Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 15 of 15
Full-Text Articles in Physical Sciences and Mathematics
A Semiparametric Approach To A Nonlinear Acd Model, Pipat Wongsaart, Jiti Gao, David E. Allen
A Semiparametric Approach To A Nonlinear Acd Model, Pipat Wongsaart, Jiti Gao, David E. Allen
Research outputs pre 2011
We introduce in this paper a new semiparametric approach to a nonlinear ACD model, namely the Semiparametric ACD (SEMI-ACD) model. This new model is more flexible in the sense that the data are allowed to speak for themselves, without a hypothetical assumption being imposed arbitrarily on its key component. Moreover, it enables a much more thorough examination of the intertemporal importance of the conditional duration on the ACD process. Our experimental analysis suggests that the new model possesses a sound asymptotic character, while its performance is also robust across data generating processes and assumptions about the conditional distribution of the …
Fitting Weibull Acd Models To High Frequency Transactions Data : A Semi-Parametric Approach Based On Estimating Functions, Kok Haur Ng, David E. Allen, Shelton Peiris
Fitting Weibull Acd Models To High Frequency Transactions Data : A Semi-Parametric Approach Based On Estimating Functions, Kok Haur Ng, David E. Allen, Shelton Peiris
Research outputs pre 2011
Autoregressive conditional duration (ACD) models play an important role in financial modeling. This paper considers the estimation of the Weibull ACD model using a semiparametric approach based on the theory of estimating functions (EF). We apply the EF and the maximum likelihood (ML) methods to a data set given in Tsay (2003, p203) to compare these two methods. It is shown that the EF approach is easier to apply in practice and gives better estimates than the MLE. Results show that the EF approach is compatible with the ML method in parameter estimation. Furthermore, the computation speed for the EF …
Realized Volatility Uncertainty, David E. Allen, Michael Mcaleer, Marcel Scharth
Realized Volatility Uncertainty, David E. Allen, Michael Mcaleer, Marcel Scharth
Research outputs pre 2011
The presence of high and time-varying volatility of volatility and leverage effects bring additional uncertainty in the tails of the distribution of asset returns, even though returns standardized by (ex-post) quadratic variation measures are nearly gaussian. We argue that in this setting modeling shocks to volatility is more relevant for applications than extracting more precise predictions of the variable, as point forecasts differences are swamped by the size of the volatility of volatility and rendered less informative by the nongaussianity in the ex-ante distribution of returns. Using S&P 500 data, we document that this volatility of volatility is subject to …
The Third Generation Acd Model : A Semiparametric Approach, Pipat Wongsaart, Jiti Gao, David E. Allen
The Third Generation Acd Model : A Semiparametric Approach, Pipat Wongsaart, Jiti Gao, David E. Allen
Research outputs pre 2011
Having concluded that thus far the question about the most appropriate type of nonlinear ACD model has not been satisfactorily answered, we intend to develop a novel ACD modelling methodology based on an iterative estimation algorithm and a semiparametric autoregressive process that not only allows the data to speak for itself, but also is robust across datasets without relying on some computational factors, such as the hypothesis about the probability density function of the standardised durations. We propose in this paper the Semiparametric ACD (SP-ACD) model, which can be considered a starting point of such a development. To address the …
Analysis And Applications Of Autoregressive Moving Average Models With Stochastic Variance, Shelton Peiris, Ramprasad Bhar, David E. Allen
Analysis And Applications Of Autoregressive Moving Average Models With Stochastic Variance, Shelton Peiris, Ramprasad Bhar, David E. Allen
Research outputs pre 2011
It is known that volatility plays a central role in financial modelling problems. This paper studies, in detail, a class of discrete time stochastic volatility (SV) models driven by ARMA models with innovations having a stochastic variances. The auto- correlation function of this class of models is derived and methods of identification of such processes are described. An example is added to illustrate the development of the theory over the standard methods.
Forecasting The Equity Premium In The Australian Market, David E. Allen, Lurion Demello
Forecasting The Equity Premium In The Australian Market, David E. Allen, Lurion Demello
Research outputs pre 2011
This paper provides a forecasting methodology for estimating the market risk premium in Australia. We employ an in-sample and out-of-sample forecast estimate using various dividend yield measures. The lagged dividend yield model is used to predict future equity premia on a data series that includes the top 85 percent of the Australian stock market. An important concern in this paper is the accuracy of dividend yield in forecasting the equity premium in the Australian market. We find that the level of predictability in the later part of the series is very weak compared to in-sample prediction during the 70s and …
Applications Of Recursive Estimation Methods In Statistical Process Control, Shelton Peiris, Aerambamoorthy Thavaneswaran, David E. Allen, R. Mellor
Applications Of Recursive Estimation Methods In Statistical Process Control, Shelton Peiris, Aerambamoorthy Thavaneswaran, David E. Allen, R. Mellor
Research outputs pre 2011
In recent years there has been a growing interest in recursive estimation techniques as applied to statistical process control (SPC). In cases where prior information about the processes are available, it is shown that procedures based on the “optimal” smoothing can be superior to the classical procedures like Shewhart’s CUSUM control charts (see, for instance, Thavaneswaran, McPherson and Abraham (1998)). This paper reviews the recursive algorithms based on EWMA (exponentially weighted moving average), DLM (dynamic linear modeling), KF (Kalman filtering) and OS (optimal smoothing) in statistical process control with correlated data. We also discuss various relationships among the asymptotic mean …
Some Evidence On The Information Content Of Undisclosed Limit Orders On The Asx, M. Aitken, David E. Allen, Wenling J. Yang
Some Evidence On The Information Content Of Undisclosed Limit Orders On The Asx, M. Aitken, David E. Allen, Wenling J. Yang
Research outputs pre 2011
This paper is concerned with investigating the information content of undisclosed limit orders, and identifying factors that affect their size, plus the examination of the brokers’ behaviour in using undisclosed orders. We adopt a sample of liquid stocks listed on the ASX, and our estimation results indicate that the size of undisclosed orders are affected by a number of factors. Given the ‘stealth trading’ pattern of behaviour observed in large disclosed orders, this paper provides evidence to support a similar pattern of behaviour in the case of undisclosed orders. Our model also provides an appropriate measure for estimating the size …
Effects Of Bank Funds Management Activities On The Disintermediation Of Bank Deposits, David E. Allen, Jerry T. Parwada
Effects Of Bank Funds Management Activities On The Disintermediation Of Bank Deposits, David E. Allen, Jerry T. Parwada
Research outputs pre 2011
This study investigates the alleged disintermediation of banks’ traditional deposit-taking in favour of investment management activities. Using data on Australian bank-affiliated funds and a nine-year record of the parent banks’ liability balances, this study finds that managed funds do not displace bank liabilities. Prudential capital adequacy requirements dissuade banks from using in-house managed investments as indirect conduits for raising funds in the same manner as deposit-taking.
Generalized Moving Average Models And Applications In High Frequency Data, Shelton Peiris, David E. Allen, Aerambamoorthy Thavaneswaran
Generalized Moving Average Models And Applications In High Frequency Data, Shelton Peiris, David E. Allen, Aerambamoorthy Thavaneswaran
Research outputs pre 2011
This paper considers a new class of first order moving average type time series model with index δ (> 0) to describe some hidden features of a time series. It is shown that this class of models provides a valid, simple solution to a new direction of time series modelling. In particular, for suitably chosen parameters (coefficient β and index δ) this type of models could be used to describe data with low or high frequency components. Various new results associated with this class are given in a general form. A simulation study is carried out to justify the theory. …
On The Evolution Of Probability-Weighting Function And Its Impact On Gambling, Steven Li, Yun Hsing Cheung
On The Evolution Of Probability-Weighting Function And Its Impact On Gambling, Steven Li, Yun Hsing Cheung
Research outputs pre 2011
It is well known that individuals treat losses and gains differently and there exists non-linearity in probability. The asymmetry between gains and losses is highlighted by the reflection effect. The non-linearity in probability is described by the curvature of the probability-weighting function. This paper studies the evolution of the probability-weighting function. It is assumed that the probability weighting for an individual follows a mean-reverting stochastic process. The Monte Carlo simulation technique is employed to study the evolution of the weighting function. The evolution of the probability- weighting function implies that an individual does not treat gains or losses consistently over …
Heckman's Methodology For Correcting Selectivity Bias : An Application To Road Crash Costs, Margaret Giles
Heckman's Methodology For Correcting Selectivity Bias : An Application To Road Crash Costs, Margaret Giles
Research outputs pre 2011
Aggregate road crash costs are traditionally determined using average costs applied to incidence figures found in Police-notified crash data. Such data only comprise a non-random sample of the true population of road crashes, the bias being due to the existence of crashes that are not notified to the Police. The traditional approach is to label the Police-notified sample as 'non-random' thereby casting a cloud over data analyses using this sample. Heckman however viewed similar problems as 'omitted variables' problems in that the exclusion of some observations in a systematic manner (so-called selectivity bias) has inadvertently introduced the need for an …
Are Bank Deposits And Bank-Affiliated Managed Funds Close Substitutes?, David E. Allen, Jerry T. Parwada
Are Bank Deposits And Bank-Affiliated Managed Funds Close Substitutes?, David E. Allen, Jerry T. Parwada
Research outputs pre 2011
This study tests the hypothesis that bank liabilities and managed funds are close substitutes. Some literature associates the alleged decline in banking business with the disintermediation of banks’ traditional deposit-taking business in favour of investment management. A comparative assessment of managed fund and bank deposit qualitative attributes fails to support substitutability. Using data on Australian bank-affiliated funds and a nine-year record of bank liability balances, this study finds that, empirically, managed funds do not displace bank liabilities. Prudential capital adequacy requirements dissuade banks from using in-house managed investments as indirect conduits for raising funds in the same manner as deposit …
Some Statistical Models For Durations And Their Applications In Finance, Harry Zheng, David E. Allen, Lyn C. Thomas
Some Statistical Models For Durations And Their Applications In Finance, Harry Zheng, David E. Allen, Lyn C. Thomas
Research outputs pre 2011
We first consider a new class of time series models (introduced by Engle and Russell (1998)) use in statistical applications in finance. These models treat the time between events (durations) as a stochastic process and the corresponding durations are modelled using a theory similar to that of autoregressive processes. This new class of time series models is called Autoregressive Conditional Duration (ACD) models. Various extensions and the statistical properties of this class of ACD models are given. We also suggest some alternative models for durations arising from the market microstructure literature. An estimation procedure is discussed. The theory is illustrated …
The Duration Derby : A Comparison Of Duration Based Strategies In Asset Liability Management, Harry Zheng, David E. Allen, Lyn C. Thomas
The Duration Derby : A Comparison Of Duration Based Strategies In Asset Liability Management, Harry Zheng, David E. Allen, Lyn C. Thomas
Research outputs pre 2011
Macaulay duration matched strategy is a key tool in bond portfolio immunization. It is well known that if term structures are not at or changes are not parallel, then Macaulay duration matched portfolio can not guarantee adequate immunization. In this paper the approximate duration is proposed to measure the bond price sensitivity to changes of interest rates of non- at term structures. Its performance in immunization is compared with those of Macaulay, partial and key rate durations using the US Treasury STRIPS and Bond data. Approximate duration turns out to be a possible contender in asset liability management: it does …