algorithmic trading
PulseAugur coverage of algorithmic trading — every cluster mentioning algorithmic trading across labs, papers, and developer communities, ranked by signal.
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FinSMART framework uses reinforcement learning for adaptive financial sentiment analysis
A new framework called FinSMART has been developed for financial sentiment analysis, utilizing market-aligned reinforcement learning. Unlike previous supervised methods that use static datasets, FinSMART directly optimi…
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LLMs applied to algorithmic trading for optimized order execution
Researchers have developed PACE (Plan-Ahead Controlled Execution), a novel framework that utilizes large language models (LLMs) for parent-order execution in algorithmic trading. This approach aims to optimize the split…
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Algorithmic Trading Faces Limits Despite Data and Compute Gains
Algorithmic trading strategies may not benefit from increased data and computational power alone. The complexity of market dynamics and the potential for overfitting suggest that simply scaling existing approaches could…
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Databricks outlines AI use cases and responsible deployment in finance
Databricks has published a guide detailing practical applications of AI in finance, covering areas such as credit scoring, algorithmic trading, and finance automation. The guide emphasizes responsible deployment through…
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Goldman Sachs sees best arbitrage conditions in 20 years; Dashangda stock falls
Goldman Sachs has identified the current environment as the most favorable for arbitrage trading in over two decades, citing the foreign exchange market's daily turnover of $9.5 trillion. The firm suggests favoring trad…
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China's securities regulator to enhance algorithmic trading oversight
China's Securities Regulatory Commission (CSRC) Chairman Wu Qing emphasized the growing importance of algorithmic trading in global capital markets, including in China. He stated that regulators have implemented various…