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Artículos de Adam
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Deep Q-Learning Applied to Algorithmic Trading
Deep Q-Learning Applied to Algorithmic Trading
In the book "A Random Walk Down Wall Street", the author Burton G. Malkiel claimed that: “a blindfolded monkey throwing…
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Machine Learning and Stochastic Models for Predicting FOMC Meetings' Impact
Machine Learning and Stochastic Models for Predicting FOMC Meetings' Impact
In this article, we will use stochastic financial modeling and machine learning to estimated the impact of the next…
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Bond Valuations Explained With Python
Bond Valuations Explained With Python
Bond selection is a good exercise in rounding ones portfolio, mainly determining the fair value of a bond based on its…
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Unsupervised Learning as Signals for Pairs Trading and StatArb
Unsupervised Learning as Signals for Pairs Trading and StatArb
In this article, we will leverage clustering algorithms to detect pairs in a universe of tradable securities. We will…
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Temporal Convolutional Neural Network with Conditioning for Broad Market Signals
Temporal Convolutional Neural Network with Conditioning for Broad Market Signals
There is a naive strategy amongst the alleged day-traders, that if you buy a levered ETF at open, and sell at close…
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Analysis of a Naive Statistical Arbitrage for Trading
Analysis of a Naive Statistical Arbitrage for Trading
Statistical arbitrage (StatArb) is any technique in quantitative finance that uses statistical and mathematical models…
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Solving for the Efficient Frontier in Stock Portfolios
Solving for the Efficient Frontier in Stock Portfolios
The Efficient Frontier, a core concept in Harry Markowitz's Modern Portfolio Theory (MPT), is used in quantitative…
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Analysis of Oscillators as Technical Trading Signals
Analysis of Oscillators as Technical Trading Signals
Oscillators are momentum indicators used in quantitative trading to identify turning points. Using moving averages and…
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Pairs-Trading Strategy Analysis
Pairs-Trading Strategy Analysis
Pairs trading is a more advanced strategy that quants would use to trade a portfolio, rather than guessing on one…
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Momentum and Reversion Trading Signals Analysis
Momentum and Reversion Trading Signals Analysis
In the world of quantitative trading, various strategies are employed to gain a competitive edge in financial markets…
Actividad
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Pathetic rebound in gold and silver, clearly confirming a corrective pattern with lower lows to be seen. BIG long then at those levels. not financial…
Pathetic rebound in gold and silver, clearly confirming a corrective pattern with lower lows to be seen. BIG long then at those levels. not financial…
Recomendado por Adam Darmanin
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Delivery Hero: The more it drops the more shares I'll buy. This time I'm not unloading at 40. The trading volume is so ridiculously low... we want…
Delivery Hero: The more it drops the more shares I'll buy. This time I'm not unloading at 40. The trading volume is so ridiculously low... we want…
Recomendado por Adam Darmanin
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Do you hold Baidu? Yeah 1 symbolic share. Do you hold any gold miner? Yeah one symbolic share of each. I dont know anybody who lost money taking…
Do you hold Baidu? Yeah 1 symbolic share. Do you hold any gold miner? Yeah one symbolic share of each. I dont know anybody who lost money taking…
Recomendado por Adam Darmanin
Experiencia
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Educación
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Licencias y certificaciones
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WDF Driver Development.
Datronic
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Publicaciones
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Language Model Guided Reinforcement Learning in Quantitative Trading
arXiv
Ver publicaciónAlgorithmic trading requires short-term decisions aligned with long-term financial goals. While reinforcement learning (RL) has been explored for such tactical decisions, its adoption remains limited by myopic behavior and opaque policy rationale. In contrast, large language models (LLMs) have recently demonstrated strategic reasoning and multi-modal financial signal interpretation when guided by well-designed prompts.
We propose a hybrid system where LLMs generate high-level trading…Algorithmic trading requires short-term decisions aligned with long-term financial goals. While reinforcement learning (RL) has been explored for such tactical decisions, its adoption remains limited by myopic behavior and opaque policy rationale. In contrast, large language models (LLMs) have recently demonstrated strategic reasoning and multi-modal financial signal interpretation when guided by well-designed prompts.
We propose a hybrid system where LLMs generate high-level trading strategies to guide RL agents in their actions. We evaluate (i) the rationale of LLM-generated strategies via expert review, and (ii) the Sharpe Ratio (SR) and Maximum Drawdown (MDD) of LLM-guided agents versus unguided baselines. Results show improved return and risk metrics over standard RL.
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Maltese
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English
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Spanish
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German
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Recomendaciones recibidas
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Unirse para verloMás actividad de Adam
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Most investors and finance scholars use the Sharpe ratio. Few use it correctly. The result? Misleading conclusions and costly mistakes. In our new…
Most investors and finance scholars use the Sharpe ratio. Few use it correctly. The result? Misleading conclusions and costly mistakes. In our new…
Recomendado por Adam Darmanin
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I have to vent a bit, sorry for that. I just experimented with implementations of Mutual Information (MI). While MI is theoretically compelling…
I have to vent a bit, sorry for that. I just experimented with implementations of Mutual Information (MI). While MI is theoretically compelling…
Recomendado por Adam Darmanin
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Bought more Delivery Hero shares on the dip.
Bought more Delivery Hero shares on the dip.
Recomendado por Adam Darmanin