The highly intelligent virtual agents for modeling financial markets

Yang, Guang; Chen, Y.; Huang, Jiping

doi:10.1016/j.physa.2015.09.071

Cited by 10 publications

(5 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the agents constructed by the researchers were able to provide eight times the returns of the S&P stock exchange, but they were not able to beat the market for the Nikkei 225. These models could also anticipate tipping points (Yang et al, 2016). One study adopted an actor‐critic “Deep Deterministic Policy Gradient,” a kind of reinforcement learning algorithm, to examine trading on the Chinese stock exchange.…”

Section: The Application Sectors Of Ai In Finance and Financial Marketsmentioning

confidence: 99%

“…For the latter, AI techniques are being used along with agent-based modeling to predict stock price dynamics, market impact, tipping points for large market movements, and prices of financial derivatives. From these, trading strategies are also being devised (Yang, Chen, & Huang, 2016).…”

Section: Overview Of Ai In Finance and Financial Marketsmentioning

confidence: 99%

“…Algorithmic trading uses agent-based models that integrate GAs to process information and to evolve the solution proposed because, with time, a fixed strategy stops working (Yang et al, 2016).…”

Section: Algorithmsmentioning

confidence: 99%

See 2 more Smart Citations

Artificial intelligence techniques in finance and financial markets: A survey of the literature

2021

View full text Add to dashboard Cite

Both academic and nonacademic literature is evolving following the oscillating development of artificial intelligence (AI) and computing power's evolution in their application to finance and financial markets. The limits to economic growth encountered after the financial crisis and, successively, the recent pandemic bursts have posed new challenges to AI-related technologies. The surveyed publications have given hope in harvesting improved efficiency, new data, information, advisory and management services, risk mitigation, and some unanswered questions regarding negative impacts on sustainable growth and increasing economic welfare.

show abstract

Section: The Application Sectors Of Ai In Finance and Financial Marketsmentioning

confidence: 99%

Section: Overview Of Ai In Finance and Financial Marketsmentioning

confidence: 99%

See 1 more Smart Citation

Artificial intelligence techniques in finance and financial markets: A survey of the literature

2021

View full text Add to dashboard Cite

show abstract

“…As an example of this, an agent could be i) informed about issues in the environment beyond the opponent himself, and ii) hypothesize about which information the opponent is actually using to make his predictions and learn. The importance of learning in automated negotiations has been previously recognized [32,33], yet the context-awareness capability is not widely seen as a key issue [2,19,30]. Most of previous works circumscribe the agent learning to ad-hoc decision-making policies that may not capture appropriately the influence of the context on the outcome of a negotiation episode.…”

Section: Introductionmentioning

confidence: 99%

“…In order to clarify our point of view, let us discuss briefly some related work. In [2,30], the context is represented through a fixed model, but any new variable that could change the course of the negotiation is discarded. Another example is given in [19].…”

Section: Introductionmentioning

confidence: 99%

The importance of context-dependent learning in negotiation agents

Kröhling

Chiotti²,

Martínez³

2019

View full text Add to dashboard Cite

Automated negotiation between artificial agents is essential to deploy Cognitive Computing and Internet of Things. The behavior of a negotiation agent depends significantly on the influence of environmental conditions or contextual variables, since they affect not only a given agent preferences and strategies, but also those of other agents. Despite this, the existing literature on automated negotiation is scarce about how to properly account for the effect of context-relevant variables in learning and evolving strategies. In this paper, a novel context-driven representation for automated negotiation is introduced. Also, a simple negotiation agent that queries available information from its environment, internally models contextual variables, and learns how to take advantage of this knowledge by playing against himself using reinforcement learning is proposed. Through a set of episodes against other negotiation agents in the existing literature, it is shown using our context-aware agent that it makes no sense to negotiate without taking context-relevant variables into account. Our context-aware negotiation agent has been implemented in the GENIUS environment, and results obtained are significant and quite revealing.

show abstract

WSIA: Web Ontological Search Engine Based on Smart Agents Applied to Scientific Articles

Ariza-Colpas

Piñeres-Melo

Bernal

et al. 2019

Lecture Notes in Computer Science

View full text Add to dashboard Cite

The Semantic Web proposed by the W3C (Word Wide Web Consortium), aims to make the automation of the information contained in the current web through semantic processing based on ontologies that define what must be the rules used for the representation knowledge. This article resulting from the research project "Model for the representation of knowledge based on Web ontologies and intelligent search agents, if required: Scientific articles WSIA" proposes an architecture for finding information through intelligent agents and ontologies Web of scientific articles. This paper shows the architecture, implementation and comparing these with traditional applications.

show abstract

The highly intelligent virtual agents for modeling financial markets

Cited by 10 publications

References 48 publications

Artificial intelligence techniques in finance and financial markets: A survey of the literature

Artificial intelligence techniques in finance and financial markets: A survey of the literature

The importance of context-dependent learning in negotiation agents

WSIA: Web Ontological Search Engine Based on Smart Agents Applied to Scientific Articles

Contact Info

Product

Resources

About