政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/147098

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政大機構典藏 > 資訊學院 > 資訊科學系碩士在職專班 > 學位論文 > Item 140.119/147098

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题名:	建構低波動量化交易模型的金融資產配置優化策略 Building a Quantitative Trading Model with Low Volatility to Achieve Optimal Financial Asset Allocation Strategy
作者:	陳韻清 Chen, Yun-Ching
贡献者:	胡毓忠 Hu,Yuh-Jong 陳韻清 Yun-Ching Chen
关键词:	深度強化學習金融資產配置低波動投資 Deep Reinforcement Learning Asset Allocation Low-volatility investing
日期:	2023
上传时间:	2023-09-01 15:40:11 (UTC+8)
摘要:	近年來，受到「地緣政治」、「貨幣緊縮」、「高通膨」、「景氣衰退」等因素影響，金融市場更加趨於波動與不穩定。為了協助一般資產客群在如此波動環境下可以穩定且安心投資，本論文提出了一種建立在低波動策略基礎上的投資組合配置模型。該模型融合了深度強化學習技術與量化交易策略，並透過獎勵函數的設計，讓模型能夠根據投資資產與市場價格近三個月波動程度的相對比例來調整獎勵。在此設計下，相對於市場波動度高的資產獲得的報酬會減少，相對於市場波動度低的資產獲得的報酬則會增加。因此，會驅使模型分配更多的權重給低波動的資產，從而建立起低波動量化交易模型的金融資產配置優化策略。我們使用美國市場交易所交易基金(Exchange Traded Funds)與總體經濟之歷史數據進行訓練與回測。實驗結果顯示，本論文建構之低波動量化交易模型，可於波動市場環境下，適度降低資產波動率，穩定投資組合，避免投資者因情緒波動而做出不理性的決策，並且可以獲得適度之報酬。 Recently, the financial market has experienced heightened volatility, exacerbated by geopolitical tensions, monetary tightening, surging inflation rates, and a prolonged reces- sion. This thesis proposes a portfolio allocation model based on a low-volatility strategy to meet mass affluents’ needs to invest stably and safely in such a volatile environment. This model integrates deep reinforcement learning (DRL) and quantitative trading strate- gies. Through the design of the DRL’s reward function, the model can adjust the reward according to the relativity of investment assets and market price fluctuations for the past three months. Under this design, assets with relatively higher market volatility will re- ceive less rewards, while those with lower volatility will receive more. Hence, the model will be driven to assign higher weightage to low-volatility assets and establish a financial asset allocation optimization strategy for a low-volatility quantitative trading model. In this thesis, we use historical data of Exchange Traded Funds in the US market and the overall economy for training and backtesting. The results of the experiments show that the low-volatility quantitative trading model constructed by this thesis can, in a volatile market environment, appropriately reduce asset volatility, stabilize investment portfolios, prevent investors from making irrational decisions due to emotional fluctuations, and ob-tain moderate returns.
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描述:	碩士國立政治大學資訊科學系碩士在職專班 110971027
資料來源:	http://thesis.lib.nccu.edu.tw/record/#G0110971027
数据类型:	thesis
显示于类别:	[資訊科學系碩士在職專班] 學位論文

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