Behind the price: on the role of agent's reflexivity in financial market microstructure

In this chapter we review some recent results on the dynamics of price formation in financial markets and its relations with the efficient market hypothesis. Specifically, we present the limit order book mechanism for markets and we introduce the concepts of market impact and order flow, presenting their recently discovered empirical properties and discussing some possible interpretation in terms of agent's strategies. Our analysis confirms that quantitative analysis of data is crucial to validate qualitative hypothesis on investors' behavior in the regulated environment of order placement and to connect these micro-structural behaviors to the properties of the collective dynamics of the system as a whole, such for instance market efficiency. Finally we discuss the relation between some of the described properties and the theory of reflexivity proposing that in the process of price formation positive and negative feedback loops between the cognitive and manipulative function of agents are present.Comment: 12 pages, 1 figur

Necessary Conditions for Open-Ended Evolution

Evolution on Earth is widely considered to be an effectively endless process. Though this phenomenon of open-ended evolution (OEE) has been a topic of interest in the artificial life community since its beginnings, the field still lacks an empirically validated theory of what exactly is necessary to reproduce the phenomenon in general (including in domains quite unlike Earth). This dissertation (1) enumerates a set of conditions hypothesized to be necessary for OEE in addition to (2) introducing an artificial life world called Chromaria that incorporates each of the hypothesized necessary conditions. It then (3) describes a set of experiments with Chromaria designed to empirically validate the hypothesized necessary conditions. Thus, this dissertation describes the first scientific endeavor to systematically test an OEE framework in an alife world and thereby make progress towards solving an open question not just for evolutionary computation and artificial life, but for science in general

Field application of capacitance-resistance models to identify potential location for infill drilling

textA significant amount of bypassed oil often remains in a mature waterflooded reservoir because of non-uniform sweep. Infill drilling is one of the most attractive options to increasing oil recovery in consequence of its operational simplicity, low risk and promising results. Targeting proper infill location is a complex task and conventionally requires a comprehensive reservoir characterization program such as the streamline simulation (SLS). Achieving a good and reliable model, however, requires massive effort. This inspired the establishment of an alternative method, the Capacitance-Resistance Model (CRM), which is fast, cheap, yet robust. The CRM was applied to an oil field in Southeast Asia, leading to the identification of several key challenges and the emphasis of the input data examination. These challenges are field operations, existence of free gas, and unavailability of flowing bottomhole pressures, in which all of them cause the violation to the CRM assumption and will be addressed appropriately. In addition, this is the first time that the two-phase flow coupled CRM was used with field data. The key additional input required by this model is the reservoir pore volume associated with each producer, which is determined from matching each well’s historical water cut with Koval's equation. Nevertheless, dealing with field data is more complicated as the trend often did not follow the theory because of early water breakthrough in a thief zone or poorly managed waterflood. The results indicated that the CRM is able to give a good fit for both field and well levels. The quality of well by well matching seems to depend on the available number of data points of that well as all wells with low r-square values have very limited available data for matching. The gain results also reveal the good efficiency of the waterflood strategy as there are only 2 injectors having injection loss. It can also be geologically inferred from the gain that the field is anisotropic; there is no obvious preferential flow path in any specific direction. Moreover, field evidence such as the tracer tests, the RFT pressures and the wells' production history support the CRM results. The hypothesis made for the identification of the potential infill locations is that areas with low normalized gain, high oil saturation and high pore volume are attractive for new infill producers. This was successfully validated with the actual infill wells' performance of this field. The combination of maps consisting of the connectivity, the saturation, the thickness, the porosity and the permeability maps, are analyzed simultaneously to see whether the potential areas identified by them correspond with the performance of the infill wells. Generally, the integrated examination of these data is theoretically expected to help locate the bypassed oil and provide an insight to the reservoir characterization and the waterflood performance. However, it was observed with this set of field data that using more properties actually does not guarantee a more accurate result, especially when there are some properties that considerably mislead the interpretation. All in all, the combination of the relevant input parameters should increase the accuracy because they help each other to mitigate the errors caused from a single parameter. In other word, the potential area needs to have both poor reservoir continuity and good rock quality so that it is likely to yield a satisfying infill performance.Petroleum and Geosystems Engineerin

Selective translational repression of HIV-1 RNA by Sam68DeltaC occurs by altering PABP1 binding to unspliced viral RNA

HIV-1 structural proteins are translated from incompletely spliced 9 kb and 4 kb mRNAs, which are transported to the cytoplasm by Crm1. It has been assumed that once in the cytoplasm, translation of incompletely spliced HIV-1 mRNAs occurs in the same manner as host mRNAs. Previous analyses have demonstrated that Sam68 and a mutant thereof, Sam68ΔC, have dramatic effects on HIV gene expression, strongly enhancing and inhibiting viral structural protein synthesis, respectively. While investigating the inhibition of incompletely spliced HIV-1 mRNAs by Sam68ΔC, we determined that the effect was independent of the perinuclear bundling of the viral RNA. Inhibition was dependent upon the nuclear export pathway used, as translation of viral RNA exported via the Tap/CTE export pathway was not blocked by Sam68ΔC. We demonstrate that inhibition of HIV expression by Sam68ΔC is correlated with a loss of PABP1 binding with no attendant change in polyadenosine tail length of the affected RNAs. The capacity of Sam68ΔC to selectively inhibit translation of HIV-1 RNAs exported by Crm1 suggests that it is able to recognize unique characteristics of these viral RNPs, a property that could lead to new therapeutic approaches to controlling HIV-1 replication

Co-generation of game levels and game-playing agents

Open-endedness, primarily studied in the context of artificial life, is the ability of systems to generate potentially unbounded ontologies of increasing novelty and complexity. Engineering generative systems displaying at least some degree of this ability is a goal with clear applications to procedural content generation in games. The Paired Open-Ended Trailblazer (POET) algorithm, heretofore explored only in a biped walking domain, is a coevolutionary system that simultaneously generates environments and agents that can solve them. This paper introduces a POET-Inspired Neuroevolutionary System for KreativitY (PINSKY) in games, which co-generates levels for multiple video games and agents that play them. This system leverages the General Video Game Artificial Intelligence (GVGAI) framework to enable co-generation of levels and agents for the 2D Atari-style games Zelda and Solar Fox. Results demonstrate the ability of PINSKY to generate curricula of game levels, opening up a promising new avenue for research at the intersection of procedural content generation and artificial life. At the same time, results in these challenging game domains highlight the limitations of the current algorithm and opportunities for improvement.Comment: 7 pages, 5 figures, AIIDE 202