Computational Model Library

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This paper investigates the impact of agents' trading decisions on market liquidity and transactional efficiency in markets for illiquid (hard-to-trade) assets. Drawing on a unique order book dataset from the fine wine exchange Liv-ex, we offer novel insights into liquidity dynamics in illiquid markets. Using an agent-based framework, we assess the adequacy of conventional liquidity measures in capturing market liquidity and transactional efficiency. Our main findings reveal that conventional liquidity measures, such as the number of bids, asks, new bids and new asks, may not accurately represent overall transactional efficiency. Instead, volume (measured by the number of trades) and relative spread measures may be more appropriate indicators of liquidity within the context of illiquid markets. Furthermore, our simulations demonstrate that a greater number of traders participating in the market correlates with an increased efficiency in trade execution, while wider trader-set margins may decrease the transactional efficiency. Interestingly, the trading period of the agents appears to have a significant impact on trade execution. This suggests that granting market participants additional time for trading (for example, through the support of automated trading systems) can enhance transactional efficiency within illiquid markets. These insights offer practical implications for market participants and policymakers aiming to optimise market functioning and liquidity.

AGENTS model is an agent-based computational framework designed to explore the socio-ecological and economic dynamics of agricultural production in the Byzantine Negev Highlands, with a focus on viticulture. It integrates historical, environmental, and social factors to simulate settlement sustainability, crop yields, and the impacts of varying climate conditions. The model is built in NetLogo and incorporates GIS-based topographical and hydrological data. Key features include the ability to assess climate impacts on crop profitability and settlement strategies, evaluate economic outputs of ancient vineyards, and simulate agent decision-making processes under diverse scenarios.

The AGENTS model is highly flexible, enabling users to simulate agricultural regimes with any two crops: one cash crop (a crop grown for profit, e.g., grapevines) and one staple crop (a crop grown for subsistence, e.g., wheat). While the default setup models viticulture and wheat cultivation in the Byzantine Negev Highlands, users can adapt the model to different environmental and socio-ecological contexts worldwide—both past and present.

Users can load external files to customize precipitation, evaporation, topography, and labor costs (measured as man-days per 0.1ha, converted to kg of wheat per model patch size area), and can also edit key parameters related to yield calculations. This includes modifying crop-specific yield formulas, soil and runoff indices, and any factors influencing crop performance. The model inherently simulates cash crops grown in floodplain regions and staple crops cultivated along riverbanks, providing a powerful tool to investigate societal resilience and responses to climate stressors across diverse environments.

AmphorABM

Stefani Crabtree | Published Tuesday, January 05, 2021

This model examines the economic interaction between Gaulish wheat farmers and Etruscan and Greek wine farming in 7th century B.C. France.

This model simulates the behaviour of the agents in 3 wine markets parallel trading systems: Liv-ex, Auctions and additionally OTC market (finally not used). Behavioural aspects (impatience) is additionally modeled. This is an extention of parallel trading systems model with technical trading (momentum and contrarian) and noise trading.

Parallel trading systems

Marcin Czupryna | Published Friday, June 26, 2020

The model simulates agents behaviour in wine market parallel trading systems: auctions, OTC and Liv-ex. Models are written in JAVA and use MASON framework. To run a simulation download source files with additional src folder with sobol.csv file. In WineSimulation.java set RESULTS_FOLDER parameter. Uses following external libraries mason19..jar, opencsv.jar, commons-lang3-3.5.jar and commons-math3-3.6.1.jar.

COOPER - Flood impacts over Cooperative Winemaking Systems

David Nortes Martinez David Nortes-Martinez | Published Thursday, February 08, 2018 | Last modified Friday, March 22, 2019

The model simulates flood damages and its propagation through a cooperative, productive, farming system, characterized as a star-type network, where all elements in the system are connected one to each other through a central element.

Model explains both the final state and the dynamics of the development process of the wine sector in the Małopolska region in Poland. Model admits heterogeneous agents (regular farms,large and small vineyards).

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