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@arXiv_qfinGN_bot@mastoxiv.page
2025-10-10 08:19:49

Smart Contract-Enabled Procurement under Bounded Demand Variability: A Truncated Normal Approach
Jinho Cha, Youngchul Kim, Junyeol Ryu, Sangjun Park, Jeongho Kang, Hyeyoung Hwang
arxiv.org/abs/2510.07801

Smart Contract-Enabled Procurement under Bounded Demand Variability: A Truncated Normal Approach
This study develops a strategic procurement framework integrating blockchain-based smart contracts with bounded demand variability modeled through a truncated normal distribution. While existing research emphasizes the technical feasibility of smart contracts, the operational and economic implications of adoption under moderate uncertainty remain underexplored. We propose a multi-supplier model in which a centralized retailer jointly determines the optimal smart contract adoption intensity and …

@arXiv_qfinGN_bot@mastoxiv.page
2025-10-09 08:42:21

Smart Contract Adoption in Derivative Markets under Bounded Risk: An Optimization Approach
Jinho Cha, Long Pham, Thi Le Hoa Vo, Jaeyoung Cho, Jaejin Lee
arxiv.org/abs/2510.07006

Smart Contract Adoption in Derivative Markets under Bounded Risk: An Optimization Approach
This study develops and analyzes an optimization model of smart contract adoption under bounded risk, linking structural theory with simulation and real-world validation. We examine how adoption intensity alpha is structurally pinned at a boundary solution, invariant to variance and heterogeneity, while profitability and service outcomes are variance-fragile, eroding under volatility and heavy-tailed demand. A sharp threshold in the fixed cost parameter A3 triggers discontinuous adoption collap…

@arXiv_qfinPR_bot@mastoxiv.page
2025-10-01 08:43:07

Deep learning CAT bond valuation
Julian Sester, Huansang Xu
arxiv.org/abs/2509.25899 arxiv.org/pdf/2509.25899

Deep learning CAT bond valuation
In this paper, we propose an alternative valuation approach for CAT bonds where a pricing formula is learned by deep neural networks. Once trained, these networks can be used to price CAT bonds as a function of inputs that reflect both the current market conditions and the specific features of the contract. This approach offers two main advantages. First, due to the expressive power of neural networks, the trained model enables fast and accurate evaluation of CAT bond prices. Second, because of…

@arXiv_qfinGN_bot@mastoxiv.page
2025-10-08 11:34:47

Crosslisted article(s) found for q-fin.GN. arxiv.org/list/q-fin.GN/new
[1/1]:
- Mechanism design and equilibrium analysis of smart contract mediated resource allocation
Jinho Cha, Justin Yoo, Eunchan Daniel Cha, Emily Yoo, Caedon Geoffrey, Hyoshin Song

@chris@mstdn.chrisalemany.ca
2025-11-24 21:14:21

There needs to be contract language drawn up for government using consultants that amounts to
"if the final report is found to contain AI-generated fake or mis-quoted information, or it is otherwise suspect that part or all of the report has been generated using an LLM, the entire report will be considered inadmissible and a full refund of all costs will be expected.”
That's how you protect the integrity of public decision making.
#CanPoli #NLPoli #AI #LLM
cbc.ca/news/canada/newfoundlan