Full electronic automation in stock exchanges has recently become popular, generating high-frequency intraday data and motivating the development of near real-time price forecasting methods. Machine learning algorithms are widely applied to mid-price stock predictions. Processing raw data as...

We model and forecast commodity spot and futures prices using fractionally cointegrated vector autoregressive (FCVAR) models generalizing the well-known (non-fractional) CVAR model to accommodate fractional integration. In our empirical analysis to daily data on 17 commodity markets, the...

In this paper, we construct mimicking crypto portfolios with 12 clean cryptocurrencies to replace the dirty cryptocurrencies, Bitcoin and Ethereum, based on the daily data for the period from 10/01/2019 to 12/31/2021. Furthermore, relying on the bivariate dynamic conditional correlation (DCC-)...

In this paper, we apply the recently developed fractionally cointegrated vector autoregressive (FCVAR) model to analyze price discovery in the spot and futures markets for five non-ferrous metals (aluminum, copper, lead, nickel, and zinc). The FCVAR model allows for long memory (fractional...

We examine theoretically and experimentally how combining between-team and within-team incentives affects behavior in team tournaments. Theory predicts that free-riding is likely to occur when there are only between-team incentives, and offering within-team incentives may solve this problem....

The modern business environment is a dynamic one, and organizations must be adaptive. In addition, organizations rely increasingly upon groups. This study provides an examination of the effectiveness of controls in dynamic, cooperative environments. As control, we study a mechanism that provides...