M.J. McAleer (Michael)
http://repub.eur.nl/ppl/6150/
List of Publicationsenhttp://repub.eur.nl/eur_signature.png
http://repub.eur.nl/
RePub, Erasmus University RepositoryBibliometric Rankings of Journals based on the Thomson Reuters Citations Database
http://repub.eur.nl/pub/77925/
Sun, 01 Mar 2015 00:00:01 GMT<div>C-L. Chang</div><div>M.J. McAleer</div>
__Abstract__
Virtually all rankings of journals are based on citations, including self citations by journals and individual academics. The gold standard for bibliometric rankings based on citations data is the widely-used Thomson Reuters Web of Science (2014) citations database, which publishes, among others, the celebrated Impact Factor. However, there are numerous bibliometric measures, also known as research assessment measures, based on the Thomson Reuters citations database, but they do not all seem to have been collected in a single source. The purpose of this paper is to present, define and compare the 16 most well-known Thomson Reuters bibliometric measures in a single source. It is important that the existing bibliometric measures be presented in any rankings papers as alternative bibliometric measures based on the Thomson Reuters citations database can and do produce different rankings, as has been documented in a number of papers in the bibliometrics literature.The Impact of Jumps and Leverage in
Forecasting Co-Volatility
http://repub.eur.nl/pub/77761/
Sun, 01 Feb 2015 00:00:01 GMT<div>M. Asai</div><div>M.J. McAleer</div>
__Abstract__
The paper investigates the impact of jumps in forecasting co-volatility, accommodating leverage effects. We modify the jump-robust two time scale covariance estimator of Boudt and Zhang (2013)such that the estimated matrix is positive definite. Using this approach we can disentangle the estimates of the integrated co-volatility matrix and jump variations from the quadratic covariation matrix. Empirical results for three stocks traded on the New York Stock Exchange indicate that the co-jumps of two assets have a significant impact on future co-volatility, but that the impact is negligible for forecasting weekly and monthly horizons.On the Invertibility of EGARCH(p,q )
http://repub.eur.nl/pub/77762/
Sun, 01 Feb 2015 00:00:01 GMT<div>G.G. Martinet</div><div>M.J. McAleer</div>
__Abstract__
Of the two most widely estimated univariate asymmetric conditional volatility models, the exponential GARCH (or EGARCH) specification can capture asymmetry, which refers to the different effects on conditional volatility of positive and negative effects of equal magnitude, and leverage, which refers to the negative correlation between the returns shocks and subsequent shocks to volatility. However, the statistical properties of the (quasi-) maximum likelihood estimator (QMLE) of the EGARCH parameters are not available under general conditions, but only for special cases under highly restrictive and unverifiable conditions, such as EGARCH(1,0) or EGARCH(1,1), and possibly only under simulation. A limitation in the development of asymptotic properties of the QMLE for the EGARCH(p,q) model is the lack of an invertibility condition for the returns shocks underlying the model. It is shown in this paper that the EGARCH(p,q) model can be derived from a stochastic process, for which the invertibility conditions can be stated simply and explicitly. This will be useful in re-interpreting the existing properties of the QMLE of the EGARCH(p,q) parameters.Frontiers in Time Series and Financial
Econometrics:
An Overview
http://repub.eur.nl/pub/77763/
Sun, 01 Feb 2015 00:00:01 GMT<div>S. Ling</div><div>M.J. McAleer</div><div>H. Tong</div>
__Abstract__
Two of the fastest growing frontiers in econometrics and quantitative finance are time series and financial econometrics. Significant theoretical contributions to financial econometrics have been made by experts in statistics, econometrics, mathematics, and time series analysis. The purpose of this special issue of the journal on “Frontiers in Time Series and Financial Econometrics” is to highlight several areas of research by leading academics in which novel methods have contributed significantly to time series and financial econometrics, including forecasting co-volatilities via factor models with asymmetry and long memory in realized covariance, prediction of Lévy-driven CARMA processes, functional index coefficient models with variable selection, LASSO estimation of threshold autoregressive models, high dimensional stochastic regression with latent factors, endogeneity and nonlinearity, sign-based portmanteau test for ARCH-type models with heavy-tailed innovations, toward optimal model averaging in regression models with time series errors, high dimensional dynamic stochastic copula models, a misspecification test for multiplicative error models of non-negative time series processes, sample quantile analysis for long-memory stochastic volatility models, testing for independence between functional time series, statistical inference for panel dynamic simultaneous equations models, specification tests of calibrated option pricing models, asymptotic inference in multiple-threshold double autoregressive models, a new hyperbolic GARCH model, intraday value-at-risk: an asymmetric autoregressive conditional duration approach, refinements in maximum likelihood inference on spatial autocorrelation in panel data, statistical inference of conditional quantiles in nonlinear time series models, quasi-likelihood estimation of a threshold diffusion process, threshold models in time series analysis - some reflections, and generalized ARMA models with martingale difference errors.Quality Weighted Citations versus Total Citations in the Sciences and Social Sciences, with an Application to Finance and Accounting
http://repub.eur.nl/pub/77422/
Tue, 13 Jan 2015 00:00:01 GMT<div>C-L. Chang</div><div>M.J. McAleer</div>
__Abstract__
The premise underlying the use of citations data is that higher quality journals generally have a higher number of citations. The impact of citations can be distorted in a number of ways. Journals can, and do, inflate the number of citations through self citation practices, which may be coercive. Another method for distorting journal impact is through a set of journals agreeing to cite each other, that is, by exchanging citations. This may be less coercive than self citations, but is nonetheless unprofessional and distortionary. Both journal self citations and exchanged citations have the effect of increasing a journal’s impact factor, which may be deceptive. The paper analyses academic journal quality and research impact using quality weighted citations versus total citations, based on the widely-used Thomson Reuters ISI Web of Science citations database (ISI). A new Index of Citations Quality (ICQ) is presented, based on quality weighted citations. The new index is used to analyse the leading 500 journals in both the Sciences and Social Sciences, as well as 58 leading journals in Finance and Accounting, using quantifiable Research Assessment Measures (RAMs) that are based on alternative transformations of citations. It is shown that ICQ is a useful additional measure to 2YIF and other well known RAMs for the purpose of evaluating the impact and quality, as well as ranking, of journals as it contains information that has very low correlations with the information contained in the well known RAMs for both the Sciences and Social Sciences, as well as in Finance and Accounting.Econometric Analysis of Financial Derivatives: An Overview
http://repub.eur.nl/pub/77399/
Tue, 16 Dec 2014 00:00:01 GMT<div>C-L. Chang</div><div>M.J. McAleer</div>
__Abstract__
One of the fastest growing areas in empirical finance, and also one of the least rigorously analyzed, especially from a financial econometrics perspective, is the econometric analysis of financial derivatives, which are typically complicated and difficult to analyze. The purpose of this special issue of the journal on “Econometric Analysis of Financial Derivatives” is to highlight several areas of research by leading academics in which novel econometric, financial econometric, mathematical finance and empirical finance methods have contributed significantly to the econometric analysis of financial derivatives, including market-based estimation of stochastic volatility models, the fine structure of equity-index option dynamics, leverage and feedback effects in multifactor Wishart stochastic volatility for option pricing, option pricing with non-Gaussian scaling and infinite-state switching volatility, stock return and cash flow predictability: the role of volatility risk, the long and the short of the risk-return trade-off, What’s beneath the surface? option pricing with multifrequency latent states, bootstrap score tests for fractional integration in heteroskedastic ARFIMA models, with an application to price dynamics in commodity spot and futures markets, a stochastic dominance approach to financial risk management strategies, empirical evidence on the importance of aggregation, asymmetry, and jumps for volatility prediction, non-linear dynamic model of the variance risk premium, pricing with finite dimensional dependence, quanto option pricing in the presence of fat tails and asymmetric dependence, smile from the past: a general option pricing framework with multiple volatility and leverage components, COMFORT: A common market factor non-Gaussian returns model, divided governments and futures prices, and model-based pricing for financial derivatives.Hedge Fund Portfolio Diversification Strategies across the GFC
http://repub.eur.nl/pub/77397/
Mon, 08 Dec 2014 00:00:01 GMT<div>D.E. Allen</div><div>M.J. McAleer</div><div>S. Peiris</div><div>A.K. Singh</div>
__Abstract__
This paper features an analysis of the eectiveness of a range of portfolio diversication strategies as applied to a set of 17 years of monthly hedge fund index returns on a set of ten market indices representing 13 major hedge fund
categories, as compiled by the EDHEC Risk Institute. The 17-year period runs from the beginning of 1997 to the end of August 2014. The sample period, which incorporates both the Global Financial Crisis (GFC) and subsequent European
Debt Crisis (EDC), is a challenging one for the application of diversication and portfolio investment strategies. The analysis features an examination of the di-
versication benets of hedge fund investments through successive crisis periods. The connectedness of the Hedge Fund Indices is explored via application of the Diebold and Yilmaz (2009, 2014) spillover index. We conduct a series of portfolio optimisation analyses: comparing Markowitz with naive diversication, and evaluate the relative eectiveness of Markowitz portfolio optimisation with various draw-down strategies, using a series of backtests. Our results suggest that Markowitz optimisation matches the characteristics of these hedge fund indices quite well.European Market Portfolio Diversification Strategies across the GFC
http://repub.eur.nl/pub/77117/
Thu, 16 Oct 2014 00:00:01 GMT<div>D.E. Allen</div><div>M.J. McAleer</div><div>R.J. Powell</div><div>A.K. Singh</div>
__Abstract__
is paper features an analysis of the effectiveness of a range of portfolio diversification strategies as applied to a set of daily arithmetically compounded returns on a set of ten market indices representing the major European markets for a nine year period from the beginning of 2005 to the end of 2013. The sample period, which incorporates the periods of both the Global Financial Crisis (GFC) and subsequent European Debt Crisis (EDC), is challenging one for the application of portfolio investment strategies. The analysis is undertaken via the examination of multiple investment strategies and a variety of hold-out periods
and back-tests. We commence by using four two year estimation periods and subsequent one year investment hold out period, to analyse a naive 1/N diversification strategy, and to contrast its effectiveness with Markowitz mean variance analysis with positive weights. Markowitz optimisation is then compared with various down-side investment opimisation strategies. We begin by comparing Markowitz with CVaR, and then proceed to evaluate the relative effectiveness of Markowitz with various draw-down strategies, utilising a series of backtests.
Our results suggest that none of the more sophisticated optimisation strategies appear to dominate naive diversification.Asymmetry and Leverage in Conditional Volatility Models
http://repub.eur.nl/pub/77115/
Thu, 18 Sep 2014 00:00:01 GMT<div>M.J. McAleer</div>
__Abstract__
The three most popular univariate conditional volatility models are the generalized autoregressive conditional heteroskedasticity (GARCH) model of Engle (1982) and Bollerslev (1986), the GJR (or threshold GARCH) model of Glosten, Jagannathan and Runkle (1992), and the exponential GARCH (or EGARCH) model of Nelson (1990, 1991). The underlying stochastic specification to obtain GARCH was demonstrated by Tsay (1987), and that of EGARCH was shown recently in McAleer and Hafner (2014). These models are important in estimating and forecasting volatility, as well as capturing asymmetry, which is the different effects on conditional volatility of positive and negative effects of equal magnitude, and leverage, which is the negative correlation between returns shocks and subsequent shocks to volatility. As there seems to be some confusion in the literature between asymmetry and leverage, as well as which asymmetric models are purported to be able to capture leverage, the purpose of the paper is two-fold, namely: (1) to derive the GJR model from a random coefficient autoregressive process, with appropriate regularity conditions; and (2) to show that leverage is not possible in these univariate conditional volatility models.Asymmetry and Leverage in Conditional Volatility Models
http://repub.eur.nl/pub/77759/
Mon, 01 Sep 2014 00:00:01 GMT<div>M.J. McAleer</div>
__Abstract__
The three most popular univariate conditional volatility models are the generalized autoregressive conditional heteroskedasticity (GARCH) model of Engle (1982) and Bollerslev (1986), the GJR (or threshold GARCH) model of Glosten, Jagannathan and Runkle (1992), and the exponential GARCH (or EGARCH) model of Nelson (1990, 1991). The underlying stochastic specification to obtain GARCH was demonstrated by Tsay (1987), and that of EGARCH was shown recently in McAleer and Hafner (2014). These models are important in estimating and forecasting volatility, as well as capturing asymmetry, which is the different effects on conditional volatility of positive and negative effects of equal magnitude, and leverage, which is the negative correlation between returns shocks and subsequent shocks to volatility. As there seems to be some confusion in the literature between asymmetry and leverage, as well as which asymmetric models are purported to be able to capture leverage, the purpose of the paper is two-fold, namely: (1) to derive the GJR model from a random coefficient autoregressive process, with appropriate regularity conditions; and (2) to show that leverage is not possible in these univariate conditional volatility models.Volatility Spillovers from Australia's Major Trading Partners across the GFC
http://repub.eur.nl/pub/77092/
Thu, 14 Aug 2014 00:00:01 GMT<div>D.E. Allen</div><div>M.J. McAleer</div><div>R.J. Powell</div><div>A.K. Singh</div>
__Abstract__
This paper features an analysis of volatility spillover effects from Australia's major trading partners,
namely, China, Japan, Korea and the United States, for a period running from 12th September
2002 to 9th September 2012. This captures the impact of the Global Financial Crisis (GFC). These
markets are represented by the following major indices: The Shanghai composite and the Hangseng.
(in the case of China, as both China and Hong Kong appear in Australian trade statistics), the
S&P500 index, the Nikkei225 and the Kospi index. We apply the Diebold and Yilmaz (2009)
Spillover Index, constructed in a VAR framework, to assess spillovers across these markets in returns
and in volatilities. The analysis confirms that the US and Hong Kong markets have the greatest
influence on the Australian one. We then move to a GARCH framework to apply further analysis
and apply a tri-variate Cholesky-GARCH model to explore the effects from the US and Chinese
market, as represented by the Hang Seng Index.A One Line Derivation of DCC: Application of a
Vector Random Coefficient Moving Average
Process
http://repub.eur.nl/pub/51652/
Fri, 11 Jul 2014 00:00:01 GMT<div>C.M. Hafner</div><div>M.J. McAleer</div>
__Abstract__
One of the most widely-used multivariate conditional volatility models is the dynamic conditional correlation (or DCC) specification. However, the underlying stochastic process to derive DCC has not yet been established, which has made problematic the derivation of asymptotic properties of the Quasi-Maximum Likelihood Estimators (QMLE). To date, the statistical properties of the QMLE of the DCC parameters have been derived under highly restrictive and unverifiable regularity conditions. The paper shows that the DCC model can be obtained from a vector random coefficient moving average process, and derives the stationarity and invertibility conditions. The derivation of DCC from a vector random coefficient moving average process raises three important issues: (i) demonstrates that DCC is, in fact, a dynamic conditional covariance model of the returns shocks rather than a dynamic conditional correlation model; (ii) provides the motivation, which is presently missing, for standardization of the conditional covariance model to obtain the conditional correlation model; and (iii) shows that the appropriate ARCH or GARCH model for DCC is based on the standardized shocks rather than the returns shocks. The derivation of the regularity conditions should subsequently lead to a solid statistical foundation for the estimates of the DCC parameters.On the Invertibility of EGARCH
http://repub.eur.nl/pub/51693/
Tue, 01 Jul 2014 00:00:01 GMT<div>G.G. Martinet</div><div>M.J. McAleer</div>
__Abstract__
Of the two most widely estimated univariate asymmetric conditional volatility models, the exponential GARCH (or EGARCH) specification can capture asymmetry, which refers to the different effects on conditional volatility of positive and negative effects of equal magnitude, and leverage, which refers to the negative correlation between the returns shocks and subsequent shocks to volatility. However, the statistical properties of the (quasi-) maximum likelihood estimator (QMLE) of the EGARCH parameters are not available under general conditions, but only for special cases under highly restrictive and unverifiable conditions. A limitation in the development of asymptotic properties of the QMLE for EGARCH is the lack of an invertibility condition for the returns shocks underlying the model. It is shown in this paper that the EGARCH model can be derived from a stochastic process, for which the invertibility conditions can be stated simply and explicitly. This will be useful in re-interpreting the existing properties of the QMLE of the EGARCH parameters.On the Invertibility of EGARCH
http://repub.eur.nl/pub/51750/
Tue, 01 Jul 2014 00:00:01 GMT<div>G.G. Martinet</div><div>M.J. McAleer</div>
__Abstract__
Of the two most widely estimated univariate asymmetric conditional volatility models, the exponential GARCH (or EGARCH) specification can capture asymmetry, which refers to the different effects on conditional volatility of positive and negative effects of equal magnitude, and leverage, which refers to the negative correlation between the returns shocks and subsequent shocks to volatility. However, the statistical properties of the (quasi-) maximum likelihood estimator (QMLE) of the EGARCH parameters are not available under general conditions, but only for special cases under highly restrictive and unverifiable conditions. A limitation in the development of asymptotic properties of the QMLE for EGARCH is the lack of an invertibility condition for the returns shocks underlying the model. It is shown in this paper that the EGARCH model can be derived from a stochastic process, for which the invertibility conditions can be stated simply and explicitly. This will be useful in re-interpreting the existing properties of the QMLE of the EGARCH parameters.Asymmetric Realized Volatility Risk
http://repub.eur.nl/pub/51551/
Mon, 23 Jun 2014 00:00:01 GMT<div>D.E. Allen</div><div>M.J. McAleer</div><div>M. Scharth</div>
__Abstract__
In this paper we document that realized variation measures constructed from high-frequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation measures are nearly gaussian, this unpredictability brings considerably more uncertainty to the empirically relevant ex ante distribution of returns. Explicitly modeling this volatility risk is fundamental.
We propose a dually asymmetric realized volatility model, which incorporates the fact that realized volatility series are systematically more volatile in high volatility periods. Returns in this framework display time varying volatility, skewness and kurtosis. We provide a detailed
account of the empirical advantages of the model using data on the S&P 500 index and eight other indexes and stocks.Advances in Financial Risk Management and
Economic Policy Uncertainty:
An Overview
http://repub.eur.nl/pub/51552/
Mon, 23 Jun 2014 00:00:01 GMT<div>S.M. Hammoudeh</div><div>M.J. McAleer</div>
__Abstract__
Financial risk management is difficult at the best of times, but especially so in the presence of economic uncertainty and financial crises. The purpose of this special issue on “Advances in Financial Risk Management and Economic Policy Uncertainty” is to highlight some areas of research in which novel econometric, financial econometric and empirical finance methods have contributed significantly to the analysis of financial risk management when there is economic uncertainty, especiallythe power of print: uncertainty shocks, markets, and the economy,
determinants of the banking spread in the Brazilian economy: the role of micro and macroeconomic factors, forecasting value-at-risk using block structure multivariate stochastic volatility models, the time-varying causality between spot and futures crude oil prices: a regime switching approach, a regime-dependent assessment of the information transmission dynamics between oil prices, precious metal prices and exchange rates, a practical approach to constructing price-based funding liquidity factors, realized range volatility forecasting: dynamic features and predictive variables, modelling a latent daily tourism financial conditions index, bank ownership, financial segments and the measurement of systemic risk: an application of CoVaR, model-free volatility indexes in the financial literature: a review, robust hedging performance and volatility risk in option markets: application to Standard and Poor’s 500 and Taiwan index options, price cointegration between sovereign CDS and currency option markets in the global financial crisis, whether zombie lending should always be prevented, preferences of risk-averse and risk-seeking investors for oil spot and futures before, during and after the global financial crisis, managing financial risk in Chinese stock markets: option pricing and modeling under a multivariate threshold autoregression, managing systemic risk in The Netherlands, mean-variance portfolio methods for energy policy risk management, on robust properties of the SIML estimation of volatility under micro-market noise and random sampling, asymmetric large-scale (I)GARCH with hetero-tails, the economic fundamentals and economic policy uncertainty of Mainland China and their impacts on Taiwan and Hong Kong, prediction and simulation using simple models characterized by nonstationarity and seasonality, and volatility forecast of stock indexes by model averaging using high frequency data.Survival Analysis of very Low Birth Weight
Infant Mortality in Taiwan
http://repub.eur.nl/pub/51528/
Sun, 01 Jun 2014 00:00:01 GMT<div>C. Chang</div><div>W. Chen</div><div>M.J. McAleer</div>
__Abstract__
This paper examines the determinants of very low birth weight infant (or neonatal) mortality using the Taiwan National Health Insurance Research database from 1997 to 2009. After infants are discharged from hospital, it is not possible to track their mortality, so the Cox proportional hazard model is used to analyze the very low birth weight infant mortality rate. In order to clarify treatment responsibility and to avoid selective referral effects, we use the number of infants treated in the preceding five years to observe the effect of a physician’s and hospital’s medical experience on the mortality rate of hospitalized minimal birth weight infants. The empirical results show that, given disease control variables, a higher infant weight, higher quality hospitals, increased hospital medical experience, and higher investment in pediatrics can reduce the mortality rate significantly. However, an increased physician’s medical experience does not seem to influence significantly the very low birth weight infant mortality rate.A One Line Derivation of EGARCH
http://repub.eur.nl/pub/51529/
Sun, 01 Jun 2014 00:00:01 GMT<div>M.J. McAleer</div><div>C.M. Hafner</div>
__Abstract__
One of the most popular univariate asymmetric conditional volatility models is the exponential GARCH (or EGARCH) specification. In addition to asymmetry, which captures the different effects on conditional volatility of positive and negative effects of equal magnitude, EGARCH can also accommodate leverage, which is the negative correlation between returns shocks and subsequent shocks to volatility. However, there are as yet no statistical properties available for the (quasi-) maximum likelihood estimator of the EGARCH parameters. It is often argued heuristically that the reason for the lack of statistical properties arises from the presence in the model of an absolute value of a function of the parameters, which does not permit analytical derivatives or the derivation of statistical properties. It is shown in this paper that: (i) the EGARCH model can be derived from a random coefficient complex nonlinear moving average (RCCNMA) process; and (ii) the reason for the lack of statistical properties of the estimators of EGARCH is that the stationarity and invertibility conditions for the RCCNMA process are not known.A One Line Derivation of EGARCH
http://repub.eur.nl/pub/51742/
Sun, 01 Jun 2014 00:00:01 GMT<div>M.J. McAleer</div><div>C.M. Hafner</div>
__Abstract__
One of the most popular univariate asymmetric conditional volatility models is the exponential GARCH (or EGARCH) specification. In addition to asymmetry, which captures the different effects on conditional volatility of positive and negative effects of equal magnitude, EGARCH can also accommodate leverage, which is the negative correlation between returns shocks and subsequent shocks to volatility. However, there are as yet no statistical properties available for the (quasi-) maximum likelihood estimator of the EGARCH parameters. It is often argued heuristically that the reason for the lack of statistical properties arises from the presence in the model of an absolute value of a function of the parameters, which does not permit analytical derivatives or the derivation of statistical properties. It is shown in this paper that: (i) the EGARCH model can be derived from a random coefficient complex nonlinear moving average (RCCNMA) process; and (ii) the reason for the lack of statistical properties of the estimators of EGARCH is that the stationarity and invertibility conditions for the RCCNMA process are not known.Survival Analysis of Very Low Birth Weight Infant Mortality in Taiwan
http://repub.eur.nl/pub/51743/
Sun, 01 Jun 2014 00:00:01 GMT<div>C. Chang</div><div>W. Chen</div><div>M.J. McAleer</div>
__Abstract__
This paper examines the determinants of very low birth weight infant (or neonatal) mortality using the Taiwan National Health Insurance Research database from 1997 to 2009. After infants are discharged from hospital, it is not possible to track their mortality, so the Cox proportional hazard model is used to analyze the very low birth weight infant mortality rate. In order to clarify treatment responsibility and to avoid selective referral effects, we use the number of infants treated in the preceding five years to observe the effect of a physician’s and hospital’s medical experience on the mortality rate of hospitalized minimal birth weight infants. The empirical results show that, given disease control variables, a higher infant weight, higher quality hospitals, increased hospital medical experience, and higher investment in pediatrics can reduce the mortality rate significantly. However, an increased physician’s medical experience does not seem to influence significantly the very low birth weight infant mortality rate.