Examining how adaptive intelligence can create resilient trading ecosystems
Researchers from IBM and Wipro explore how multi-agent LLMs and multi-modal trading agents can be used to build trading ecosystems that perform better under stress.
The ever-increasing complexity and volatility of global stock markets necessitate the implementation of advanced systems to ensure systemic resilience against abrupt disruptions. Traditional trading mechanisms struggle to adapt to dynamic market conditions, exacerbating systemic risks and inefficiencies during significant shocks. Recent technological advancements, such as multi-agent large language models and multi-modal trading agents, provide promising avenues for achieving adaptive, scalable
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