We establish that the risk-return tradeoff of cryptocurrencies (Bitcoin, Ripple, and Ethereum) is distinct from those of stocks, currencies, and precious metals. Cryptocurrencies have no exposure to most common stock market and macroeconomic factors. They also have no exposure to the returns of...

This article is concerned with the calibration of the empirical likelihood (EL) for high-dimensional data where the data dimension may increase as the sample size increases. We analyze the asymptotic behavior of the EL under a general multivariate model and provide weak conditions under which...

We apply empirical likelihood method to constructing confidence regions for the difference of the means of two d-dimensional samples. It is shown that the empirical likelihood ratio test has an asymptotic chi-squared distribution. The Bartlett correction for the univariate case (d=1) has been...

A nonparametric method based on the empirical likelihood is proposed to detect the change-point from a sequence of independent random variables. The empirical likelihood ratio test statistic is proved to have the same limit null distribution as that with classical parametric likelihood. Under...

We establish that the risk-return tradeoff of cryptocurrencies (Bitcoin, Ripple, and Ethereum) is distinct from those of stocks, currencies, and precious metals. Cryptocurrencies have no exposure to most common stock market and macroeconomic factors or to the returns of currencies and...

We establish that the risk-return tradeoff of cryptocurrencies (Bitcoin, Ripple, and Ethereum) is distinct from those of stocks, currencies, and precious metals. Cryptocurrencies have no exposure to most common stock market and macroeconomic factors. They also have no exposure to the returns of...

We construct a comprehensive dataset on a near universe of non-fungible token (NFT) transactions, create indices for the NFT market and its components, and analyze their properties. The NFT market return is significantly exposed to the cryptocurrency market return, but the majority of the NFT...

Using high-frequency data, we estimate and characterize the evolution of the factor structure of global asset returns across aggregate equity, fixed income and exchange rates over the period 2007-2020. We show how the factor structure of asset returns evolves through time, providing clear...