We conducted a comprehensive analysis on the sequential introductions of dynamic and static volatility interruptions (VIs) in the Korean stock markets. The Korea Exchange introduced VIs to improve price formation, and to limit risk to investors from brief periods of abnormal volatility for...

This paper investigates the information content of the ex post overnight return for one-day-ahead equity Value-at-Risk (VaR) forecasting. To do so, we deploy a univariate VaR modeling approach that constructs the forecast at market open and, accordingly, exploits the available overnight...

We examine price discovery and liquidity provision in the secondary market for bitcoin-an asset with a high level of speculative trading. Based on BTC-e's full limit order book over the 2013-2014 period, we find that order informativeness increases with order aggressiveness within the first 10...

Both the scientific community and the popular press have paid much attention to the speed of the Securities Information Processor-the data feed consolidating all trades and quotes across the US stock market. Rather than the speed of the Securities Information Processor (SIP), we focus here on...

Concerns about the negative consequences of the excessive underpricing of the current arrangement in the initial public offering (IPO) market for the provision of entrepreneurial finance-book building-have led to research into the viability of auctions for IPO pricing and allocation. IPO firms...

This paper uses two highly liquid S&P 500 and gold exchange-traded funds (ETFs) to evaluate the impact of liquidity and macroeconomic news surprises on the frequency of observing intraday jumps. It explicitly addresses market microstructure noise-induced biases in realized estimators used in...

This paper studies price discovery in Nikkei 225 markets through the nonlinear smooth transition price adjustments between spot and future prices and across all three futures markets. We test for smooth transition nonlinearity and employ an exponential smooth transition error correction model...

In this paper, we examine the impact of destination risk and currency valuation on the U.S. tourism-growth nexus using the recently developed nonlinear autoregressive distributed lag cointegration technique. Tourism development is proxied by tourist arrivals, while growth is measured by real...

We employed linear and nonlinear error correction models (ECMs) to predict the log returns of Bitcoin (BTC). The linear ECM is the best model for predicting BTC compared to the neural network and autoregressive models in terms of RMSE, MAE, and MAPE. Using a linear ECM, we are able to understand...

Falling energy intensity (increasing efficiency) is believed to be a result of more efficient production methods that have evolved over time, indicating overall sustainability in the production process. The objective of this study is to investigate the diminishing trend of energy intensity and...