Is there any pattern regarding the vulnerability of smart contracts in the food supply chain to a stressed event? A quantile connectedness investigation
Ghosh, B and Paparas, D. (2023) Is there any pattern regarding the vulnerability of smart contracts in the food supply chain to a stressed event? A quantile connectedness investigation. Journal of Risk and Financial Management, 16 (2).
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Dimitrios Paparas Is there any pattern regarding the vulnerability UPLOAD OCR.pdf - Published Version Available under License Creative Commons Attribution. Download (1MB) | Preview |
Abstract
Blockchain can support the food supply chain in several aspects. Particularly, food traceability and trading across pre-existing contracts can make the supply chain fast, error-free, and support in detecting potential fraud. A proper algorithm, keeping in mind specific geographic, demographic, and additional essential parameters, would let the automated market maker (AMM) supply ample liquidity to pre-determined orders. AMMs are usually run by a set of sequential algorithms called a ‘smart contract’ (SM). Appropriate use of SM reduces food waste, contamination, extra or no delivery in due course, and, possibly most significantly, increases traceability. However, SM has definite vulnerabilities, making it less adaptable at times. We are investigating whether they are genuinely vulnerable during stressful periods or not. We considered seven SM platforms, namely, Fabric, Ethereum (ETH), Waves, NEM (XEM), Tezos (XTZ), Algorand (ALGO), and Stellar (XLM), as the proxies for food supply-chain-based smart contracts from 29 August 2021 to 5 October 2022. This period coincides with three stressed events: Delta (Covid II), Omicron (Covid III), and the Russian invasion of Ukraine. We found strong traces of risk transmission, comovement, and interdependence of SM return among the diversified SMs; however, the SMs focused on the food supply chain ended up as net receivers of shocks at both of the extreme tails. All these SMs share a stronger connection in both positive shocks (bullish) and negative shocks (bearish).
Item Type: | Article |
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Keywords: | Traceability, smart contract, automated market maker, connectedness, spillover |
Divisions: | Food, Land and Agribusiness Management |
Depositing User: | Miss Anna Cope |
Date Deposited: | 23 Feb 2023 16:26 |
Last Modified: | 23 Feb 2023 16:26 |
URI: | https://hau.repository.guildhe.ac.uk/id/eprint/17915 |
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