The new frontier of personalized portfolio management: quantitative methods with LangChain
This paper explores the integration of advanced computational techniques and Large Language Models (LLMs) in portfolio management, aiming to overcome the limitations of traditional robo-advisors and mean-variance optimization (MVO). We present a novel framework that incorporates Monte Carlo simulati...
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2024
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sg-ntu-dr.10356-1752122024-04-26T15:41:36Z The new frontier of personalized portfolio management: quantitative methods with LangChain Cheam, Caleb Zhong Wei Ng Wee Keong School of Computer Science and Engineering AWKNG@ntu.edu.sg Computer and Information Science Mathematical Sciences Monte Carlo Portfolio optimization Risk management This paper explores the integration of advanced computational techniques and Large Language Models (LLMs) in portfolio management, aiming to overcome the limitations of traditional robo-advisors and mean-variance optimization (MVO). We present a novel framework that incorporates Monte Carlo simulations, Geometric Brownian Motion, and machine learning methods like clustering algorithms and differential evolution to enhance portfolio optimization. Our methodology leverages the power of LLMs to process unstructured data and provide personalized investment advice, reflecting a shift from conventional financial advisory methods toward more adaptive and investor-centric models. The research demonstrates how combining modern computational tools and AI can address specific investor preferences, improve risk management, and increase the transparency of investment strategies. We use a series of experiments to validate the effectiveness of our proposed solutions in achieving superior portfolio allocations compared to traditional methods. The findings suggest that our integrated approach not only aligns more closely with individual investor profiles but also enhances the robustness and efficiency of portfolio management in dynamic market conditions. Bachelor's degree 2024-04-21T11:43:11Z 2024-04-21T11:43:11Z 2024 Final Year Project (FYP) Cheam, C. Z. W. (2024). The new frontier of personalized portfolio management: quantitative methods with LangChain. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175212 https://hdl.handle.net/10356/175212 en SCSE23-0205 application/pdf Nanyang Technological University |
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Computer and Information Science Mathematical Sciences Monte Carlo Portfolio optimization Risk management Cheam, Caleb Zhong Wei The new frontier of personalized portfolio management: quantitative methods with LangChain |
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This paper explores the integration of advanced computational techniques and Large Language Models (LLMs) in portfolio management, aiming to overcome the limitations of traditional robo-advisors and mean-variance optimization (MVO). We present a novel framework that incorporates Monte Carlo simulations, Geometric Brownian Motion, and machine learning methods like clustering algorithms and differential evolution to enhance portfolio optimization. Our methodology leverages the power of LLMs to process unstructured data and provide personalized investment advice, reflecting a shift from conventional financial advisory methods toward more adaptive and investor-centric models. The research demonstrates how combining modern computational tools and AI can address specific investor preferences, improve risk management, and increase the transparency of investment strategies. We use a series of experiments to validate the effectiveness of our proposed solutions in achieving superior portfolio allocations compared to traditional methods. The findings suggest that our integrated approach not only aligns more closely with individual investor profiles but also enhances the robustness and efficiency of portfolio management in dynamic market conditions. |
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Ng Wee Keong |
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Ng Wee Keong Cheam, Caleb Zhong Wei |
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Final Year Project |
author |
Cheam, Caleb Zhong Wei |
author_sort |
Cheam, Caleb Zhong Wei |
title |
The new frontier of personalized portfolio management: quantitative methods with LangChain |
title_short |
The new frontier of personalized portfolio management: quantitative methods with LangChain |
title_full |
The new frontier of personalized portfolio management: quantitative methods with LangChain |
title_fullStr |
The new frontier of personalized portfolio management: quantitative methods with LangChain |
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The new frontier of personalized portfolio management: quantitative methods with LangChain |
title_sort |
new frontier of personalized portfolio management: quantitative methods with langchain |
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Nanyang Technological University |
publishDate |
2024 |
url |
https://hdl.handle.net/10356/175212 |
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1806059896478629888 |