Bubbles in hybrid markets: How expectations about algorithmic trading affect human trading

Farjam, Mike; Kirchkamp, Oliver

doi:10.1016/j.jebo.2017.11.011

Cited by 32 publications

(21 citation statements)

References 51 publications

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“…If we interpret strategic interaction as a lottery where the outcome depends on a second player, the results of this paper suggest that the nature of the second player may be an important feature in itself, irrespective of strategic considerations. On modern stock markets for example human traders are partially replaced by algorithmic traders and it remains unclear how, irrespective of any actual difference in trading, the new type of agent affects human traders and the market as a whole (as a first experiment on this see Farjam and Kirchkamp (2018)).…”

Section: Discussionmentioning

confidence: 99%

On whom would I want to depend; humans or computers?

Farjam

2019

Journal of Economic Psychology

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We study in a laboratory experiment whether humans prefer to depend on decisions of others (Human-Driven Uncertainty) or states generated by a computer (Computerized Uncertainty). The experimental design introduced in this paper is unique in that it introduces Human-Driven Uncertainty such that it does not derive from a strategic context. In our experiment, Human-Driven Uncertainty derives from decisions, which were taken in a morally neutral context and in ignorance of externalities that the decisions may have on others. Our results indicate that even without strategic interaction and moral elements humans prefer Computerized to Human-Driven Uncertainty. This holds even when the distribution of outcomes under both types of uncertainty is identical. From a methodological point of view, the findings shed a critical light on behavioral research in which it is common practice to control for strategic uncertainty by comparing interaction with an artificial agent with a known strategy to interaction with humans. Outside the laboratory, our results suggest that whenever dependence on humans is changed to dependence on computers and other kinds of "artificial" decision makers, preferences with regard to these dependencies may change too.

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Section: Discussionmentioning

confidence: 99%

On whom would I want to depend; humans or computers?

Farjam

2019

Journal of Economic Psychology

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“…However, in the defense of algorithmic traders, there has also been research published by Farjam et al in the Journal of Economic Behavior & Organization showing that hybrid markets with both human and algorithmic traders generally exhibit smaller bubbles than human-only markets [34]. One possible interpretation is that in a highly competitive environment with algorithmic traders, such programs can more effectively close up arbitrage opportunities as they arise and contribute to price discovery.…”

Section: Use-case: Trade Reconciliationsmentioning

confidence: 99%

“…Interestingly, this effect still persists in a version of a human-only market where participants believe they could be trading against algorithms. It is speculated that this effect is observed as a result of human traders expecting trading algorithms to have more rational behavior and so human traders alter their behavior to be more rational in return even if there are no algorithmic traders [34].…”

Section: Use-case: Trade Reconciliationsmentioning

confidence: 99%

Survey of EU ethical guidelines for commercial AI: case studies in financial services

2021

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A macro perspective examining the general nature of AI implementations and how enforcement should be structured under the new frontier of AI technologies is severely needed. The paper critically analyzes real and potential ethical impacts of AI-enabled systems as well as the standard process regulators, researchers, and firms use to assess the risks of these technologies. Three real-world cases are detailed as each type of AI implementation highlights varying degrees of ethical impacts. The paper surveys whether the current September 2020 European Parliament standard titled "European framework on ethical aspects of artificial intelligence, robotics and related technologies" will handle all cases effectively. Future regulators enforcing principles must be able to discern how each AI implementation should be handled as it is evident that there is a spectrum of ethical applicability on the use-case level. The cases examined are in using AI to automate the mortgage application process, find matching attributes for trade reconciliation tasks, and optimizing order entries within trading algorithms. The focus of the cases provided is in the financial industry as firms in this sector, on average, spend the highest percentage of their total revenue on information technology projects. Though the EU framework is thorough in recommending an ex-ante approach, providing risk classifications, and detailing effective measures to mitigate harm from AI-enabled systems, it falls short in identifying certain macroeconomic harms caused by AI-enabled systems and tracking the applications responsible within complex, interlinked systems.

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“…From the perspective of human-machine collaboration, Farjam and Kirchkamp (2018) believe that HI is an advanced form of collective intelligence. The early researches on collective intelligence mainly focus on the philosophical level.…”

Section: Related Workmentioning

confidence: 99%

Hybrid Intelligence in Big Data Environment: Concepts, Architectures, and Applications of Intelligent Service

Liu

Zeng

2021

Data and Information Management

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Based on the emerging concept of “Hybrid Intelligence,” this paper aims to explore a new model of human–computer interaction, and deeply research on its development and application of Intelligent Service in the big data environment. It systematically explores the related academic concepts of hybrid intelligence, and establishes its architecture model. The development of hybrid intelligence is faced with cognitive differences, system fragmentation, human–machine digital divide, and other issues. Strengthening the interaction between cognition and perception can be the key to break through the bottleneck. The intelligent service system based on the hybrid intelligent architecture takes knowledge fusion as the core, and “cloud intelligent brain” is making it possible for the human–computer symbiosis driven by hybrid intelligence. The proposed advanced human–computer interaction mode constructs a hybrid intelligent architecture model, enriches the concept system of human–machine hybrid intelligence, and provides a new landing scheme for intelligent services based on complex scenes in the big data environment.

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Bubbles in hybrid markets: How expectations about algorithmic trading affect human trading

Cited by 32 publications

References 51 publications

On whom would I want to depend; humans or computers?

On whom would I want to depend; humans or computers?

Survey of EU ethical guidelines for commercial AI: case studies in financial services

Hybrid Intelligence in Big Data Environment: Concepts, Architectures, and Applications of Intelligent Service

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