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In this study we investigate possible long-range trends in the cryptocurrency market. We employed the Hurst exponent in a sample covering the period from 1 January 2016 to 26 March 2021. We calculated the Hurst exponent in three non-overlapping consecutive windows and in the whole sample. Using...
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using the sample autocorrelation function (ACF) to identify long-memory processes. While the ACF establishes the theoretical …
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This article defines the Autoregressive Fractional Unit Root Integrated Moving Average (ARFURIMA) model for modelling ILM time series with fractional difference value in the interval of 1൏𝑑൏2. The performance of the ARFURIMA model is examined through a Monte Carlo simulation. Also, some...
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Starting from an information process governed by a geometric Brownian motion we show that asset returns are predictable if the elasticity of the pricing kernel is not constant. Declining [Increasing] elasticity of the pricing kernel leads to mean reversion and negatively autocorrelated asset...
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autocorrelation dynamics of firm growth. We use firm level data of 1000 European companies with details on R&D investments in 2003 to … autocorrelation dynamics of firm growth. We find that R&D has, on average, a positive effect on firm growth, but the effect and its …
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We consider the finite sample power of various tests against serial correlation in the disturbances of a linear regression when these disturbances follow a stationary long memory process. It emerges that the power depends on the form of the regressor matrix and that, for the Durbin-Watson test...
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