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In a Constant Proportion Portfolio Insurance (CPPI) framework, a constant risk exposure is defined by the multiple of the strategy. This article proposes an alternative conditional multiple estimation model, which is based on an autoregressive quantile regression dynamic approach. We estimate...
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demand function sometimes yield unsatisfactory results: instability of short and long-term coefficients, relatively large …-run relations. Hence the idea of constructing a money demand function that excludes the external counterpart of M3 or, alternatively …, introducing financial asset prices in the demand function of M3, as suggested by Friedman (1988). First, the basic equation, based …
Persistent link: https://www.econbiz.de/10004998851
We consider the problem of testing whether the observations X1, · · ·, Xn of a time series are independent with unspecified (possibly nonidentical) distributions symmetric about a common known median. Various bounds on the distributions of serial correlation coefficients are proposed:...
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In this paper, we develop finite-sample inference procedures for stationary and nonstationary autoregressive (AR) models. The method is based on special properties of Markov processes and a split-sample technique. The results on Markovian processes (intercalary independence and truncation) only...
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seasonal behaviors of tourist stay demand in Tunisia by using recent tools of monthly time series analysis. The available … demand and the theory of supply induced demand. Empirical results show that these series are generated by non stationary …
Persistent link: https://www.econbiz.de/10005579069
specifications of the money demand function sometimes yield unsatisfactory results : instability of short and long-term coefficients … of long-run relations. Hence the idea of constructing a money demand function that excludes the external counterpart of M …3 or, alternatively, introducing financial asset prices in the demand function of M3, as suggested by Friedman (1988 …
Persistent link: https://www.econbiz.de/10008800016