ParameterisedResponse ZeroIntelligence Traders
Abstract
I introduce PRZI (ParameterisedResponse Zero Intelligence), a new form of zerointelligence trader intended for use in simulation studies of auction markets. Like Gode & Sunder's classic ZeroIntelligence Constrained (ZIC) trader, PRZI generates quoteprices from a random distribution over some specified domain of discretelyvalued allowable quoteprices. Unlike ZIC, which uses a uniform distribution to generate prices, the probability distribution in a PRZI trader is parameterised in such a way that its probability mass function (PMF) is determined by a realvalued control variable s in the range [1.0, +1.0] that determines the strategy for that trader. When s is zero, a PRZI trader behaves identically to the ZIC strategy, with a flat/rectangular PMF; but when s is close to plus or minus one the PRZI trader's PMF becomes asymptotically maximally skewed to one extreme or the other of the pricerange, thereby enabling the PRZI trader to act in the same way as the "Shaver" strategy (SHVR) or the "Giveaway" strategy (GVWY), both of which have recently been demonstrated to be surprisingly dominant over more sophisticated, and supposedly more profitable, traderstrategies that incorporate adaptive mechanisms and machine learning. Depending on the value of s, a PRZI trader will behave either as a ZIC, or as a SHVR, or as a GVWY, or as some hybrid strategy partway between two of these three previouslyreported strategies. The novel smoothlyvarying strategy in PRZI has value in giving traderagents plausibly useful "market impact" responses to imbalances in an auctionmarket's limitorderbook, and also allows for the study of coadaptive dynamics in continuous strategyspaces rather than the discrete spaces that have traditionally been studied in the literature.
 Publication:

arXiv eprints
 Pub Date:
 March 2021
 arXiv:
 arXiv:2103.11341
 Bibcode:
 2021arXiv210311341C
 Keywords:

 Quantitative Finance  Trading and Market Microstructure;
 Computer Science  Computational Engineering;
 Finance;
 and Science;
 Computer Science  Computer Science and Game Theory;
 Computer Science  Multiagent Systems;
 Economics  Theoretical Economics
 EPrint:
 39 pages, 18 figures, 67 references