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Dynamic Market Behavior and Price Prediction in Cryptocurrency: An Analysis Based on Asymmetric Herding Effects and LSTM
This study employs the cross-sectional absolute deviation model and Carhart pricing model to examine the existence and authenticity of various market...
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Comparing the Mixed Logit Estimates and True Parameters under Informative and Uninformative Heterogeneity: A Simulated Discrete Choice Experiment
In discrete choice experiments (DCEs), differences between respondents’ preferences may be associated with observable or unobservable factors....
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Systemic Financial Risk of Stock Market Based on Multiscale Networks
This paper investigates the connectedness among 36 financial institutions in China from time–frequency perspective. Specifically, using MEMD and...
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Bias Correction in the Least-Squares Monte Carlo Algorithm
This paper addresses the issue of foresight bias in the Longstaff and Schwartz (Rev Financ Stud 14(1):113–147, 2001) algorithm for American option...
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Modelling Mixed-Frequency Time Series with Structural Change
Predictive ability of time series models is easily compromised in the presence of structural breaks, common among financial and economic variables...
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Comparison of the Performance of Structural Break Tests in Stationary and Nonstationary Series: A New Bootstrap Algorithm
Structural breaks are considered as permanent changes in the series mainly because of shocks, policy changes, and global crises. Hence, making...
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Enhancing Stock Market Prediction Using Gradient Boosting Neural Network: A Hybrid Approach
This paper introduces an innovative paradigm in cryptocurrency market analysis and prediction by exploiting the potency of the gradient boosting...
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A Generalized Hyperbolic Distance Function for Benchmarking Performance: Estimation and Inference
This paper describes a new multiplicative, generalized hyperbolic distance function (GHDF) that allows the researcher to measure technical efficiency...
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Operations Research at Netherlands Railways
This paper briefly summarises the role of Operations Research techniques at Netherlands Railways (NS). We discuss the type of problems we are facing,...
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Extracting Stock Predictive Information in Mutual Fund Managers’ Portfolio Decisions Through Machine Learning with Hypergraph
This paper proposes a machine learning framework that incorporates mutual fund managers’ portfolio decisions to predict stock price movements. It...
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Operations Research at Ryanair
This short paper presents how Operations Research methods are employed at Ryanair in various decision problems, the project we have conducted and the...
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Operations Research at M.A.I.O.R. srl
This short paper presents how Operations Research methods are employed at M.A.I.O.R. srl in various decision problems, the project we have conducted...
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Global Dynamics of a Kawasaki Disease Vascular Endothelial Cell Injury Model with Backward Bifurcation and Hopf Bifurcation
Kawasaki disease (KD) is an acute, febrile, systemic vasculitis that mainly affects children under five years of age. In this paper, we propose and...
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Building an Annual Retrospective for French Labor Market (1959–1975) As a Complement of the INSEE’s Time Series (1975–2021)
This paper presents the steps of the building of PAC (Active available population), PEMP (Population in employment) and TCHO (Unemployment rate) time...
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An Alternative Approach for Determining the Time-Varying Decay Parameter of the Nelson-Siegel Model
This paper presents an alternative and straightforward two-step estimation method for the Nelson–Siegel yield curve model. The goal is to generate...
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Operations Research at Norfolk Southern Railway Company
This short paper presents how Operations Research methods are employed at Norfolk Southern Railway Company in several optimization problems, example...
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Operations Research at DSB
This short paper presents how Operations Research methods are employed at DSB Denmark in various decision problems, the project we have conducted and...
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Surface Defects Detection of Cylindrical High-Precision Industrial Parts Based on Deep Learning Algorithms: A Review
High-precision cylindrical parts are critical components across various industries including aerospace, automotive, and manufacturing. Since these...
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One-Shot Learning for MIPs with SOS1 Constraints
Efficient algorithms and solvers are required to provide optimal or near-optimal solutions quickly and enable organizations to react promptly to...
