A. Lucas (AndrĂ©)
http://repub.eur.nl/ppl/5768/
List of Publications
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Generalized Autoregressive Score Models with Applications
http://repub.eur.nl/pub/34950/
Mon, 23 Jan 2012 00:00:01 GMT
<div>D. Creal</div><div>S.J. Koopman</div><div>A. Lucas</div>
We propose a class of observationdriven time series models referred to as generalized autoregressive score (GAS) models. The mechanism to update the parameters over time is the scaled score of the likelihood function. This new approach provides a unified and consistent framework for introducing timevarying parameters in a wide class of nonlinear models. The GAS model encompasses other wellknown models such as the generalized autoregressive conditional heteroskedasticity, autoregressive conditional duration, autoregressive conditional intensity, and Poisson count models with timevarying mean. In addition, our approach can lead to new formulations of observationdriven models. We illustrate our framework by introducing new model specifications for timevarying copula functions and for multivariate point processes with timevarying parameters. We study the models in detail and provide simulation and empirical evidence.

Short patches of outliers, ARCH and volatility modeling
http://repub.eur.nl/pub/2179/
Sun, 01 Feb 2004 00:00:01 GMT
<div>Ph.H.B.F. Franses</div><div>D.J.C. van Dijk</div><div>A. Lucas</div>
The (Generalized) AutoRegressive Conditional Heteroscedasticity [(G)ARCH] model is tested for daily data on 22 exchange rates and 13 stock market indices using the standard Lagrange Multiplier [LM] test for GARCH and a LM test that is resistant to patches of additive outliers. The data span two samples of five years ranging from 1986 to 1995. Using asymptotic arguments and Monte Carlo simulations, in which the empirical method is evaluated, it is shown that patches of outliers can have significant effects on test outcomes. The main empirical result is that spurious GARCH is found in about 40% of the cases, while in many other cases evidence of GARCH is found even though such sequences of extraordinary observations seem to be present.

Stock Selection, Style Rotation, and Risk
http://repub.eur.nl/pub/6876/
Mon, 12 Feb 2001 00:00:01 GMT
<div>A. Lucas</div><div>R. van Dijk</div><div>T. Kloek</div>
Using US data from June 1984 to July 1999, we show that the impact of firmspecific characteristics like size and booktoprice on future excess stock returns varies considerably over time. The impact can be either positive or negative at different times. This time variation is partially predictable. We investigate whether the partial predictability signals security mispricing or risk compensation by formulating alternative modeling strategies. The strategies are compared empirically, In particular, we allow for a statedependent choice of investment styles rather than a onceandforall choice for a particular style, for example based on high booktoprice ratios or small market cap values. Using alternative ways to correct for risk, we find significant and robust excess returns to style rotating investment strategies. Business cycle oriented approaches exhibit the best overall performance. Purely statistical models for style rotation or fixed investment styles reveal less robust behavior.

SETS, arbitrage activity, and stock price dynamics
http://repub.eur.nl/pub/2175/
Tue, 01 Aug 2000 00:00:01 GMT
<div>Ph.H.B.F. Franses</div><div>N. Taylor</div><div>D.J.C. van Dijk</div><div>A. Lucas</div>
This paper provides an empirical description of the relationship between the trading system operated by a stock exchange and the trading behaviour of heterogeneous investors who use the exchange. The recent introduction of SETS in the London Stock Exchange provides an excellent opportunity to study the impact of an electronic trading system upon traders who use the exchange. Using the costofcarry model of futures prices we estimate (nonlinearly) the transaction costs and trade speeds faced by arbitragers who take advantage of mispricing of FTSE100 futures contracts relative to the spot prices of the stocks that make up the FTSE100 stock index. We divide the sample period into preSETS and postSETS sample periods and conduct a comparative study of arbitrager behaviour under different trading systems. The results indicate that there has been a significant reduction in the level of transaction costs faced by arbitragers and in the degree of transaction cost heterogeneity. Finally, generalised impulse response functions show that both spot and futures prices adjust more quickly in the postSETS period. These results suggest that both spot and futures markets have become more efficient under SETS.

Arbitrage and sampling uncertainty in financial stochastic programming models
http://repub.eur.nl/pub/1589/
Mon, 26 Apr 1999 00:00:01 GMT
<div>A.B. Berkelaar</div><div>H. Hoek</div><div>A. Lucas</div>
Asset liability management (ALM) is an important and challenging
problem for institutional investors and financial intermediaries. The
requirement to fulfill its liablilities constrains the institutional
investor in its asset allocation possiblilites. We formulate an ALM
model for pension funds as a multistage stochastic programming model.
Relevant variables such as future inflation rates, stock retruns, and
bond yields are unknown. This is incorporated in the ALM model by
means of an event tree, which represents the expected development of
the economic variables as well as the corresponding uncertainty.
The event tree is constructed by sampling from a time series model
for the variables, and is therefore subject to sampling uncertainty.
Moreover, for the event tree to be realistic, it is required not to
exhibit arbitrage opportunies. In ths paper we examine the effect
of sampling uncertainty and the structure of the event tree on the
optimal policies. Furthermore, we consider the effect of random
sampling and the tree structure on the probability of arbitragefree
trees. We also compare the optimal solutions to the ALM problem for
trees with an without arbitrage. For these purposes, we consider
data from a Dutch pension fund.

Testing for ARCH in the presence of additive outliers
http://repub.eur.nl/pub/11154/
Fri, 01 Jan 1999 00:00:01 GMT
<div>D.J.C. van Dijk</div><div>Ph.H.B.F. Franses</div><div>A. Lucas</div>
In this paper we investigate the properties of the Lagrange Multiplier [LM] test for autoregressive conditional heteroscedasticity (ARCH) and generalized ARCH (GARCH) in the presence of additive outliers (AOs). We show analytically that both the asymptotic size and power are adversely affected if AOs are neglected: the test rejects the null hypothesis of homoscedasticity too often when it is in fact true, while the test has difficulty detecting genuine GARCH effects. Several Monte Carlo experiments show that these phenomena occur in small samples as well. We design and implement a robust test, which has better size and power properties than the conventional test in the presence of AOs. We apply the tests to a number of US macroeconomic time series, which illustrates the dangers involved when nonrobust tests for ARCH are routinely applied as diagnostic tests for misspecification.

Testing for smooth transition nonlinearity in the presence of outliers
http://repub.eur.nl/pub/11157/
Fri, 01 Jan 1999 00:00:01 GMT
<div>D.J.C. van Dijk</div><div>Ph.H.B.F. Franses</div><div>A. Lucas</div>
Regimeswitching models, like the smooth transition autoregressive (STAR) model, are typically applied to time series of moderate length. Hence, the nonlinear features that these models intend to describe may be reflected in only a few observations. Conversely, neglected outliers in a linear time series of moderate length may incorrectly suggest STAR (or other) types of nonlinearity. Outlier robust tests are proposed for STARtype nonlinearity. These tests are designed such that they have a better level and power behavior than standard nonrobust tests in situations with outliers. Local and global robustness properties of the new tests are formally derived. Extensive Monte Carlo simulations show the practical usefulness of the robust tests. An application to several quarterly industrial production indexes illustrates that apparent nonlinearity in time series sometimes seems due to only a few outliers.

SETS, Arbitrage Activity, and Stock Price Dynamics
http://repub.eur.nl/pub/7729/
Fri, 01 Jan 1999 00:00:01 GMT
<div>N. Taylor</div><div>D.J.C. van Dijk</div><div>Ph.H.B.F. Franses</div><div>A. Lucas</div>
This paper provides an empirical description of the relationship between the trading system operated by a stock exchange and the transaction costs faced by heterogeneous investors who use the exchange. The recent introduction of SETS in the London Stock Exchange provides an excellent opportunity to study the impact of an electronic trading system upon transaction costs and the time taken to carry out a trade. Using the costofcarry model of futures prices we estimate (nonlinearly) the transaction costs and trade speeds faced by arbitragers who take advantage of mispricing of FTSE100 futures contracts relative to the spot prices of the stocks that make up the FTSE100 stock index. We divide the sample period into preSETS and postSETS sample periods and conduct a comparative study of arbitrager behaviour under different trading systems. The results indicate that there has been a significant reduction in the level of transaction costs faced by arbitragers and in the degree of transaction cost heterogeneity since the introduction of SETS. Finally, generalised impulse response functions show that both spot and futures prices adjust more quickly in the postSETS period.

Outlier robust analysis of longrun marketing effects for weekly scanning data
http://repub.eur.nl/pub/13824/
Sun, 01 Nov 1998 00:00:01 GMT
<div>Ph.H.B.F. Franses</div><div>T. Kloek</div><div>A. Lucas</div>
We consider econometric modeling of weekly observed scanning data on a fast moving consumer good (FMCG), with a specific focus on the relationship between market share, distribution, advertising, price, and promotion. Such data can show nonstationary characteristics. Therefore, we use cointegration techniques to quantify the longrun effects of marketing efforts. Since weekly scanning data can contain aberrant observations due to, e.g., outofstock situations or measurement errors, we favor an outlier robust cointegration method, which we outline in detail. In our illustrative FMCG example, we find different results across robust and nonrobust methods for the longrun marketing effects.

A Hybrid Joint Moment Ratio Test for Financial Time Series
http://repub.eur.nl/pub/7746/
Tue, 08 Sep 1998 00:00:01 GMT
<div>P.A. Groenendijk</div><div>A. Lucas</div><div>C.G. de Vries</div>
We advocate the use of absolute moment ratio statistics in conjunction with standard variance ratio statistics in order to disentangle linear dependence, nonlinear dependence, and leptokurtosis in financial time series. Both statistics are computed for multiple return horizons simultaneously, and the results are presented in a comprehensive way using a graphical device. We construct a formal joint testing procedure based on bootstrapped and blockbootstrapped uniform confidence intervals. The methodology is hybrid because it combines a formal testing procedure with volatility curve pattern recognition based on expert opinions. An application to forex data illustrates the procedure.

Outlier detection in cointegration analysis
http://repub.eur.nl/pub/2146/
Thu, 01 Jan 1998 00:00:01 GMT
<div>Ph.H.B.F. Franses</div><div>A. Lucas</div>
Standard unitroot and cointegration tests are sensitive to atypical events such as outliers and structural breaks. Outlierrobust estimation techniques are used to examine the impact of these events on cointegration analysis. The outlierrobust cointegration test provides a new diagnostic tool for signaling when standard cointegration results might be driven by a few aberrant observations. A main feature of the approach is that the proposed robust estimator can be used to compute weights for all observations, which in turn can be used to identify the approximate dates of atypical events. The method is evaluated using simulated data and a Monte Carlo experiment. An empirical example is provided showing the usefulness of the proposed analysis.

Stochastic processes, nonnormal innovations, and the use of scaling ratios
http://repub.eur.nl/pub/12475/
Tue, 16 Dec 1997 00:00:01 GMT
<div>P.A. Groenendijk</div><div>A. Lucas</div><div>C.G. de Vries</div>
hlarket efficiency tests that rely on the martingale difference behavior
of returns can be based on various volatility measures. This
paper argues that, to be able to differentiate between dependence and
fattailedness. one should look simultaneously at plots based on absolute
returns and variances. If the distribution is heavytailed, this
shows up in the absolute moment plots, but not in the variance related
plots. Linear dependence. by contrast, is revealed in both plots.
We provide and discuss an analytical and a simulation experime illustrating these points.

Outlier robust unit root analysis
http://repub.eur.nl/pub/10454/
Thu, 25 Jan 1996 00:00:01 GMT
<div>A. Lucas</div>
This book focuses on statistical methods for discriminating between competing models for the longrun behavior of economic time series. Traditional methods that are used in this context are sensitive to outliers in the data. Therefore, this book considers alternative methods that take into account the possibility that not all observations are generated by the postulated model. These methods are called outlier robust. The basic principle underlying outlier robust methods is that discordant observations are downweighted automatically. The use of weights has important consequences for the statistical properties of the methods discussed. These consequences are studied by means of asymptotic theory, MonteCarlo simulations, and empirical illustrations. Based on the results of this study, it is argued that outlier robust methods provide useful tools for applied researchers as the methods disclose valuable additional information about the longrun behavior of economic processes.

Testing for Smooth Transition Nonlinearity in the Presence of Outliers
http://repub.eur.nl/pub/1382/
Mon, 01 Jan 1996 00:00:01 GMT
<div>D.J.C. van Dijk</div><div>Ph.H.B.F. Franses</div><div>A. Lucas</div>
Regimeswitching models, like the smooth transition autoregressive (STAR) model are typically applied to time series of moderate length. Hence, the nonlinear features which these models intend to describe may be reflected in only a few observations.
Conversely, neglected outliers in a linear time series of moderate length may incorrectly suggest STAR type nonlinearity. In this paper we propose outlier robust tests for STAR type nonlinearity. These tests are designed such that they have a better level and power behavior than standard nonrobust tests in situations with outliers. We formally derive local and global robustness properties of the new tests. Extensive Monte Carlo simulations show the practical usefulness of the robust tests. An application to several quarterly industrial production indices illustrates that apparent nonlinearity in time series sometimes seems due to only a small number of outliers.

Outlier Robust Analysis of Market Share and Distribution Relations for Weekly Scanning Data
http://repub.eur.nl/pub/1390/
Mon, 01 Jan 1996 00:00:01 GMT
<div>Ph.H.B.F. Franses</div><div>T. Kloek</div><div>A. Lucas</div>
In this paper we consider empirical econometric models for nine brands of fastmoving nondurable consumer product using weekly observed scanning data on market share and distribution conditional on advertising, price, and promotion activities. Since the data show nonstationary characteristics, we rely on cointegration techniques to estimate longrun and shortrun parameters. Additionally, as there are many outlying observations in our weekly scanning data, we apply robust cointegration methods. We find different results across robust and nonrobust methods for the longrun relations between market share and distribution and for the shortrun response to disequilibrium situations.

Testing for ARCH in the Presence of Additive Outliers
http://repub.eur.nl/pub/1395/
Mon, 01 Jan 1996 00:00:01 GMT
<div>D.J.C. van Dijk</div><div>Ph.H.B.F. Franses</div><div>A. Lucas</div>
In this paper we investigate the properties of the Lagrange Multiplier (LM) test for autoregressive conditional heteroskedasticity (ARCH) and generalized ARCH (GARCH) in the presence of additive outliers (AO's). We show analytically that both the asymptotic size and power are adversely affected if AO's are neglected: the test rejects the null hypothesis of homoskedasticity too often when it is in fact true, while the test has difficulty detecting genuine GARCH effects. Several Monte Carlo experiments show that these phenomena occur in small samples as well. We design and implement a robust test, which has better size and power properties than the conventional test in the presence of AO's. Applications to the French industrial production series and weekly returns of the Spanish peseta/US dollar exchange rate reveal that, sometimes, apparent GARCH effects may be due to only a small number of outliers and, conversely, that genuine GARCH effects can be masked by outliers.

A note on the relationship between GARCH and symmetric stable processes
http://repub.eur.nl/pub/12409/
Fri, 01 Sep 1995 00:00:01 GMT
<div>P.A. Groenendijk</div><div>A. Lucas</div><div>C.G. de Vries</div>
This note provides some explanations and extensions for the interesting results in Ghose and Kroner (1995). Specifically, we address the following points: (1) It is shown that the stable distribution and the stationary ARCH distributions are partially nested with respect to their tail shapes; (2) A novel interpretation of the McCulloch estimator is developed from the vantage point of extreme value theory; (3) This interpretation not only explains the apparent bias in some of the reported estimates, but it also helps in remedying the problem. Taken together, all three points reinforce the main conclusion of Ghose and Kroner.