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Market Efficiency and the Euro: The case of the Athens Stock Exchange
Panagiotidis, Theodore - EconWPA - 2005
. Bootstrap and asymptotic values of these tests are estimated. Alternative models from the GARCH family (GARCH, EGARCH and TGARCH …
Persistent link: https://www.econbiz.de/10005413222
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ON THE FORECASTABILITY OF ASEAN-5 STOCK MARKETS RETURNS USING TIME SERIES MODELS
Liew, Khim-Sen; Lim, Kian-Ping; Choong, Chee-Keong - EconWPA - 2003
. Time series models with GARCH errors are also considered. Based on formal econometrics tests, this study shows that the …
Persistent link: https://www.econbiz.de/10005076958
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Volatility in the Italian Stock Market: An Empirical Study
Raberto, Marco; Scalas, Enrico; Cuniberti, Gianaurelio; … - EconWPA - 2004
We study the volatility of the MIB30–stock–index high–frequency data from November 28, 1994 through September 15, 1995. Our aim is to empirically characterize the volatility random walk in the framework of continuous–time finance. To this end, we compute the index volatility by means of...
Persistent link: https://www.econbiz.de/10005413205
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CAN LONG HORIZON DATA BEAT RANDOM WALK UNDER ENGEL-WEST EXPLANATION?
Wang, Jian - EconWPA - 2005
Engel and West (2004a) provide an explanation to reconcile the random walk behavior of exchange rate and linear present value asset pricing models. In this paper, we study the long horizon property of exchange rate under Engel-West explanation. It is found that the long horizon data can not...
Persistent link: https://www.econbiz.de/10005556624
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Fractional calculus and continuous-time finance
Scalas, Enrico; Gorenflo, Rudolf; Mainardi, Francesco - EconWPA - 2004
In this paper we present a rather general phenomenological theory of tick-by-tick dynamics in financial markets. Many well-known aspects, such as the Lévy scaling form, follow as particular cases of the theory. The theory fully takes into account the non-Markovian and non-local character of...
Persistent link: https://www.econbiz.de/10005561606
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Correlations in the Bond–Future Market
Cuniberti, Gianaurelio; Raberto, Marco; Scalas, Enrico - EconWPA - 2004
We analyze the time series of overnight returns for the bund and btp futures exchanged at liffe (London). The overnight returns of both assets are mapped onto a one–dimensional symbolic–dynamics random walk: The “bond walk”. During the considered period (October 1991—January 1994) the...
Persistent link: https://www.econbiz.de/10005561683
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Are Exchange Rates Really Random Walks? Some Evidence Robust to Parameter Instability
Rossi, Barbara - EconWPA - 2005
Many authors have documented that it is challenging to explain exchange rate fluctuations with macroeconomic fundamentals: a random walk forecasts future exchange rates better than existing macroeconomic models. This paper applies newly developed tests for nested model that are robust to the...
Persistent link: https://www.econbiz.de/10005062396
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Are Exchange Rates Really Random Walks? Some Evidence Robust to Parameter Instability
Rossi, Barbara - EconWPA - 2005
Many authors have documented that it is challenging to explain exchange rate fluctuations with macroeconomic fundamentals: a random walk forecasts future exchange rates better than existing macroeconomic models. This paper applies newly developed tests for nested model that are robust to the...
Persistent link: https://www.econbiz.de/10005119462
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Measuring Tail Thickness under GARCH and an Application to Extreme Exchange Rate Changes
Wagner, Niklas; Marsh, Terry A. - EconWPA - 2004
properties of adaptive tail index estimators under the class of student-t marginal distribution functions including GARCH and … propose a model-based bias-corrected estimation approach. Our simulation results indicate that bias strongly relates to the … substantial differences in measured tail-thickness due to small sample bias. As a consequence, high quantile estimation may lead …
Persistent link: https://www.econbiz.de/10005407899
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One-Factor-GARCH Models for German Stocks - Estimation and Forecasting -
Kaiser, Thomas - EconWPA - 1996
factor models with GARCH dynamics (GARCH(1,1)-M, IGARCH(1,1)-M, Nonlinear Asymmetric GARCH(1,1)-M and Glosten …-Jagannathan-Runkle GARCH(1,1)-M) and three different distributions for the disturbances (Normal, Student's t and Generalized Error Distribution … compared with forecasts based on individual GARCH(1,1)-M models, static factor models, naive, random walk and exponential …
Persistent link: https://www.econbiz.de/10005407963