We observe that daily highs and lows of stock prices do not diverge over time and, hence, adopt the cointegration concept and the related vector error correction model (VECM) to model the daily high, the daily low, and the associated daily range data. The in-sample results attest the importance...

We observe that daily highs and lows of stock prices do not diverge over time and, hence, adopt the cointegration concept and the related vector error correction model (VECM) to model the daily high, the daily low, and the associated daily range data. The in-sample results attest the importance...

We observe that daily highs and lows of stock prices do not diverge over time and, hence, adopt the cointegration concept and the related vector error correction model (VECM) to model the daily high, the daily low, and the associated daily range data. The in-sample results attest the importance...

In the past twenty years, measures of economic uncertainty have been developed that are either purely market price-based, structural model-based using data on real fundamentals and asset prices, text-based, or survey-based. We compare the performance of these uncertainty measures in forecasting...

We observe that daily highs and lows of stock prices do not diverge over time and, hence, adopt the cointegration concept and the related vector error correction model (VECM) to model the daily high, the daily low, and the associated daily range data. The in-sample results attest the importance...

We present a detailed bubble analysis of the Bitcoin to US Dollar price dynamics from January 2012 to February 2018. We introduce a robust automatic peak detection method that classifies price time series into periods of uninterrupted market growth (drawups) and regimes of uninterrupted market...

Like no other calamitous event in recent memory, the COVID-19 pandemic has plunged the world’s financial system into disarray, triggering systemic risk spillovers across markets. In this study, we use 5-minute index futures price data to examine the multiscale interdependence structure of...

This paper considers the performance of different long-memory dynamic models when forecasting volatility in the stock market using implied volatility as an exogenous variable in the information set. Observed volatility is separated into its continuous and jump components in a framework that...

We construct an empirical model for daily highs and daily lows of US stock indexes based on the intuition that highs and lows do not drift apart over time. Our empirical results show that daily highs and lows of three main US stock price indexes are cointegrated. Data on openings, closings, and...

This paper analyzes volatility spillovers in multivariate GARCH-type models. We show that the cross-effects between the conditional variances determine the persistence of the transmitted volatility innovations. In particular, the effect of a foreign volatility innovation on a conditional...