基于市场情绪平稳度的股指期货日内交易策略源码(基于python实现)

from all_utils import emotional_stability_utils from domain.configuration import Configuration # 计算一天的交易数据 # transaction_data 保存所有的交易数据 # date_value 日期 # date_init_list 一天所有的原始csv数据 # sample_observation_begin_index 样本观察开始索引 # sample_observation_end_index 样本观察结束索引 # finish_index 收盘平仓时的索引 def calculate_transaction_data(transaction_data, date_value, date_init_list, sample_observation_begin_index, sample_observation_end_index, finish_index): # 根据样本观察索引区间获取样本数据 sample_observation = date_init_list[sample_observation_begin_index:sample_observation_end_index] print("样本长度为：" + str(len(sample_observation))) # 根据样本数据计算情绪平稳度 emotional_stability = emotional_stability_utils.calculate_emotional_stability(sample_observation) # 情绪平稳度小于阈值，决定开仓 if emotional_stability < Configuration.emotional_stability_threshold: print("情绪平稳度小于阈值，决定开仓") # 样本观察收盘价 sample_observation_end_close = date_init_list[sample_observation_end_index - 1]["close"] # 样本观察开盘价 sample_observation_begin_open = date_init_list[sample_observation_begin_index]["open"] # 在样本观察之后的下一分钟开盘买入 buy_price = date_init_list[sample_observation_end_index]["open"] # 如果样本观察的收盘价大于样本观察开盘价，则做多 if sample_observation_end_close > sample_observation_begin_open: print("开始做多") long = 1 else: print("开始做空") long = 0 for i_value in range(sample_observation_end_index + 1, finish_index): # 在开盘之后判断是否需要止损 sell_price = date_init_list[i_value]["open"] # 如果做多，则用卖出价格减去买入价格 if long == 1: percent = (sell_price - buy_price) / buy_price # 如果做空，则用买入价格减去卖出价格 else: percent = (buy_price - sell_price) / sell_price # 如果损失大于止损阈值，则平仓止损 if percent < 0 and abs(percent) > Configuration.stop_loss_threshold: print("平仓止损") transaction_data["money"] = transaction_data["money"] * (1 + percent - Configuration.service_charge) transaction_data["details"].append( dict(date=date_value, money=transaction_data["money"])) return print("收盘平仓") sell_price = date_init_list[finish_index - 1]["close"] # 如果做多，则用卖出价格减去买入价格 if long == 1: percent = (sell_price - buy_price) / buy_price # 如果做空，则用买入价格减去卖出价格 else: percent = (buy_price - sell_price) / sell_price transaction_data["money"] = transaction_data["money"] * (1 + percent - Configuration.service_charge) transaction_data["details"].append( dict(date=date_value, money=transaction_data["money"])) return else: print("情绪平稳度大于阈值，决定不开仓") transaction_data["details"].append(dict(date=date_value, money=transaction_data["money"])) return