-- coding: utf-8 --import pandas as pd 全局配置 BENCHMARK “000852.XSHG”INDEX_CODE “000852.XSHG”STOCK_NUM 50SINGLE_MAX_WEIGHT 0.03FACTOR_WEIGHT {“pe”: 0.3,“roe”: 0.3,“gp”: 0.2,“mom”: 0.2} 因子预处理函数 def winsorize(ser):q1 ser.quantile(0.01)q99 ser.quantile(0.99)return ser.clip(q1, q99)def standard(ser):mean_val ser.mean()std_val ser.std()return (ser - mean_val) / std_val 初始化 def initialize(context):set_benchmark(BENCHMARK)context.last_month None 月度调仓核心 def rebalance(context):today context.current_dt.strftime(“%Y-%m-%d”)# 获取中证1000成分股并过滤ST、新股stock_list get_index_stocks(INDEX_CODE, datetoday)valid []for s in stock_list:info get_security_info(s)if “ST” in info.display_name:continuestart_date pd.to_datetime(info.start_date)curr_date pd.to_datetime(today)if (curr_date - start_date).days 60:valid.append(s)target_count len(valid) if len(valid) STOCK_NUM else STOCK_NUM # 拉取财务因子 q query( valuation.code, valuation.pe_ratio, indicator.roe, indicator.gross_profit_margin ).filter(valuation.code.in_(valid)) fund_df get_fundamentals(q, datetoday).set_index(code) fund_df fund_df.dropna() if len(fund_df) 0: log.info(无有效财务数据跳过调仓) return # 计算动量修复DataFrame取数报错 mom_dict {} for code in fund_df.index: # 网页免费版get_price 返回DataFrame df get_price(code, count20, fields[close]) if len(df) 5: continue # 正确取最后一日/首日收盘价 close_first df[close].iloc[0] close_last df[close].iloc[-1] mom_dict[code] close_last / close_first - 1 # 动量缺失兜底 if len(mom_dict) 0: mom_df pd.DataFrame(list(mom_dict.items()), columns[code, mom]).set_index(code) all_df pd.concat([fund_df, mom_df], axis1).dropna() else: log.info(动量数据缺失仅使用财务因子打分) all_df fund_df.copy() all_df[mom] 0 if len(all_df) 1: log.info(无有效因子标的跳过调仓) return # 多因子加权打分 score pd.DataFrame(indexall_df.index) score[pe] -1 * standard(winsorize(all_df[pe_ratio])) * FACTOR_WEIGHT[pe] score[roe] standard(winsorize(all_df[roe])) * FACTOR_WEIGHT[roe] score[gp] standard(winsorize(all_df[gross_profit_margin])) * FACTOR_WEIGHT[gp] score[mom] standard(winsorize(all_df[mom])) * FACTOR_WEIGHT[mom] score[total] score.sum(axis1) target_stocks score.sort_values(total, ascendingFalse).head(target_count).index.tolist() single_weight min(1 / len(target_stocks), SINGLE_MAX_WEIGHT) # 清仓不在目标内的股票 for pos_code in list(context.portfolio.positions.keys()): if pos_code not in target_stocks: order(pos_code, 0) # 买入新持仓修复行情取数KeyError total_cash context.portfolio.cash single_cash total_cash * single_weight for code in target_stocks: df_check get_price(code, count1, fields[close]) if df_check.empty: continue close_price df_check[close].iloc[-1] # A股100股一手 trade_share int(single_cash / close_price / 100) * 100 if trade_share 0: order(code, trade_share) log.info(f月度调仓完成当期持仓{len(target_stocks)}只股票)每日循环按月判断调仓def handle_data(context, data):cur_month context.current_dt.monthif cur_month ! context.last_month:rebalance(context)context.last_month cur_month