Fraudulent agents in an artificial financial market

Physics – Condensed Matter – Statistical Mechanics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

presented at WEHIA 2003

Scientific paper

The problem of insider trading and other illegal practices in financial markets is an important issue in the field of financial regulatory policies. Market control bodies, such as the US SEC or the Italian CONSOB regularly perform statistical analyses on security prices in order to unveil clues of fraudulent behaviour within the market. Fraudulent behaviour is connected to the more general problem of information asymmetries, which had already been addressed in the field of experimental economics. Recently, interesting conclusions were drawn thanks to a computer-simulated market where agents had different pieces of information about the future dividend cash flow of exchanged securities. Here, by means of an agent-based artificial market: the Genoa Artificial Stock Market (GASM), the more specific problem of fraudulent behaviour in a financial market is studied. A simplified model of fraudulent behaviour is implemented and the action of fraudulent agents on the statistical properties of simulated prices and the agent wealth distribution is investigated.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Fraudulent agents in an artificial financial market does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Fraudulent agents in an artificial financial market, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Fraudulent agents in an artificial financial market will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-211821

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.