approaches by developing and applying bootstrap methods to innovative evolutionary kernel based subset time- series modelling

  • O'Neill, Terence (PI)
  • Higgins, Timothy (CoI)
  • Martin, Michael (CoI)
  • Penm, Jack HW (CoI)
  • Roberts, Steven (CoI)
  • Terrell, Deane (CoI)
  • Welsh, Alan (CoI)

    Project: Research

    Project Details


    The project will improve investment approaches by applying innovative statistical algorithms, using bootstrap methods, to modelling and data analysis. The project comprises 4 programs: developing and applying bootstrap approaches to innovative evolutionary kernel-based subset time-series modelling for investment improvement; assessing the dynamic and evolving relations among oil prices, inflation risks and financial activities through the development of new statistical models; modelling and predicting large financial market crashes/crises through financial market movements; and benchmarking and evaluating the performance of investment funds, in particular those involved in superannuation investment associated with retirement.
    Effective start/end date10/07/091/06/10


    • Japanese Association of Administrative Science: A$13,301.00
    • Jiashan Fengyuan Co Ltd: A$34,699.00
    • Rice Warner Actuaries Pty Ltd: A$30,000.00
    • Australian Research Council (ARC): A$390,000.00


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