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Metcalfe's law and log-period power laws in the cryptocurrencies market

Pele, Daniel Traian; Mazurencu-Marinescu-Pele, Miruna - In: Economics: The Open-Access, Open-Assessment E-Journal 13 (2019) 2019-29, pp. 1-26

In this paper the authors investigate the statistical properties of some cryptocurrencies by using three layers of analysis: alpha-stable distributions, Metcalfe's law and the bubble behaviour through the LPPL modelling. The results show, in the medium to long-run, the validity of Metcalfe's law...

Persistent link: https://www.econbiz.de/10012007754

Exchange-rates volatility in Nigeria: Application of GARCH models with exogenous break

Bala, Dahiru A.; Asemota, Joseph O. - In: CBN Journal of Applied Statistics 04 (2013) 1, pp. 89-116

This paper examines exchange-rate volatility with GARCH models using monthly exchange-rate return series from 1985:1 to 2011:7 for Naira/US dollar return and from 2004:1 to 2011:7 for Naira/British Pounds and Naira/Euro returns. The study compare estimates of variants of GARCH models with break...

Persistent link: https://www.econbiz.de/10011482587

From zero to hero: Realized partial (co)variances

Bollerslev, Tim; Medeiros, Marcelo C.; Patton, Andrew J.; … - 2021

This paper proposes a generalization of the class of realized semivariance and semicovariance measures introduced by Barndorff-Nielsen, Kinnebrock and Shephard (2010) and Bollerslev, Li, Patton and Quaedvlieg (2020a) to allow for a finer decomposition of realized (co)variances. The new "realized...

Persistent link: https://www.econbiz.de/10012817062

Right on target, or is it? The role of distributional shape in variance targeting

Anatolyev, Stanislav A.; Khrapov, Stanislav - In: Econometrics 3 (2015) 3, pp. 610-632

Estimation of GARCH models can be simplified by augmenting quasi-maximum likelihood (QML) estimation with variance targeting, which reduces the degree of parameterization and facilitates estimation. We compare the two approaches and investigate, via simulations, how non-normality features of the...

Persistent link: https://www.econbiz.de/10011755296

Volatility forecasting: Downside risk, jumps and leverage effect

Audrino, Francesco; Hu, Yujia - In: Econometrics 4 (2016) 1, pp. 1-24

We provide empirical evidence of volatility forecasting in relation to asymmetries present in the dynamics of both … return and volatility processes. Using recently-developed methodologies to detect jumps from high frequency price data, we … estimate the size of positive and negative jumps and propose a methodology to estimate the size of jumps in the quadratic …

Persistent link: https://www.econbiz.de/10011755317

Exchange rate risk premium: An analysis of its determinants for the Mexican Peso-USD

Benavides, Guillermo - 2016

The objective of this paper is to analyze what are the main determinants of the exchange rate risk premium (ERP). The empirical case is conducted for the daily Mexican peso-USD exchange rate for a sample period from 2007 until 2015. According to the results the ERP is influenced by several...

Persistent link: https://www.econbiz.de/10011788935

FloGARCH: Realizing long memory and asymmetries in returns volatility

Vander Elst, Harry - 2015

related to the FloGARCH models in terms of in-sample fit, out-of-sample fit and forecasting accuracy compared to classical and …

Persistent link: https://www.econbiz.de/10011506800

Cryptocurrencies, Metcalfe's law and LPPL models

Pele, Daniel Traian; Mazurencu-Marinescu-Pele, Miruna - 2018

In this paper we investigate the statistical properties of cryptocurrencies by using alpha-stable distributions. We also study the benefits of the Metcalfe's law (the value of a network is proportional to the square of the number of connected users of the system) for the evaluation of...

Persistent link: https://www.econbiz.de/10012433205

Forecasting volatility with Copula-based time series models

Sokolinskiy, Oleg; Dijk, Dick van - 2011

Persistent link: https://www.econbiz.de/10009720755

Predicting time-varying parameters with parameter-driven and observation-driven models

Koopman, Siem Jan; Lucas, André; Scharth, Marcel - 2012

Persistent link: https://www.econbiz.de/10009722696