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Keywords = IANM

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19 pages, 3494 KiB  
Article
China’s Stock Market under COVID-19: From the Perspective of Behavioral Finance
by Kaizheng Li and Xiaowen Jiang
Int. J. Financial Stud. 2024, 12(3), 70; https://doi.org/10.3390/ijfs12030070 - 19 Jul 2024
Cited by 1 | Viewed by 2283
Abstract
As a colossal developing economy, irrational, and inefficient trades broadly exist in China’s stock market and are intensified by the once-in-a-century COVID-19 pandemic. This atypical but prominent event enhances systemic risk and requires a more effective analysis tool that adapts to the investors’ [...] Read more.
As a colossal developing economy, irrational, and inefficient trades broadly exist in China’s stock market and are intensified by the once-in-a-century COVID-19 pandemic. This atypical but prominent event enhances systemic risk and requires a more effective analysis tool that adapts to the investors’ sentiment and behavior. Based on the behavioral asset pricing model, this paper verifies the existence of noise traders in China’s stock market, measures the intensity of the noise with the NTR indicator, and examines the market noise with IANM. Furthermore, the mechanism of how COVID-19 influences the market noise through investors’ behaviors is analyzed with the event study method. The findings show that, based on 92 Chinese companies, the market noise significantly exists, and the noise is associated with psychological biases including over-confidence, herding effects and regret aversion. These biases are affected to varying degrees by COVID-19-related events, leading to notable implications for market stability and investor behavior during crises. Our study provides critical insights for policymakers and investors on managing market risks and understanding behavioral impacts during unprecedented events. Full article
(This article belongs to the Special Issue Risks and Uncertainties in Financial Markets)
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14 pages, 843 KiB  
Article
Optimization of a Micromixer with Automatic Differentiation
by Julius Jeßberger, Jan E. Marquardt, Luca Heim, Jakob Mangold, Fedor Bukreev and Mathias J. Krause
Fluids 2022, 7(5), 144; https://doi.org/10.3390/fluids7050144 - 22 Apr 2022
Cited by 8 | Viewed by 2702
Abstract
As micromixers offer the cheap and simple mixing of fluids and suspensions, they have become a key device in microfluidics. Their mixing performance can be significantly increased by periodically varying the inlet pressure, which leads to a non-static flow and improved mixing process. [...] Read more.
As micromixers offer the cheap and simple mixing of fluids and suspensions, they have become a key device in microfluidics. Their mixing performance can be significantly increased by periodically varying the inlet pressure, which leads to a non-static flow and improved mixing process. In this work, a micromixer with a T-junction and a meandering channel is considered. A periodic pulse function for the inlet pressure is numerically optimized with regard to frequency, amplitude and shape. Thereunto, fluid flow and adsorptive concentration are simulated three-dimensionally with a lattice Boltzmann method (LBM) in OpenLB. Its implementation is then combined with forward automatic differentiation (AD), which allows for the generic application of fast gradient-based optimization schemes. The mixing quality is shown to be increased by 21.4% in comparison to the static, passive regime. Methodically, the results confirm the suitability of the combination of LBM and AD to solve process-scale optimization problems and the improved accuracy of AD over difference quotient approaches in this context. Full article
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