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This paper features an analysis of causal relations between the daily VIX, S&P500 and the daily realised volatility (RV) of the S&P500 sampled at 5 min intervals, plus the application of an Artificial Neural Network (ANN) model to... more
This paper features an analysis of causal relations between the daily VIX, S&P500 and the daily realised volatility (RV) of the S&P500 sampled at 5 min intervals, plus the application of an Artificial Neural Network (ANN) model to forecast the future daily value of the VIX. Causal relations are analysed using the recently developed concept of general correlation Zheng et al. and Vinod. The neural network analysis is performed using the Group Method of Data Handling (GMDH) approach. The results suggest that causality runs from lagged daily RV and lagged continuously compounded daily return on the S&P500 index to the VIX. Sample tests suggest that an ANN model can successfully predict the daily VIX using lagged daily RV and lagged daily S&P500 Index continuously compounded returns as inputs.
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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... more
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. We justify the importance of this class of models in practice using a set of real time series data
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This article examines the deviation of the UK market index from market fundamentals implied by the simple dividend discount model and identifies other components that also affect price movements. The components are classified as... more
This article examines the deviation of the UK market index from market fundamentals implied by the simple dividend discount model and identifies other components that also affect price movements. The components are classified as permanent, temporary, excess stock returns and nonfundamental innovations in terms of a multivariate moving average model (Lee (1998)). We find that time varying discounted rates play an active role in explaining price deviations.
This paper features an analysis of volatility spillover effects from the US market, represented by the S&P500 index to the Australian capital market as represented by the Australian S&P200 for a period running from 12th September 2002 to... more
This paper features an analysis of volatility spillover effects from the US market, represented by the S&P500 index to the Australian capital market as represented by the Australian S&P200 for a period running from 12th September 2002 to 9th September 2012. This captures the impact of the Global Financial Crisis (GFC). The GARCH analysis features an exploration of whether there are any spillover effects in the mean equations as well as in the variance equations. We adopt a bi-mean equation to model the conditional mean in the Australian markets plus an ARMA model to capture volatility spillovers from the US. We also apply a Markov Switching GARCH model to explore the existence of regime changes during this period and we also explore the non-constancy of correlations between the markets and apply a moving window of 120 days of daily observations to explore time-varying conditional and fitted correlations. There appears to be strong evidence of regime switching behaviour in the Austra...
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This study estimates the income and tourism price elasticities of demand for Australian domestic tourism using a panel data approach. Given that about 76% of total tourism revenue in Australia is generated by domestic tourism, it is... more
This study estimates the income and tourism price elasticities of demand for Australian domestic tourism using a panel data approach. Given that about 76% of total tourism revenue in Australia is generated by domestic tourism, it is worthwhile examining whether changes in Australian households’ income and the prices of domestic travel can influence the demand for domestic travel. The research employs a panel data approach. This method has been widely employed in the literature on international tourism demand, but thus far, has not appeared in the context of the domestic tourism demand literature. The model used for this study is panel Three-Stage Least Square (3SLS). The data employed are based on quarterly time-series from 1999 to 2007 across seven Australian States. The paper reveals some notable results. First, the income elasticity for domestic visiting friends and relatives (VFR) trips in Australia is negative, implying that Australian households will not choose to travel domes...
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Malaysia’s response to the Asian Financial Crisis involved an industry-wide bank consolidation program within which the Malaysian banking sector underwent a comprehensive merger exercise. In this study the relative preand post-merger pure... more
Malaysia’s response to the Asian Financial Crisis involved an industry-wide bank consolidation program within which the Malaysian banking sector underwent a comprehensive merger exercise. In this study the relative preand post-merger pure technical efficiency and scale efficiency scores of Malaysian domestic banks for a period from 1996 to 2002 are measured and compared. The non-parametric Data Envelopment Analysis (DEA) approach is applied to detect any efficiency gains resulting from bank mergers. Changes in banks’ market share of deposits are subsequently probed to examine the extent to which post-merger efficiency gains were transmitted to benefit the public in the form of more favorable deposit pricing and improved service quality. The evidence shows that acquiring banks were more technically efficient but less scale efficient than target banks at the time of merger. Nevertheless, the acquiring banks did not always maintain their premerger efficiency levels. Inefficiencies grew...
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).... more
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 approach is much faster than for the MLE and therefore offers a significant reduction of the completion time.
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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... more
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 nineyear 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 taking.
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The phenomenon of the occurrence of rare yet extreme events, “Black Swans” in Taleb’s terminology, seems to be more apparent in financial markets around the globe. This means there is not only a need to design proper risk modelling... more
The phenomenon of the occurrence of rare yet extreme events, “Black Swans” in Taleb’s terminology, seems to be more apparent in financial markets around the globe. This means there is not only a need to design proper risk modelling techniques which can predict the probability of risky events in normal market conditions but also a requirement for tools which can assess the probabilities of rare financial events; like the recent Global Financial Crisis (2007-2008). An obvious candidate, when dealing with extreme financial events and the quantification of extreme market risk is Extreme Value Theory (EVT). This proves to be a natural statistical modelling technique of relevance. Extreme Value Theory provides well established statistical models for the computation of extreme risk measures like the Return Level, Value at Risk and Expected Shortfall. In this paper we apply Univariate Extreme Value Theory to model extreme market risk for the ASX-All Ordinaries (Australian) index and the S&P...
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This paper tests whether conditional versions of the CAPM are consistent with the behaviour of returns in 20 emerging markets and four developed ones. A country's risk is defined as the conditional sensitivity or covariance of its... more
This paper tests whether conditional versions of the CAPM are consistent with the behaviour of returns in 20 emerging markets and four developed ones. A country's risk is defined as the conditional sensitivity or covariance of its market return with a world stock return. This risk is permitted to vary through time. The conditional covariances calculated for each emerging market should explain the differences in national stock index performance. The results are varied: those markets with high capitalizations and high correlations with world ma rkets appear to be priced more in terms of world factors whilst others are much more influenced by local factors.
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... more
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 strong leverage effects, short-lived explosive regimes and is strongly and positively related to the level of volatility. Starting from a mixing hypothesis for volatility and returns, we propose a Monte Carlo method for translating these features into refined density forecasts for returns from our conditional volatility, sk...
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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... more
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 durations. Furthermore, the empirical analysis in this paper illustrates the advantage of our model over its parametric counterparts. Finally, the paper discusses some important theoretical issues, especially its asymptotic properties, in order to pave the way for a more detailed analysis, which will be presented in a future paper.
In this paper we analyse the performance of fixed interest managed funds. We examine the relative effectiveness of seven different indices of bond performance, some commercially available and some that we construct ourselves as... more
In this paper we analyse the performance of fixed interest managed funds. We examine the relative effectiveness of seven different indices of bond performance, some commercially available and some that we construct ourselves as explanators of Australian fixed interest managed fund returns. We combine these measures with four different measures of interest rate fluctuations, four measures of economic fundamentals, two measures of maturity risk, two measures of default risk, and two measures of equity market returns in an attempt to find an ‘optimum’ index for benchmarking Australian fixed interest managed fund returns. We run our tests over two independent periods in an effort to identify (in a consistent setting) the most accurate and least biased methodology. The use of an Australian dataset, sourced from the Australian fund-rating agency ASSIRT means that we can provide some independent results from previous US studies, as there is little prior work on Australian fixed-interest ma...
Masulis and Korwar (1986) documented significant underperformance of companies issuing new equity, subsequently confirmed by Asquith and Mullins (1986), Mikkleson and Partch (1986) and Schipper and Smith (1986). Loughran and Ritter... more
Masulis and Korwar (1986) documented significant underperformance of companies issuing new equity, subsequently confirmed by Asquith and Mullins (1986), Mikkleson and Partch (1986) and Schipper and Smith (1986). Loughran and Ritter (1995), extended Healy and Palepu (1990), Ritter (1991) and Loughran, Ritter and Rydqvist’s (1994) work in the area of initial public offerings (IPOs), examining the performance of SEO firms. They observed 15.7% and 33.4% fiveyear holding period returns for IPOs and SEOs when the returns on non-issuing firms matched by capitalisation were 66.4% and 92.8%. Loughran and Ritter (1995) concluded “an investor would have had to invest 44 percent more money in the issuers than in non-issuers of the same size to have the same wealth five years after the offering date”. Loughran and Ritter (1997) suggest possible “windows of opportunity”, periods during which firms are significantly overvalued providing an opportunity to augment “financial slack”. Allen and Soucik...
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The market regulators of the Indonesia stock exchange have made several changes in permissible minimum price variations, from a single tick size (IDR 5) in 2000 to multiple tick sizes (IDR1, 5, 10, 25, 50) in 2007 for the purposes of... more
The market regulators of the Indonesia stock exchange have made several changes in permissible minimum price variations, from a single tick size (IDR 5) in 2000 to multiple tick sizes (IDR1, 5, 10, 25, 50) in 2007 for the purposes of promoting efficient trading and liquidity improvements. Researchers have demonstrated that finer tick sizes will lower bidask spreads, yet studies which examine the impact of tick size on other key liquidity dimensions such as realized market depth and speed of quote revision are limited. As tick size diminishes so too do the benefits of time precedence rules and encouragement is given to the existence of front-runners, traders are more reluctant to show their orders and more aggressive to consume market orders which leads to a thinner order book. This paper will adopt the V-Net measurement (Engle & Lange, 2001) to assess whether there is a significant difference in net directional volume pre and post tick size changes and to further assess the relation...
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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... more
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 80s. This finding is similar to many claims in most U.S. studies that find that other macroeconomic factors such as the business cycle, inflation and the level of economic growth can play a part in the prediction process. JEL classification: M4
The worldwide impact of the Global Financial Crisis on stock markets, investors and fund managers has lead to a renewed interest in tools for robust risk management. Quantile regression is a suitable candidate and deserves the interest of... more
The worldwide impact of the Global Financial Crisis on stock markets, investors and fund managers has lead to a renewed interest in tools for robust risk management. Quantile regression is a suitable candidate and deserves the interest of financial decision makers given its remarkable capabilities for capturing and explaining the behaviour of financial return series more effectively than the ordinary least squares regression methods which are the standard tool. In this paper we present quantile regression estimation as an attractive additional investment tool, which is more efficient than Ordinary Least Square in analyzing information across the quantiles of a distribution. This translates into the more accurate calibration of asset pricing models and subsequent informational gains in portfolio formation. We present empirical evidence of the effectiveness of quantile regression based techniques as applied across the quantiles of return distributions to derive information for portfol...
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This paper features a new autoregressive conditional duration (ACD) model which sits within the theoretical framework provided by the recently developed observation-driven time series models by Creal et al. (2013): the generalized... more
This paper features a new autoregressive conditional duration (ACD) model which sits within the theoretical framework provided by the recently developed observation-driven time series models by Creal et al. (2013): the generalized autoregressive score (GAS) models. The autoregressive conditional directional duration (ACDD) model itself contains three novelties. First, durations (intra-trade intervals or waiting-times) are signed, based on whether a (positive) ask-driven trade or a (negative) bid-driven trade occurred. These signed trade-durations are known as directional durations. Second, as the resultant directional durations are no longer positive and asymmetrical but are symmetrically distributed, the familiar generalized autoregressive conditional heteroskedasticity (GARCH)-like formulation of the ACD process is proposed for modeling these directional durations. Consequently, the proposed model is called the ACDD model. Third, using the alternative GARCH-like formulation, persi...
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Research Interests: Economics, Risk assessment, Applied Economics, Stock Market, Internal Control, and 8 moreApplied Economics Letters, Quantile Regression, Value at Risk, Regression Analysis, Banking Industry, Public health systems and services research, Risk Assessment, and Autoregressive Conditional Heteroskedasticity
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This paper analyses the various hypotheses,regarding the term structure of interest rates. We test the expectations hypothesis for four major countries, namely, the United States, the United Kingdom, Germany and Japan. The data rejects... more
This paper analyses the various hypotheses,regarding the term structure of interest rates. We test the expectations hypothesis for four major countries, namely, the United States, the United Kingdom, Germany and Japan. The data rejects the expectations hypothesis and the results indicate the presence of a time varying term premium. To explain the results, we posit a relationship between the
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In his seminal article, Samuelson (1965) formulated the proposition that futures prices are more volatile the closer a particular contract is to expiry. This paper applies testing procedures for the Samuelson Hypothesis (or maturity... more
In his seminal article, Samuelson (1965) formulated the proposition that futures prices are more volatile the closer a particular contract is to expiry. This paper applies testing procedures for the Samuelson Hypothesis (or maturity effect) to commodity futures contracts on the Sydney Futures Exchange, the London International Financial Futures and Options Exchange and the Singapore International Monetary Exchange. Traditional regression analysis is supplemented by fitting ARCH models to the data and in doing so it is concluded that evidence in favour of the Samuelson hypothesis does exist in a majority of the contracts analysed.
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This paper analyses takeover effects on the Thai stock market in terms of the impact on bidding firms shareholders. Various shareholder wealth effects are reported including those from a matched reference portfolio control method with... more
This paper analyses takeover effects on the Thai stock market in terms of the impact on bidding firms shareholders. Various shareholder wealth effects are reported including those from a matched reference portfolio control method with bootstrapped skewness-adjusted t-statistics. The findings are consistent with past studies: see the survey studies by Jensen and Ruback (1983), Agrawal and Jaffe (1999), Bruner (2002)
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Credit risk modelling,has become,increasingly important,to Banks since the advent of Basel II which allows Banks with sophisticated mod- elling techniques to use internal models,for thepurpose,of calculating capital requirements.,A high... more
Credit risk modelling,has become,increasingly important,to Banks since the advent of Basel II which allows Banks with sophisticated mod- elling techniques to use internal models,for thepurpose,of calculating capital requirements.,A high level of credit risk is often the key rea- son behind,banks,failing or experiencing,severe di¢ culty. The man- agement,of sectoral concentration,is a critical component,of credit risk management, as over concentration of
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The purpose of this paper is to examine the causality between DUST, CO2 and temperature for the Vostok ice core data series [Vostok Data Series], dating from 420 000 years ago, and the EPICA C Dome data going back 800 000 years. In... more
The purpose of this paper is to examine the causality between DUST, CO2 and temperature for the Vostok ice core data series [Vostok Data Series], dating from 420 000 years ago, and the EPICA C Dome data going back 800 000 years. In addition, the time-varying volatility and coefficient of variation in the CO2, dust and temperature is examined, as well as their dynamic correlations and interactions. We find a clear link between atmospheric C02 levels, dust and temperature, together with a bi-directional causality effects when applying both Granger Causality Tests (1969) and multi-directional Non-Linear analogues, i.e. Generalized Correlation. We apply both parametric and non-parametric statistical measures and testing. Linear interpolation with 100 years and 1000 years is applied to the three variables, in order to solve the problem of data points mismatch among them. The visualizations and descriptive statistics of the interpolated variables (using the two periods) show robustness in the results. The data analysis points out that variables are volatile, but their respective rolling mean and standard deviation remain stable. Additionally, 1000 years interpolated data suggests positive correlation between temperature and CO2, while dust is negatively correlated with both temperature and CO2. The application of the non-parametric Generalized Measure of Correlation to our data sets, in a pairwise fashion suggested that CO2 better explains temperature than temperature does CO2, that temperature better explains dust than dust does temperature, and finally that CO2 better explains dust than vice-versa. The latter two pairs of relationships are negative. The summary of the paper presents some avenues for further research, as well as some policy relevant suggestions.