Now showing 1 - 6 of 6
  • Publication
    The minimum local cross-entropy criterion for inferring risk-neutral price distributions from traded options prices
    (University College Dublin. School of Business. Centre for Financial Markets, 2004-04-18)
    A quantity known as the Local Cross-Entropy (LCE) for a density is proposed, defined to be the local derivative of the Cross-Entropy between a density and a ’kernel-smoothed’ version of itself, with respect to bandwidth of the smoothing. This criterion is argued to be of the ’smoothness’ type and is also argued to be more sensible and ’natural’ than the frequently used ’Maximum Entropy’ criterion for many applications. When applied to price distributions in conjunction Options constraints the minimum LCE criterion is shown to produce estimates which share the best theoretical properties of the Maximum Entropy approach with the best practical properties of the estimators identified by Jackwerth and Rubinstein
  • Publication
    The non-linear evolution of high frequency short term interest rates
    (University College Dublin. School of Business. Centre for Financial Markets, 2008-04-02) ;
    In this paper new results are documented regarding the short term evolution of global short term interest rates. Much work has been carried out concerning the evolution of interest rates over long time scales, on the order on one month or greater. However high frequency data has only been considered in a limited number of studies. In this study the evolution of the short term yield curve, on a day to day basis, is considered and results are presented that suggest that over these short time scales, short term interest rates exhibit non-linear autoregressive behaviour, in contradiction of the efficient markets hypothesis. In addition the high frequency data indicates that the observed co-movement across currencies of longer maturity interest rates result from a vector error correction process (VECM). Greater information on the nature of the process may be obtained by considering a non-linear VECM process. Based on the output of both non-linear uni-variate and multi-variate models, limited short term statistically significant predictions of the evolution of various short term interest rate instruments may be carried out.
  • Publication
    Conundrum or complication : a study of yield curve dynamics under unusual economic conditions and monetary policies
    (University College Dublin. School of Business. Centre for Financial Markets, 2008-03-04) ;
    The definition of the decline of long term yields in the light of increasing short term yields as a conundrum by Chairman Greenspan in February 2005 has generated a significant amount of research. This paper presents a study of yield curve dynamics over this period using economic surprise data as the diagnostic tool. Results are presented for both US and Japanese data which indicate a non-linear response of the yield curve to economic data and monetary policy over the period in question. Further, a limited model is presented that is consistent with the observations. This can lead to an explanation of the conundrum in terms of a non-linear yield response to expected long term inflation and a variable expected long term real rate.
  • Publication
    Swarm intelligent optimisation based stochastic programming model for dynamic asset allocation
    Asset allocation is critical for the portfolio management process. In this paper, we solve a dynamic asset allocation problem through a multiperiod stochastic programming model. The objective is to maximise the expected utility of wealth at the end of the planning periods. To improve the optimisation result of the model, we employ swarm intelligent optimisers, the Bacterial Foraging Optimisation (BFO) algorithm and the Particle Swarm Optimisation (PSO) algorithm. A hybrid optimiser using the Bacterial Foraging Optimisation algorithm for initialisation and the Sequential Quadratic Programming (SQP) for local search is also suggested. The results are compared with the standard-alone SQP and the canonical Genetic Algorithm. The numerical results suggest the hybrid method provides better result, with improved accuracy, stability and computing speed than using BFO, PSO, GA, or SQP alone.
      2429Scopus© Citations 3
  • Publication
    Natural computing in finance : a review
    The field of Natural Computing (NC) has advanced rapidly over the past decade. One significant offshoot of this progress has been the application of NC methods in finance. This chapter provides an introduction to a wide range of financial problems to which NC methods have been usefully applied. The chapter also identifies open issues and suggests future directions for the application of NC methods in finance.
      2630Scopus© Citations 6
  • Publication
    Adaptive universal portfolios
    The purpose of this paper is to develop a stock selection algorithm with similar properties as Cover’s Universal Portfolio, but providing superior early growth. Cover’s Universal Portfolio generates a growth rate asymptotically equal to the best achievable growth rate over the set of constant rebalanced portfolios. However, Cover’s Universal Portfolio is empirically seen to generate poor early growth. While much research has been conducted in relation to Cover’s Universal Portfolio, much of this has focused on efficient implementation of the algorithm and considerations of market frictions. As such, there remains a significant research gap in addressing the issue of poor early growth generated by Cover’s strategy. With this in mind we develop the Adaptive Universal Portfolio, a sequential portfolio selection algorithm with similar asymptotic properties as Cover’s Universal Portfolio but providing greater early growth. In this paper we provide an analysis of the growth generated by the two algorithms. Furthermore we present empirical evidence of the superior early growth generated by the Adaptive Universal Portfolio. Finally we discuss possible criticisms of the Adaptive Universal Portfolio, including evidence of momentum following and vulnerability to individual stock risks, and provide an insight into possible future work in this area.
      1528Scopus© Citations 12