# 基于深度学习和强化学习的量化交易系统（quantitative trading system based on Deep learning and Reinforcement Learning） (中文版本在英文版本的下面，请下拉查看) OUTLINE: 1. main structure 2. still working on 3. conclusion MAIN STRUCTURE: The system consist of: Data processing module Price prediction module The reinforcement learning module based on: the design for 6 actions(sell, short, sellhold, shorthold, sell, cover) The reinforcement learning module based on: 1. Using the up and down line of VWAP or BBIBOLL to transform the price into (-1,1) 2. Design two reinforcement learning models seperately for (buy, sell hold) and (short, cover,hold) 3. Set the priority for two models, and decide which action should be output Stocking picking strategy based on price prediction and RL return Data Processing Module I get the data set from Kaggle, which is the daily price and volume data of American stock market. The data set consist of open price, close price, high price, low price and volume. But this kind of data doesn't work well in the training of Deep learning and Reinforcement Learning. So I create dozens of technical analys

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