Uncertainty shocks of Trump election in an interval model of stock market

This paper proposes a new class of nonlinear interval models for interval-valued time series. By matching the interval model with interval observations, we develop a nonlinear minimum-distance estimation method for the proposed models, and establish the asymptotic theory for the proposed estimators. Superior to traditional point-based methods, the proposed interval modelling approach can assess the change in both the trend and volatility simultaneously. Within the proposed interval framework, this paper examines the impact of the 2016 US presidential election (henceforth Trump election) on the US stock market as a case study. Considering the validity of daily high-low range as a proxy of market efficiency, we employ an interval-valued return to jointly measure the fundamental value movement and market efficiency simultaneously. Empirical results suggest a strong evidence that the Trump election has increased the level/trend and lowered the volatility of the S&P 500 index in both ex ante and ex post analysis. Furthermore, a longer half-life period for the impact on fundamental value (62.4 days) than high-low range (15.9 days) has shown that the impact of Trump's victory on fundamental value is more persistent than its impact on market efficiency

Market inefficiencies associated with pricing oil stocks during shocks

The assumption that market efficiency informs the pricing of oil stocks is critical to understanding the co-movement between stock markets and oil markets. To test this assumption in relation to various types of real oil price changes, this article proposes a two-stage analysis method that starts with a quantile regression to identify oil shocks and develop interval-valued factor pricing models. These interval-based methods, relative to traditional point-based methods, can produce more efficient parameter estimations by providing more information. The results show that oil stocks tend to be overpriced following negative oil price shocks, which partially violates the efficient market hypothesis. Yet oil stocks are efficiently priced in response to moderate changes or positive oil price shocks, such that in most cases, the market remains efficient in pricing oil stocks. (C) 2019 Elsevier B.V. All rights reserved

catena-Poly[[tri-n-butyl­tin(IV)]-μ-2-thio­phene­acetato]

The title compound, [Sn(C4H9)3(C6H5O2S)]n, possesses an infinite chain structure. The SnO2C3 centre has a distorted trigonal-bipyramidal geometry (τ = 0.145) with the O atoms in the axial positions. Atoms of the thio­phene group S1 and C4 are disordered over two sites The S atom and one C atom, with attached H atom, of the thiophene ring are disordered over two positions; the site occupancy factors are ca 0.7 and 0.3

Numerical investigation of flow unsteadiness and heat transfer on suction surface of rotating airfoils within a gas turbine cascade

The effects of the periodical turbulence and pressure fluctuation on suction surface heat transfer over airfoils of a row of rotor blades with a certain type have been investigated numerically in this paper. The calculation is performed using model with the numerical results of pressure fluctuation and heat transfer performance over 4 sample points being analyzed and compared with existing experimental data. It shows that the static pressure change has significant impact on heat transfer performance of the fore suction surface, especially in the active region of the shock waves formed from the trailing edge of upstream nuzzles. While, for the rear suction surface, the flow turbulence contributes more to the heat transfer change over the surface, due to the reduced pressure oscillation through this region. Phase shifted phenomenon across the surface can be observed for both pressure and heat transfer parameters, which should be a result of turbulence migration and wake passing across the airfoil