This paper assesses the impact of US policy responses to the Covid-19 pandemic on various cryptocurrencies and also technology stocks using fractional integration techniques. More precisely, it analyses the behaviour of the percentage returns in the case of nine major coins (Bitcoin - BITC,...

We develop a new targeted maximum likelihood estimation method that provides improved forecasting for misspecified linear autoregressive models. The method weighs data points in the observed sample and is useful in the presence of data generating processes featuring structural breaks, complex...

This paper uses R/S analysis and fractional integration techniques to examine the persistence of two sets of 12 ESG and conventional stock price indices from the MSCI database over the period 2007-2020 for a large number of both developed and emerging markets. Both sets of results imply that...

This paper employs a price-based measure of integration, namely stock return differentials between ten emerging Asian economies and the US (as an indicator of global integration), as well as Japan and the Asian region (as two alternative indicators of regional integration), to test for mean...

This paper employs a price-based measure of integration, namely stock return differentials between ten emerging Asian economies and the US (as an indicator of global integration), as well as Japan and the Asian region (as two alternative indicators of regional integration), to test for mean...

Making use of restrictions imposed by equilibrium, theoretical progress has been made on the nonparametric and semiparametric estimation and identification of scalar additive hedonic models (Ekeland, Heckman, and Nesheim, 2002) and scalar nonadditive hedonic models (Heckman, Matzkin, and...

This paper considers the identification and estimation of hedonic models. We establish that in an additive version of the hedonic model, technology and preferences are generically identified up to affine transformations from data on demand and supply in a single hedonic market. For a very...

We develop a multivariate unobserved components model to extract business cycle and financial cycle indicators from a panel of economic and financial time series of four large developed economies. Our model is flexible and allows for the inclusion of cycle components in different selections of...

We propose a novel multivariate GARCH model that incorporates realized measures for the variance matrix of returns. The key novelty is the joint formulation of a multivariate dynamic model for outer-products of returns, realized variances and realized covariances. The updating of the variance...