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Displaying 10 of 75 results for "Marcel Volosin" clear search

Marc Ferozi Member since: Wed, Jul 03, 2013 at 04:51 AM

Marc Legrand Member since: Tue, Jul 20, 2021 at 09:02 AM

Manuel Chica Member since: Tue, Nov 05, 2013 at 08:46 AM

PhD Computer Science

Marcos Aurelio Santos Da Silva Member since: Mon, Feb 06, 2017 at 10:32 PM

MSc. Applied Computing

Marc Parenthoën Member since: Tue, Oct 09, 2018 at 07:37 AM

Anne Marie Treguier Member since: Sat, Jun 15, 2013 at 03:38 PM

PhD

Ocean modelling

William Hamilton Member since: Tue, Mar 17, 2015 at 01:15 AM Full Member

Bachelor of Arts, Psychology, University of California, Merced, Associate of Arts, Social Science, Reedley College

Chuck Collver Member since: Sat, Feb 24, 2018 at 11:27 AM

Continuous double auction markets; call auction; alternative market structures

Marco Braasch Member since: Fri, Mar 02, 2018 at 04:49 PM

Forest engineer (FH), University of applied forestry sciences Rottenburg a.N. Germany, M.Sc Environmental science IPICYT, San Luis Potosi, Mexico

Talal Alsulaiman Member since: Fri, Feb 27, 2015 at 04:10 AM

Bachelor of Science in Systems Engineering, Master of Science in Industrial Engineering, Master of Science in Financial Engineering

In this paper, we explore the dynamic of stock prices over time by developing an agent-based market. The developed artificial market comprises of heterogeneous agents occupied with various behaviors and trading strategies. To be specific, the agents in the market may expose to overconfidence, conservatism or loss aversion biases. Additionally, they may employ fundamental, technical, adaptive (neural network) strategies or simply being arbitrary agents (zero intelligence agents). The market has property of direct interaction. The environment takes the form of network structure, namely, it takes the manifestation of scale-free network. The information will flow between the agents through the linkages that connect them. Furthermore, the tax imposed by the regulator is investigated. The model is subjected to goodness of fit to the empirical observations of the S\&P500. The fitting of the model is refined by calibrating the model parameters through heuristic approach, particularly, scatter search. Conclusively, the parameters are validated against normality, absence of correlations, volatility cluster and leverage effect using statistical tests.

Displaying 10 of 75 results for "Marcel Volosin" clear search

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