TY - JOUR
T1 - Economic Peaks and Value-at-Risk Analysis
T2 - A Novel Approach Using the Laplace Distribution for House Prices
AU - Das, Jondeep
AU - Hazarika, Partha Jyoti
AU - Alizadeh, Morad
AU - Contreras-Reyes, Javier E.
AU - Mohammad, Hebatallah H.
AU - Yousof, Haitham M.
N1 - Publisher Copyright:
© 2025 by the authors.
PY - 2025/2
Y1 - 2025/2
N2 - In this article, a new extension of the standard Laplace distribution is introduced for house price modeling. Certain important properties of the new distribution are deducted throughout this study. We used the new extension of the Laplace model to conduct a thorough economic risk assessment utilizing several metrics, including the value-at-risk (VaR), the peaks over a random threshold value-at-risk (PORT-VaR), the tail value-at-risk (TVaR), the mean of order-P (MOP), and the peaks over a random threshold based on the mean of order-P (PORT-MOP). These metrics capture different facets of the tail behavior, which is essential for comprehending the extreme median values in the Boston house price data. Notably, PORT-VaR improves the risk evaluations by incorporating randomness into the selection of the thresholds, whereas VaR and TVaR focus on measuring the potential losses at specific confidence levels, with TVaR offering insights into significant tail risks. The MOP method aids in balancing the reliability goals while optimizing the performance in the face of uncertainty.
AB - In this article, a new extension of the standard Laplace distribution is introduced for house price modeling. Certain important properties of the new distribution are deducted throughout this study. We used the new extension of the Laplace model to conduct a thorough economic risk assessment utilizing several metrics, including the value-at-risk (VaR), the peaks over a random threshold value-at-risk (PORT-VaR), the tail value-at-risk (TVaR), the mean of order-P (MOP), and the peaks over a random threshold based on the mean of order-P (PORT-MOP). These metrics capture different facets of the tail behavior, which is essential for comprehending the extreme median values in the Boston house price data. Notably, PORT-VaR improves the risk evaluations by incorporating randomness into the selection of the thresholds, whereas VaR and TVaR focus on measuring the potential losses at specific confidence levels, with TVaR offering insights into significant tail risks. The MOP method aids in balancing the reliability goals while optimizing the performance in the face of uncertainty.
KW - economic risk
KW - extreme house price data
KW - Laplace
KW - mean of order-P
KW - odd log-logistic
KW - peaks over a random threshold
KW - tail behavior
KW - value-at-risk
UR - http://www.scopus.com/inward/record.url?scp=85217982441&partnerID=8YFLogxK
U2 - 10.3390/mca30010004
DO - 10.3390/mca30010004
M3 - Article
AN - SCOPUS:85217982441
SN - 1300-686X
VL - 30
JO - Mathematical and Computational Applications
JF - Mathematical and Computational Applications
IS - 1
M1 - 4
ER -