http://repub.eur.nl/res/aut/5768/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/34950/ 2012-01-23T00:00:00Z We propose a class of observation-driven 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 time-varying parameters in a wide class of nonlinear models. The GAS model encompasses other well-known models such as the generalized autoregressive conditional heteroskedasticity, autoregressive conditional duration, autoregressive conditional intensity, and Poisson count models with time-varying mean. In addition, our approach can lead to new formulations of observation-driven models. We illustrate our framework by introducing new model specifications for time-varying copula functions and for multivariate point processes with time-varying parameters. We study the models in detail and provide simulation and empirical evidence. http://repub.eur.nl/res/pub/2179/ 2004-02-01T00:00:00Z 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. http://repub.eur.nl/res/pub/6876/ 2001-02-12T00:00:00Z Using US data from June 1984 to July 1999, we show that the impact of firm-specific characteristics like size and book-to-price 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 state-dependent choice of investment styles rather than a once-and-for-all choice for a particular style, for example based on high book-to-price 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. http://repub.eur.nl/res/pub/2175/ 2000-08-01T00:00:00Z 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 cost-of-carry model of futures prices we estimate (non-linearly) 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 pre-SETS and post-SETS 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 post-SETS period. These results suggest that both spot and futures markets have become more efficient under SETS. http://repub.eur.nl/res/pub/1589/ 1999-04-26T00:00:00Z 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. http://repub.eur.nl/res/pub/11154/ 1999-01-01T00:00:00Z 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. http://repub.eur.nl/res/pub/11157/ 1999-01-01T00:00:00Z Regime-switching 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 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. 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. http://repub.eur.nl/res/pub/7729/ 1999-01-01T00:00:00Z 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 cost-of-carry model of futures prices we estimate (non-linearly) 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 pre-SETS and post-SETS 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 post-SETS period. http://repub.eur.nl/res/pub/13824/ 1998-11-01T00:00:00Z 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 non-stationary characteristics. Therefore, we use cointegration techniques to quantify the long-run effects of marketing efforts. Since weekly scanning data can contain aberrant observations due to, e.g., out-of-stock 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 non-robust methods for the long-run marketing effects. http://repub.eur.nl/res/pub/7746/ 1998-09-08T00:00:00Z We advocate the use of absolute moment ratio statistics in conjunction with standard variance ratio statistics in order to disentangle linear dependence, non-linear 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 block-bootstrapped 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. http://repub.eur.nl/res/pub/2146/ 1998-01-01T00:00:00Z Standard unit-root and cointegration tests are sensitive to atypical events such as outliers and structural breaks. Outlier-robust estimation techniques are used to examine the impact of these events on cointegration analysis. The outlier-robust 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. http://repub.eur.nl/res/pub/12475/ 1997-12-16T00:00:00Z 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 fat-tailedness. one should look simultaneously at plots based on absolute returns and variances. If the distribution is heavy-tailed, 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. http://repub.eur.nl/res/pub/10454/ 1996-01-25T00:00:00Z This book focuses on statistical methods for discriminating between competing models for the long-run 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, Monte-Carlo 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 long-run behavior of economic processes. http://repub.eur.nl/res/pub/1382/ 1996-01-01T00:00:00Z Regime-switching 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. http://repub.eur.nl/res/pub/1390/ 1996-01-01T00:00:00Z In this paper we consider empirical econometric models for nine brands of fast-moving 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 long-run and short-run 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 non-robust methods for the long-run relations between market share and distribution and for the short-run response to disequilibrium situations. http://repub.eur.nl/res/pub/1395/ 1996-01-01T00:00:00Z 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. http://repub.eur.nl/res/pub/12409/ 1995-09-01T00:00:00Z 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.