Article
Physics, Fluids & Plasmas
C. Tyler Diggans, Erik M. Bollt, Daniel ben-Avraham
Summary: This study presents a link-by-link rule-based method for constructing a collection of spanning trees with desired properties, offering a solution for optimization problems in complex networks.
Article
Management
Martine Labbe, Mercedes Landete, Marina Leal
Summary: This study introduces the problem of jointly determining a set of features and a dendrogram according to the single linkage method, proposing different formulations and studying different bounds on the objective function. The effectiveness of the different models is discussed through extensive computational study, comparing the model with valid inequalities to the decomposition algorithm. The computational results also demonstrate that integrating feature selection into the optimization model allows for a satisfactory percentage of information to be preserved.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Operations Research & Management Science
Pedro Correia, Luis Paquete, Jose Rui Figueira
Summary: This article introduces a new algorithm based on the connectedness property for computing the set of supported non-dominated points and corresponding efficient solutions for the multi-objective spanning tree problem. The algorithm utilizes decomposition of the weight set and adjacency relation in the decision space to determine efficient spanning trees and indifference regions. An in-depth computational analysis is presented for different types of networks with three objectives.
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
(2021)
Article
Physics, Multidisciplinary
Tristan Millington, Mahesan Niranjan
Summary: This paper examines the inference of MSTs from financial returns of the US, UK, and Germany using Pearson, Spearman, and Kendall's tau rank correlation methods. MSTs constructed with rank methods are more stable and maintain more edges over the dataset compared to those constructed with Pearson correlation. The agreement between Pearson and rank MSTs varies depending on market conditions, with rank MSTs generally showing strong agreement at all times.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Computer Science, Interdisciplinary Applications
Pei Yao, Longkun Guo
Summary: This paper proposes two algorithms to solve the constrained minimum spanning tree (CMST) problem with length and weight constraints. The first algorithm provides an exact solution for the case when the edge length is restricted to 0 and 1, by combining local search and bicameral edge replacement. The second algorithm extends the solution to the case when the edge length is restricted to 0, 1, and 2, by iteratively improving a feasible solution towards an optimum one. Numerical experiments validate the practical performance of the proposed algorithms compared to previous algorithms as baselines.
JOURNAL OF COMBINATORIAL OPTIMIZATION
(2022)
Article
Computer Science, Software Engineering
David Eppstein
Summary: This study proves that in an undirected graph with n vertices and m edges, where each vertex is labeled with a linear function of a parameter lambda, the number of different minimum spanning trees obtained as the parameter varies can be at least Omega (m log n).
Article
Computer Science, Artificial Intelligence
Riccardo La Grassa, Ignazio Gallo, Nicola Landro
Summary: We propose a novel model OCmst for novelty detection problem, which utilizes a CNN as deep feature extractor and a graph-based model based on MST. Experimental results on two publicly available datasets demonstrate the effectiveness of our approach, achieving state-of-the-art results on the CIFAR10 dataset.
PATTERN RECOGNITION LETTERS
(2022)
Article
Operations Research & Management Science
Martin Naegele, Rico Zenklusen
Summary: Short spanning trees subject to additional constraints are important in approximation algorithms. A new dynamic programming approach is proposed to handle various constraint types, including chain constraints and laminar family cut constraints. The approach can also handle parity constraints and has implications in the context of TSP.
MATHEMATICS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Software Engineering
Swati Gupta, Ali Khodabakhsh, Hassan Mortagy, Evdokia Nikolova
Summary: This paper presents the first provable approximation guarantees for the network reconfiguration problem, providing various lower bounds and approximation factors for different settings. Significant advancements have been made on both general graphs and grids with a new method for spectral graph sparsification.
MATHEMATICAL PROGRAMMING
(2022)
Article
Computer Science, Hardware & Architecture
John Augustine, Seth Gilbert, Fabian Kuhn, Peter Robinson, Suman Sourav
Summary: This article studies the cost of distributed MST construction considering the latency, capacity, and weight of each edge. Tight bounds are provided on the time and messages required for MST construction based on the relationship between edge latencies and weights. The total weight of the MST is found to be the bottleneck parameter in determining the running time, rather than the total number of nodes. The article also presents algorithms with nearly matching upper and lower bounds for different scenarios.
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2022)
Article
Mathematics
Ghurumuruhan Ganesan
Summary: The study focuses on the weighted length of the minimum spanning tree containing all nodes distributed in a unit square, as well as the length of the minimum weighted spanning tree for nodes distributed throughout the unit square with location-dependent edge weights. Variance estimates are obtained using approximation methods, and it is proven that under certain conditions of good connectivity among cities, these quantities converge to zero in probability.
COMMUNICATIONS IN MATHEMATICS AND STATISTICS
(2022)
Article
Statistics & Probability
Ghurumuruhan Ganesan
Summary: In this study, we investigated the problem of minimum spanning trees in random geometric graphs (RGG), assigning weights to each edge and providing upper and lower bound deviation estimates for MSTn. We also obtained estimates for L2-convergence of appropriately scaled and centred MSTn.
Article
Computer Science, Theory & Methods
Baolei Cheng, Dajin Wang, Jianxi Fan
Summary: This survey provides a comprehensive collection of important works on ISTs and offers a historical perspective on the development of ISTs, serving as a useful reference for future research in this field.
ACM COMPUTING SURVEYS
(2023)
Article
Computer Science, Hardware & Architecture
Radislav Vaisman
Summary: The study investigates the performance of the Cross-Entropy algorithm, which relies on rigorous developments in information theory and stochastic simulation. Findings suggest that the Cross-Entropy method is not sensitive to different graph models and can obtain optimal or near-optimal solutions with reasonable computational effort.
Article
Computer Science, Software Engineering
Daniel Alcaide, Jan Aerts
Summary: STAD is a parameter-free dimensionality reduction method that projects high-dimensional data into a graph, preserving approximate distances in the original high-dimensional space. This method can be used to explore and analyze data, highlighting potential traits in the data.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2021)
Article
Business, Finance
Yi Li, Brian Lucey, Andrew Urquhart
Summary: Bitcoin remains the most popular cryptocurrency and has attracted significant research attention, especially in the hedging and safe-haven literature. Meme coins offer hedging benefits, while a wider range of altcoins can act as safe-havens against bitcoin, including Defi, smart contracts, metaverse, and privacy cryptocurrencies. The effectiveness of these coins as hedges and safe-havens depends on whether the market is in a bubble or non-bubble period.
FINANCE RESEARCH LETTERS
(2023)
Article
Business, Finance
Suwan(Cheng) Long, Brian Lucey, Ying Xie, Larisa Yarovaya
Summary: This study investigates the role of social media platform Reddit in the events surrounding the GameStop share rally, and contributes to the growing body of literature on meme stocks and the impact of discussions on investment forums on intraday stock price movements by analyzing the influence of discussions on the r/WallStreetBets subreddit on the price dynamics of GameStop.
Article
Business, Finance
Michael Dowling, Brian Lucey
Summary: Based on ratings from finance journal reviewers, the AI chatbot ChatGPT demonstrates significant usefulness in finance research, with potential for application in other domains. It excels in idea generation and data identification, while facing challenges in literature synthesis and developing appropriate testing frameworks. Moreover, the quality of output is influenced by the extent of private data and researcher domain expertise input. Ethical implications and other potential impacts are also considered.
FINANCE RESEARCH LETTERS
(2023)
Article
Operations Research & Management Science
Muhammad Abubakr Naeem, Sitara Karim, Larisa Yarovaya, Brian M. M. Lucey
Summary: This study measures the tail connectedness between sustainable, religious, and conventional investments and finds that sustainable assets offer stronger diversification benefits during crisis periods, while religious and conventional investments are more exposed to tail risk. The findings have implications for policymakers, regulatory bodies, investors, financial market participants, and portfolio managers in terms of diversifying risk using sustainable/green investments.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Economics
Boru Ren, Brian Lucey
Summary: In this paper, the authors investigate the herd behaviour of the Chinese renewable energy sector, finding evidence of changing herding behaviour over time. The study suggests that herding asymmetry is more pronounced during up markets and among smaller firms. Additionally, large price movements in the overall stock market contribute to the formation of herding behaviour in this sector when within-industry herding weakens.
Article
Environmental Studies
Imen Mbarki, Muhammad Arif Khan, Sitara Karim, Andrea Paltrinieri, Brian M. Lucey
Summary: This study presents a bibliometric examination of 437 journal articles on commodity connectedness, using a blend of qualitative and quantitative approaches. Four primary research streams have been identified, including commodity interconnectivity, the relationship between traditional commodities, renewable energy, and cryptocurrencies, the relationship between oil and stock markets, and studies utilizing copula methods to examine the interconnectivity between oil and financial markets. The study proposes 15 future research questions for further investigation in the domain of commodity connectedness.
Article
Business, Finance
Suwan (Cheng) Long, Brian Lucey, Dayong Zhang, Zhiwei Zhang
Summary: This paper adopts an interactive network approach to investigate the factors driving the carbon footprint of Bitcoin and finds that the dynamics of Bitcoin prices play a crucial role in driving its associated carbon emissions, especially during the pandemic period.
FINANCE RESEARCH LETTERS
(2023)
Article
Business, Finance
Brian Lucey, Onur Kemal Tosun
Summary: This study examines the economic turmoil in the UK caused by a mini budget announcement by the Chancellor between 06September and 19October2022. Despite the anticipation of growth, UK firms experienced a loss of about 0.30% in daily excess returns and 0.87 million pounds in market value. The Moron Risk Premium in the UK increased by 0.48%. Analysis using the Google Search Volume Index supports the detrimental impact on companies. The durables, construction, manufacturing, and wholesale & retail sectors were less affected by this economic turbulence. The study concludes that low-tax economic policies may not always inspire confidence in future growth, particularly during periods of high inflation and political instability.
FINANCE RESEARCH LETTERS
(2023)
Article
Business, Finance
Tong Fu, Feng He, Brian Lucey
Summary: This paper examines the impact of court justice on the allocative efficiency of electricity. It suggests that courts pursuing justice will ensure the efficiency of electricity allocation. Using micro-evidence from China, the study measures the elasticity of electricity reliability on value added per employee and confirms that court justice positively moderates this elasticity, while corruption as a proxy for injustice has a negative moderating effect. Therefore, the quality of courts plays a crucial role in determining the allocative efficiency of electricity, contributing to the understanding of economic institutions for sustainable development.
JOURNAL OF INTERNATIONAL FINANCIAL MARKETS INSTITUTIONS & MONEY
(2023)
Article
Business, Finance
Xu Han, Elaine Laing, Brian M. Lucey, Samuel Vigne
Summary: This paper presents a large-scale multi-country longitudinal study that explores the exposure of firms to commodity price risk in 23 OECD countries. The results indicate that all industries are significantly affected by commodity price fluctuations, ranging from 8 to 10%, except for the energy sector where 38% of firms are significantly exposed. Regarding the determinants of commodity price exposure, the study finds a negative association with firm size and positive relationships with the fraction of R&D expenses, leverage, country GDP, and sophistication of financial derivatives markets.
JOURNAL OF COMMODITY MARKETS
(2023)
Article
Business, Finance
Yu Wei, Yizhi Wang, Brian M. Lucey, Samuel A. Vigne
Summary: This study compares the impact and predictive ability of cryptocurrency uncertainty on volatility forecasts of COMEX gold and silver futures markets using the GARCH-MIDAS model and other commonly used uncertainty measures. The results show that cryptocurrency uncertainty significantly affects the volatilities of precious metal futures markets, and the out-of-sample evidence confirms the strong predictive power of cryptocurrency uncertainty on volatility forecasting of the precious metal market.
JOURNAL OF COMMODITY MARKETS
(2023)
Article
Economics
Brian Lucey, Boru Ren
Summary: In this paper, the dynamic transmission of tail risk among sustainability-related financial indices, equities, and energy assets is analyzed using a new CAViaR-TVP-VAR connectedness measure. The study finds that the overall risk connectedness is moderate and the short-term impact of COVID-19 on risk transmission is mild. It is also observed that ESG and green equities are persistent net risk transmitters, while green bond, carbon asset, and energy commodities are tail risk takers. The findings provide insightful implications for policymakers and investors in risk diversification.
Article
Business, Finance
Molla Ramizur Rahman, Arun Kumar Misra, Brian M. Lucey, Sabyasachi Mohapatra, Satish Kumar
Summary: This study examines the stock market integration for Asia-Pacific countries using RADR and BIN indices. The study finds that the RADR index is higher during the GFC, indicating higher integration. Network parameters are higher during the GFC and are used to form a network index - BIN. The study concludes that BIN is a better measure than RADR, as it is independent of differential index return.
JOURNAL OF INTERNATIONAL FINANCIAL MARKETS INSTITUTIONS & MONEY
(2023)
Article
Business, Finance
Sitara Karim, Brian M. Lucey, Muhammad A. Naeem, Larisa Yarovaya
Summary: The current study examines the extreme risk dependence between green bonds and financial markets using the dual approaches of time-varying optimal copula and extreme risk spillover analysis. Significant symmetric (asymmetric) tail-dependent copulas are found in the upper (lower) tails, indicating independent regimes. Green bonds provide diversification, safe-haven, and hedging opportunities during stable and distressing times for financial markets. The analysis reveals that COVID-19 has altered the spillovers between green bonds and financial markets, except for Bitcoin.
EUROPEAN FINANCIAL MANAGEMENT
(2023)
Article
Business, Finance
Dayong Zhang, Yalin Wu, Qiang Ji, Kun Guo, Brian Lucey
Summary: The objective of this paper is to investigate the impact of climate risk on the stability of regional commercial banks in China. The study finds that higher levels of climate risk are associated with higher levels of non-performing loans, and banks react to transitional policies by modifying their portfolios.
JOURNAL OF INTERNATIONAL MONEY AND FINANCE
(2024)
Article
Physics, Multidisciplinary
Xiaoyu Shi, Jian Zhang, Xia Jiang, Juan Chen, Wei Hao, Bo Wang
Summary: This study presents a novel framework using offline reinforcement learning to improve energy consumption in road transportation. By leveraging real-world human driving trajectories, the proposed method achieves significant improvements in energy consumption. The offline learning approach demonstrates generalizability across different scenarios.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Junhyuk Woo, Soon Ho Kim, Hyeongmo Kim, Kyungreem Han
Summary: Reservoir computing (RC) is a new machine-learning framework that uses an abstract neural network model to process information from complex dynamical systems. This study investigates the neuronal and network dynamics of liquid state machines (LSMs) using numerical simulations and classification tasks. The findings suggest that the computational performance of LSMs is closely related to the dynamic range, with a larger dynamic range resulting in higher performance.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Yuwei Yang, Zhuoxuan Li, Jun Chen, Zhiyuan Liu, Jinde Cao
Summary: This paper proposes an extreme learning machine (ELM) algorithm based on residual correction and Tent chaos sequence (TRELM-DROP) for accurate prediction of traffic flow. The algorithm reduces the impact of randomness in traffic flow through the Tent chaos strategy and residual correction method, and avoids weight optimization using the iterative method. A DROP strategy is introduced to improve the algorithm's ability to predict traffic flow under varying conditions.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Chengwei Dong, Min Yang, Lian Jia, Zirun Li
Summary: This work presents a novel three-dimensional system with multiple types of coexisting attractors, and investigates its dynamics using various methods. The mechanism of chaos emergence is explored, and the periodic orbits in the system are studied using the variational method. A symbolic coding method is successfully established to classify the short cycles. The flexibility and validity of the system are demonstrated through analogous circuit implementation. Various chaos-based applications are also presented to show the system's feasibility.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Viorel Badescu
Summary: This article discusses the maximum work extraction from confined particles energy, considering both reversible and irreversible processes. The results vary for different types of particles and conditions. The concept of exergy cannot be defined for particles that undergo spontaneous creation and annihilation. It is also noted that the Carnot efficiency is not applicable to the conversion of confined thermal radiation into work.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
P. M. Centres, D. J. Perez-Morelo, R. Guzman, L. Reinaudi, M. C. Gimenez
Summary: In this study, a phenomenological investigation of epidemic spread was conducted using a model of agent diffusion over a square region based on the SIR model. Two possible contagion mechanisms were considered, and it was observed that the number of secondary infections produced by an individual during its infectious period depended on various factors.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zuan Jin, Minghui Ma, Shidong Liang, Hongguang Yao
Summary: This study proposes a differential variable speed limit (DVSL) control strategy considering lane assignment, which sets dynamic speed limits for each lane to attract vehicle lane-changing behaviors before the bottleneck and reduce the impact of traffic capacity drop. Experimental results show that the proposed DVSL control strategy can alleviate traffic congestion and improve efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Matthew Dicks, Andrew Paskaramoorthy, Tim Gebbie
Summary: In this study, we investigate the learning dynamics of a single reinforcement learning optimal execution trading agent when it interacts with an event-driven agent-based financial market model. The results show that the agents with smaller state spaces converge faster and are able to intuitively learn to trade using spread and volume states. The introduction of the learning agent has a robust impact on the moments of the model, except for the Hurst exponent, which decreases, and it can increase the micro-price volatility as trading volumes increase.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zhouzhou Yao, Xianyu Wu, Yang Yang, Ning Li
Summary: This paper developed a cooperative lane-changing decision system based on digital technology and indirect reciprocity. By introducing image scoring and a Q-learning based reinforcement learning algorithm, drivers can continuously evaluate gains and adjust their strategies. The study shows that this decision system can improve driver cooperation and traffic efficiency, achieving over 50% cooperation probability under any connected vehicles penetration and traffic density, and reaching 100% cooperation probability under high penetration and medium to high traffic density.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Josephine Nanyondo, Henry Kasumba
Summary: This paper presents a multi-class Aw-Rascle (AR) model with area occupancy expressed in terms of vehicle class proportions. The qualitative properties of the proposed equilibrium velocity and the stability conditions of the model are established. The numerical results show the effect of proportional densities on the flow of vehicle classes, indicating the realism of the proposed model.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Oliver Smirnov
Summary: This study proposes a new method for simultaneously estimating the parameters of the 2D Ising model. The method solves a constrained optimization problem, where the objective function is a pseudo-log-likelihood and the constraint is the Hamiltonian of the external field. Monte Carlo simulations were conducted using models of different shapes and sizes to evaluate the performance of the method with and without the Hamiltonian constraint. The results demonstrate that the proposed estimation method yields lower variance across all model shapes and sizes compared to a simple pseudo-maximum likelihood.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Przemyslaw Chelminiak
Summary: The study investigates the first-passage properties of a non-linear diffusion equation with diffusivity dependent on the concentration/probability density through a power-law relationship. The survival probability and first-passage time distribution are determined based on the power-law exponent, and both exact and approximate expressions are derived, along with their asymptotic representations. The results pertain to diffusing particles that are either freely or harmonically trapped. The mean first-passage time is finite for the harmonically trapped particle, while it is divergent for the freely diffusing particle.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Hidemaro Suwa
Summary: The choice of transition kernel is crucial for the performance of the Markov chain Monte Carlo method. A one-parameter rejection control transition kernel is proposed, and it is shown that the rejection process plays a significant role in determining the sampling efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Xudong Wang, Yao Chen
Summary: This article investigates the joint influence of expanding medium and constant force on particle diffusion. By starting from the Langevin picture and introducing the effect of external force in two different ways, two models with different force terms are obtained. Detailed analysis and derivation yield the Fokker-Planck equations and moments for the two models. The sustained force behaves as a decoupled force, while the intermittent force changes the diffusion behavior with specific effects depending on the expanding rate of the medium.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
