This study predicts stock market volatility and applies them to the standard problem in finance, namely, asset allocation. Based on machine learning and model averaging approaches, we integrate the drivers’ predictive information to forecast market volatilities. Using various evaluation...

Stablecoins are a bridge between fiat currencies and cryptocurrencies. As they are on-chain (on the blockchain) assets that are reliably pegged to the value of off-chain fiat currencies, users gain relatively low-risk access to store or trade fiat and cryptocurrencies. The two most important...

The rapid digitisation of the world made it clear that traditional money needs to be replaced with alternatives, otherwise we risk missing out on the future. Consequently, central banks around the world are examining whether and how they can introduce Central Bank Digital Currency. CBDC has...

This article contributes to the existing literature on European financial market integration by investigating whether the degree of integration between the Athens Stock Exchange (ASE) and three major euro zone stock markets has varied over time since the signing of the Maastricht treaty. To this...

An alternative definition for market efficiency, based on econometric rather than financial arguments is suggested. It is argued that this new definition, though equivalent to the existing one, has some comparative advantages. Moreover, the conditions under which the results from the application...

We introduce a novel GMM estimation procedure to assess conditional factor models without the need to specify a set of conditioning variables. The conditional Dollar-Carry (DOL-CAR) two factor pricing model is able to explain a rich cross-section of average currency returns. It is important to...

We measure bond and stock conditional return volatility as a function of changes in sentiment, proxied by six indicators from the Tel Aviv Stock Exchange. We find that changes in sentiment affect conditional volatilities at different magnitudes and often in an opposite manner in the two markets,...

This is the first paper about the high dimensional beta tests with high frequency financial data, which allowing that the number of regressors can be larger than the number of observations within each estimation block and can also grow to infinity in asymptotics. In this paper, the sum-type test...

Using overnight volatility as the proxy for overnight information, this paper models future Chinese stock market realized range-based volatility (RRV) within a class of heterogeneous autoregressive models augmented by this proxy. We confirm the important role of overnight information in...

This paper introduces novel volatility diffusion models to account for the stylized facts of high-frequency financial data such as volatility clustering, intra-day U-shape, and leverage effect. For example, the daily integrated volatility of the proposed volatility process has a realized GARCH...