Kaihang Shi, Qianru Guo and Ann Jeffers
This paper describes a preliminary study to explore the use of Monte Carlo simulation to assess the reliability of structures in fire given uncertainty in the fire, thermal, and…
Abstract
This paper describes a preliminary study to explore the use of Monte Carlo simulation to assess the reliability of structures in fire given uncertainty in the fire, thermal, and structural model parameters. The methodology requires (1) the probabilistic characterization of the uncertain parameters in the system, (2) a stochastic model for the thermo-structural response, and (3) a limit state function that describes the failure of the system. The study focuses on assessing the failure probability of a protected steel beam under natural fire exposure. The system was modeled stochastically using a series of sequentially coupled thermo-structural finite element analyses that were embedded within a Monte Carlo simulation. Although the example considered here is relatively simplistic in that it focuses on member level performance, it effectively demonstrates the application of the proposed reliability method and provides insight into the practicalities of extending the approach to more complex structural systems.
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Dongwei Su and Tianhui Hu
We examine the relationship between macroeconomic news and fund price jumps, using high-frequency 5-min intraday data for Exchange Traded Funds (ETFs) and Listed Open-end Funds…
Abstract
Purpose
We examine the relationship between macroeconomic news and fund price jumps, using high-frequency 5-min intraday data for Exchange Traded Funds (ETFs) and Listed Open-end Funds (LOFs) from 2019 to 2020.
Design/methodology/approach
We utilize the non-parametric jump test known as the LM method to detect fund price jumps. In addition, we perform Logistic regression to analyze the relationship between macroeconomic news and fund price jumps. Moreover, we use multiple linear regression to explore the relationship between fund price jumps and subsequent returns.
Findings
The probability of price jumps increases by 22.56% when macroeconomic news is released. Moreover, the returns associated with news-driven price jumps display a reversal pattern, and there is an asymmetric relationship in subsequent returns following macroeconomic shocks. Specifically, funds tend to exhibit lower returns after news-driven price jumps compared to those that are not influenced by news events.
Research limitations/implications
In today's digital age, investors have unprecedented access to a wealth of information through the Internet and various communication platforms. News and market data can be instantly accessed and disseminated, allowing for swift dissemination of information to investors worldwide. However, despite this enhanced accessibility, investors continue to exhibit overreactions or underreactions to new information.
Practical implications
Macroeconomic news release provide crucial insights into the overall health and performance of the economy. By monitoring and analyzing these indicators, investors can gain valuable information that can guide their investment decisions. Furthermore, by fostering a transparent and reliable information disclosure systems, governments can play a critical role in ensuring the stability and transparency of the funds market.
Originality/value
The paper utilizes 5-min high-frequency data from funds and incorporates a comprehensive macroeconomic news information database. These methodological choices enhance the precision and reliability of the analysis, allowing for a more nuanced understanding of the relationship between macroeconomic news releases and fund price jumps.
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Yancang Li, Chenguang Ban and Rouya Li
Ant colony algorithm is widely used in recent years as a heuristic algorithm. It provides a new way to solve complicated combinatorial optimization problems. Having been…
Abstract
Ant colony algorithm is widely used in recent years as a heuristic algorithm. It provides a new way to solve complicated combinatorial optimization problems. Having been enlightened by the behavior of ant colony's searching for food, positive feedback construction and distributed computing combined with certain heuristics are adopted in the algorithm, which makes it easier to find better solution. This paper introduces a series of ant colony algorithm and its improved algorithm of the basic principle, and discusses the ant colony algorithm application situation. Finally, several problems existing in the research and the development prospect of ACO are reviewed.