The Market Fraction Hypothesis under different GP algorithms

In a previous work, inspired by observations made in many agent-based financial models, we formulated and presented the Market Fraction Hypothesis, which basically predicts a short duration for any dominant type of agents, but then a uniform distribution over all types in the long run. We then proposed a two-step approach, a rule-inference step and a rule-clustering step, to testing this hypothesis. We employed genetic programming as the rule inference engine, and applied self-organizing maps to cluster the inferred rules. We then ran tests for 10 international markets and provided a general examination of the plausibility of the hypothesis. However, because of the fact that the tests took place under a GP system, it could be argued that these results are dependent on the nature of the GP algorithm. This chapter thus serves as an extension to our previous work. We test the Market Fraction Hypothesis under two new different GP algorithms, in order to prove that the previous results are rigorous and are not sensitive to the choice of GP. We thus test again the hypothesis under the same 10 empirical datasets that were used in our previous experiments. Our work shows that certain parts of the hypothesis are indeed sensitive on the algorithm. Nevertheless, this sensitivity does not apply to all aspects of our tests. This therefore allows us to conclude that our previously derived results are rigorous and can thus be generalized

CSM-385 Cooperation in Competitions - Constraint Propagation Strategies in Chain-bargaining

Electronic business motivates automatic bargaining: computers may not be as good bargainers as expert human bargainers, but by talking to a large number of traders on the Internet, they stand a better chance of getting good deals. While an end-seller may be interested in getting the highest profit from each negotiation, traders have to balance between making large profits in few deals (thus missing opportunities in the failed negotiations) and making smaller profits in larger number of deals. When a deal is to be constructed through a chain of middlemen, these middlemen have to cooperate (in order to construct the deal) while trying to maximize their own profits. The middlemen can be seen as propagating constraints along the chain, with the aim to maximize its profit while satisfying all the bargainers' constraints (failing that, the chain will break down). In this paper, a simple chainbargaining problem is defined. It is used to study constraint propagation strategies, which are essential components of automatic bargaining

Investment Opportunities Forecasting: Extending the Grammar of a GP-based Tool

In this paper we present a new version of a GP financial forecasting tool, called EDDIE 8. The novelty of this version is that it allows the GP to search in the space of indicators, instead of using pre-specified ones. We compare EDDIE 8 with its predecessor, EDDIE 7, and find that new and improved solutions can be found. Analysis also shows that, on average, EDDIE 8's best tree performs better than the one of EDDIE 7. The above allows us to characterize EDDIE 8 as a valuable forecasting tool

Predicted Abundances of Carbon Compounds in Volcanic Gases on Io

We use chemical equilibrium calculations to model the speciation of carbon in volcanic gases on Io. The calculations cover wide temperature (500-2000 K), pressure (10^-8 to 10^+2 bars), and composition ranges (bulk O/S atomic ratios \~0 to 3), which overlap the nominal conditions at Pele (1760 K, 0.01 bar, O/S ~ 1.5). Bulk C/S atomic ratios ranging from 10^-6 to 10^-1 in volcanic gases are used with a nominal value of 10^-3 based upon upper limits from Voyager for carbon in the Loki plume on Io. Carbon monoxide and CO2 are the two major carbon gases under all conditions studied. Carbonyl sulfide and CS2 are orders of magnitude less abundant. Consideration of different loss processes (photolysis, condensation, kinetic reactions in the plume) indicates that photolysis is probably the major loss process for all gases. Both CO and CO2 should be observable in volcanic plumes and in Io's atmosphere at abundances of several hundred parts per million by volume for a bulk C/S ratio of 10^-3.Comment: 21 pages, 4 figures, 4 tables; accepted by Astrophysical Journa

Proximity Effects in Radiative Transfer

Though the dependence of near-field radiative transfer on the gap between two planar objects is well understood, that between curved objects is still unclear. We show, based on the analysis of the surface polariton mediated radiative transfer between two spheres of equal radii $R$ and minimum gap $d$, that the near--field radiative transfer scales as $R/d$ as $d/R \rightarrow 0$ and as $\ln(R/d)$ for larger values of $d/R$ up to the far--field limit. We propose a modified form of the proximity approximation to predict near--field radiative transfer between curved objects from simulations of radiative transfer between planar surfaces.Comment: 5 journal pages, 4 figure

CES-509 Market Microstructure: Can Dinosaurs Return? A Self-Organizing Map Approach under an Evolutionary Framework

This paper extends a previous model where we examined the markets' microstructure dynamics by using Genetic Programming as a trading rule inference engine, and Self Organizing Maps as a cluster- ing machine for those rules. However, an assumption we made in that model was that clusters, and thus trading strategy types, had to remain the same over time. This assumption could be considered unrealistic, but it was necessary for the purposes of our tests. For this reason, in this paper we extend this model by relaxing this assumption. Hence our framework does not lie on pre-speci?ed types, nor do these types remain the same throughout time. This allows us to investigate the dynamics of market behavior and more speci?cally whether successful strategies from the past can be successfully applied to the future. In the past, we investigated this phenomenon by using a simple ?tness test. Neverthe- less, a drawback of that approach was that because of its simplicity, it could only o?er limited understanding of the complex dynamics of mar- ket behavior. With the extended model we can thus have a more realistic view of the markets and hence draw safer conclusions about their behav- ior. Empirical results show that market behavior is non-stationary, and thus agents' strategies need to continuously co-evolve with the market, in order to remain eff?ective

CSM-401 - Population based Incremental Learning vesus Genetic Algorithms: Iterated Prisoners Dilemma

Axelrod?s originally experiments for evolving IPD player strategies involved the use of a basic GA. In this paper we examine how well a simple GA performs against the more recent Population Based Incremental Learning system under similar conditions. We find that while PBIL performs well, GA in general does slightly better although more experiments should be conducted

CES-511 The Market Fraction Hypothesis under different GP algorithms

In a previous work, inspired by observations made in many agent-based financial models, we formulated and presented the Market Fraction Hypothesis, which basically predicts a short duration for any dominant type of agents, but then a uniform distribution over all types in the long run. We then proposed a two-step approach, a rule-inference step and a rule-clustering step, to testing this hypothesis. We employed genetic programming as the rule in- ference engine, and applied self-organizing maps to cluster the inferred rules. We then ran tests for 10 international markets and provided a general examination of the plausibility of the hypothesis. However, because of the fact that the tests took place under a GP system, it could be argued that these results are dependent on the nature of the GP algorithm. This chapter thus serves as an extension to our previous work. We test the Market Fraction Hypothesis under two new different GP algorithms, in order to prove that the previous results are rigorous and are not sensitive to the choice of GP. We thus test again the hypothesis under the same 10 empirical datasets that were used in our previous experiments. Our work shows that certain parts of the hypothesis are indeed sensitive on the algorithm. Nevertheless, this sensitivity does not apply to all aspects of our tests. This therefore allows us to conclude that our previously derived results are rigorous and can thus be generalized