Optimization of Dynamic Crypto Portfolios via Deep Reinforcement Learning Under Transaction Costs
The DRL-PPO strategy generated an annualized return of 37.22% under a 0.1% transaction cost constraint.
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The DRL-PPO strategy generated an annualized return of 37.22% under a 0.1% transaction cost constraint.
BIS Working Paper No. 1049 assembled a Sensor Tower panel of retail crypto-exchange app downloads and daily active users (DAUs) covering 95 countries from August 2015 to June 2022.
The proposed DAC-CPPO model achieves an overall accuracy of 97.6%, an MAE of 0.074, and an RMSE of 0.081 for portfolio optimization.