Improve jq microcap execution semantics

2026-04-18 18:02:50 +08:00
parent 9f4165e689
commit 0e2c25e4c4
26 changed files with 5058 additions and 362 deletions
--- a/聚宽微盘股策略.py
+++ b/聚宽微盘股策略.py
@@ -0,0 +1,654 @@
+'''
+设定的市值17—26亿 可以根据指数的变化来更改
+比如3300点集中在15—25亿市值最小的四十只 3400点 集中在17—27亿
+对应指数乘以一个系数 对应市值选出40只
+'''
+from jqdata import *
+from datetime import datetime, timedelta
+
+
+## 初始化函数，设定要操作的股票、基准等等
+def initialize(context):
+
+    set_benchmark('000852.XSHG')  #对标中证1000
+    # True为开启动态复权模式，使用真实价格交易
+    set_option('use_real_price', True)
+    # 设定成交量比例
+    set_option('order_volume_ratio', 1)
+    # 股票类交易手续费是：买入时佣金万分之三，卖出时佣金万分之三加千分之一印花税, 每笔交易佣金最低扣5块钱
+    set_order_cost(OrderCost(open_tax=0, close_tax=0.001, \
+                             open_commission=0.0003, close_commission=0.0003,\
+                             close_today_commission=0, min_commission=5), type='stock')
+
+    # 交易日计时器
+    g.days = 0
+    # 分仓常量参数,无须人为修改
+    g.TR = 1;
+    # 区间最高价
+    g.summit = {}
+    g.muster = []
+    # 运行状态 1/运行; 0/停运
+    g.OpenYN = 1
+
+    # 开始范围
+    #g.mystart = 13
+    # 截至范围
+    #g.myend = 23
+
+    # 调仓频率
+    g.refresh_rate = 15
+    # 运行函数1
+    run_daily(trade, time='10:18')
+    # 运行函数2
+    run_daily(CPtrade, time='10:17')
+
+    # 持仓数量
+    g.stocknum = 40
+    # 上证指数对应系数
+    g.XS = 4/500
+    #止盈比率
+    g.CloseRate = 1.07
+     #止损比率
+    g.LossRate = 0.93
+
+    # 均线上涨比率
+    g.RSIRate = 1.0001
+
+    # 保证金仓位比率: 1/2为半仓
+    g.TradeRate = 0.5
+    # 调试日志展示数量
+    g.debug_log_limit = 60
+    g.debug_boundary_window = 5
+    g.market_cap_map = {}
+
+
+def _fmt_num(value, digits=2):
+    try:
+        return ('%.' + str(digits) + 'f') % float(value)
+    except Exception:
+        return str(value)
+
+
+def _safe_bar_values(bar_data, field):
+    try:
+        values = bar_data[field]
+    except Exception:
+        values = getattr(bar_data, field)
+    try:
+        return [float(x) for x in list(values)]
+    except Exception:
+        try:
+            return list(values)
+        except Exception:
+            return []
+
+
+def _safe_bar_last(bar_data, field):
+    values = _safe_bar_values(bar_data, field)
+    if values:
+        return values[-1]
+    return None
+
+
+def _market_cap_text(stock):
+    cap = getattr(g, 'market_cap_map', {}).get(stock)
+    if cap is None:
+        return 'None'
+    return _fmt_num(cap, 2) + '亿'
+
+
+def _describe_stock(stock, extras=None):
+    parts = [stock, '市值=' + _market_cap_text(stock)]
+    if extras:
+        parts.extend(extras)
+    return ','.join(parts)
+
+
+def _log_detail_items(label, details, limit=None, chunk=10):
+    total = len(details)
+    if total == 0:
+        log.info(label + ': 0')
+        return
+
+    if limit is None:
+        limit = total
+    shown = details[:limit]
+    log.info('%s: 总数=%d, 展示=%d' % (label, total, len(shown)))
+    for idx in range(0, len(shown), chunk):
+        part = shown[idx:idx + chunk]
+        log.info('%s[%d-%d]: %s' % (
+            label,
+            idx + 1,
+            idx + len(part),
+            ' | '.join(part)
+        ))
+    if total > limit:
+        log.info('%s: 其余%d项省略' % (label, total - limit))
+
+
+def _log_market_cap_snapshot(df, caller):
+    if df is None or len(df) == 0:
+        log.info('市值筛选快照[%s]: 无数据' % caller)
+        return
+
+    top_n = min(len(df), g.debug_log_limit)
+    top_details = []
+    for i in range(top_n):
+        row = df.iloc[i]
+        top_details.append('%d.%s:%s亿' % (
+            i + 1,
+            row['code'],
+            _fmt_num(row['market_cap'], 2)
+        ))
+    _log_detail_items('市值排序前段[%s]' % caller, top_details, limit=top_n, chunk=8)
+
+    start_idx = max(0, g.stocknum - g.debug_boundary_window - 1)
+    end_idx = min(len(df), g.stocknum + g.debug_boundary_window)
+    boundary_details = []
+    for i in range(start_idx, end_idx):
+        row = df.iloc[i]
+        boundary_details.append('%d.%s:%s亿' % (
+            i + 1,
+            row['code'],
+            _fmt_num(row['market_cap'], 2)
+        ))
+    _log_detail_items('市值排序边界[%s]' % caller, boundary_details, limit=len(boundary_details), chunk=5)
+
+
+## 选出小市值股票
+def check_stocks(context, caller='unknown'):
+
+    g.today = context.current_dt
+    validate_date()
+
+    #不停运参数
+    g.OpenYN = 1
+
+    log.info('选股开始[%s]: 日期=%s, g.days=%d, refresh_rate=%d, 持仓数=%d' % (
+        caller,
+        context.current_dt.strftime('%Y-%m-%d %H:%M:%S'),
+        g.days,
+        g.refresh_rate,
+        len(context.portfolio.positions)
+    ))
+
+    # 检查日期是否在范围内
+    if g.OpenYN == 0:
+        log.warn("该时段属于停运==================范围")
+        return []
+    else:
+        # g.OpenYN = 1
+
+        g.security = '000001.XSHG'
+
+        #000852.XSHG
+
+        close_data = get_bars(g.security, count=1, unit='1d', fields=['close'])
+        # 取得过去五天的平均价格
+        MA5 = close_data['close'].mean()
+
+        ###################################################
+        close5_data = get_bars(g.security, count=5, unit='1d', fields=['close'])
+        # 获取股票的收盘价
+        close10_data = get_bars(g.security, count=10, unit='1d', fields=['close'])
+        # 取得过去五天的平均价格
+        MA5 = close5_data['close'].mean()
+        # 取得过去十天的平均价格
+        MA10 = close10_data['close'].mean()
+
+        #5日线下穿,则半仓交易
+        if MA5 < MA10*g.RSIRate:
+            g.TR = g.TradeRate
+        elif MA5 >= MA10*g.RSIRate:
+            g.TR = 1
+        ###################################################
+
+        close5_list = _safe_bar_values(close5_data, 'close')
+        log.info('指数均线调试[%s][%s] close[-5:]=%s, ma5=%s, ma10=%s, ma5<ma10*RSIRate=%s, TR=%s' % (
+            caller,
+            context.current_dt.strftime('%Y-%m-%d'),
+            str([round(float(v), 2) for v in close5_list]),
+            _fmt_num(MA5, 4),
+            _fmt_num(MA10, 4),
+            str(MA5 < MA10 * g.RSIRate),
+            _fmt_num(g.TR, 4)
+        ))
+
+
+        # 取得上一时间点价格
+        current_price = close_data['close'][-1]
+
+        log.info('中证指数(current_price)：'+str(current_price))
+
+        if current_price == 2000:
+            g.mystart = 7
+            g.myend = 17
+        elif current_price > 0:
+            #Y = (current_price - 3000) *g.XS + 14
+            Y = (current_price - 2000) *g.XS + 7
+            g.mystart = Y
+            g.myend = Y + 10
+
+        # mystart = g.start
+        # myend = g.end
+        mystart = round(g.mystart)
+        myend = round(g.myend)
+
+        log.info('价格区间为:'+ str(mystart) + '~'+str(myend))
+
+
+        # 设定查询条件
+        q = query(
+                valuation.code,
+                valuation.market_cap
+            ).filter(
+                valuation.market_cap.between(mystart,myend)
+            ).order_by(
+                valuation.market_cap.asc()
+            )
+
+        # 选出低市值的股票，构成buylist
+        df = get_fundamentals(q)
+        g.market_cap_map = {}
+        if df is not None and len(df) > 0:
+            for _, row in df.iterrows():
+                try:
+                    g.market_cap_map[row['code']] = float(row['market_cap'])
+                except Exception:
+                    g.market_cap_map[row['code']] = None
+        log.info('市值筛选结果[%s]: %d只股票' % (caller, 0 if df is None else len(df)))
+        _log_market_cap_snapshot(df, caller)
+        buylist =list(df['code'])
+
+        # 过滤停牌，ST，科创，新股，1元股
+        buylist = filter_paused_stock(buylist, caller=caller)
+
+        final_list = buylist[:g.stocknum]
+        g.muster = final_list
+        _log_detail_items(
+            '最终选股[%s]' % caller,
+            [_describe_stock(stock) for stock in final_list],
+            limit=len(final_list),
+            chunk=8
+        )
+        boundary_slice = buylist[max(0, g.stocknum - g.debug_boundary_window): min(len(buylist), g.stocknum + g.debug_boundary_window)]
+        _log_detail_items(
+            '最终选股边界[%s]' % caller,
+            [_describe_stock(stock) for stock in boundary_slice],
+            limit=len(boundary_slice),
+            chunk=5
+        )
+
+        return final_list
+
+
+def before_trading_start(context):
+    # 取得当前日期
+    g.todayDT = context.current_dt
+    g.today = context.current_dt.strftime('%Y-%m-%d')
+    g.start = context.current_dt + timedelta(-2)
+    g.market_cap_map = {}
+
+## 交易函数
+def CPtrade(context):
+
+    ## 选股
+    stock_list = check_stocks(context, caller='CPtrade')
+    if g.OpenYN == 0:
+        #log.warn("日期属于范围")
+         ## 获取持仓列表
+        sell_list = list(context.portfolio.positions.keys())
+        # 如果有持仓，则卖出
+        if len(sell_list) > 0 :
+            for stock in sell_list:
+                order_target_value(stock, 0)
+        return
+
+
+## 交易函数
+def trade(context):
+     ## 选股
+    stock_list = check_stocks(context, caller='trade')
+    if g.OpenYN == 0:
+        #log.warn("日期属于范围")
+         ## 获取持仓列表
+        sell_list = list(context.portfolio.positions.keys())
+        # 如果有持仓，则卖出
+        if len(sell_list) > 0 :
+            for stock in sell_list:
+                order_target_value(stock, 0)
+        return
+
+    g.changeYN = 0
+    curr_data = get_current_data()
+    log.info('交易调试[trade]: 日期=%s, g.days=%d, refresh_hit=%s, TR=%s, cash=%s, total_value=%s, 持仓数=%d, 目标池数=%d' % (
+        context.current_dt.strftime('%Y-%m-%d %H:%M:%S'),
+        g.days,
+        str(g.days % g.refresh_rate == 0),
+        _fmt_num(g.TR, 4),
+        _fmt_num(context.portfolio.cash, 2),
+        _fmt_num(context.portfolio.total_value, 2),
+        len(context.portfolio.positions),
+        len(stock_list)
+    ))
+    _log_detail_items(
+        '交易目标池[trade]',
+        [_describe_stock(stock) for stock in stock_list],
+        limit=len(stock_list),
+        chunk=8
+    )
+    # --------------------------------------------------------------------------
+    for stockPos in context.portfolio.positions:
+        # SS、记录股票峰值信息
+    #   if g.summit.get(stock, 0)<data[stock].high: g.summit[stock]=data[stock].high
+        # S0、取得最近几天股票价格信息
+        grid = get_price(stockPos, start_date=g.start, end_date=g.today, fields=['open', 'high', 'low', 'close', 'high_limit', 'paused'])
+        # SP、跳过退市、停牌、无效数据
+    #    if grid.paused[-1]: continue
+        # S1、目前持仓不在预选股票池中(g.muster)则清仓
+    #    if stock not in g.muster:
+    #        order_target(stock,0)
+    #        log.info("市值清仓：%s" % (stock))
+        # S2、回撤10%则清仓
+        hold = context.portfolio.positions[stockPos]
+        current_price = curr_data[stockPos].last_price
+        avg_cost = hold.avg_cost
+        return_ratio = current_price / avg_cost - 1 if avg_cost else 0
+        grid_high_limit = _safe_bar_last(grid, 'high_limit')
+        grid_close = _safe_bar_last(grid, 'close')
+        grid_paused = _safe_bar_last(grid, 'paused')
+        stop_hit = (current_price / avg_cost < g.LossRate) if avg_cost else False
+        profit_hit = (current_price < grid_high_limit and current_price / avg_cost > g.CloseRate) if (avg_cost and grid_high_limit is not None) else False
+        log.info('止盈止损评估[%s] %s: qty=%s, avg_cost=%s, current=%s, return=%s%%, stop_threshold=%s, profit_threshold=%s, high_limit=%s, bar.close=%s, paused=%s, in_target=%s, stop_hit=%s, profit_hit=%s' % (
+            context.current_dt.strftime('%Y-%m-%d'),
+            stockPos,
+            str(getattr(hold, 'total_amount', getattr(hold, 'amount', 'None'))),
+            _fmt_num(avg_cost, 4),
+            _fmt_num(current_price, 4),
+            _fmt_num(return_ratio * 100, 2),
+            _fmt_num(g.LossRate, 4),
+            _fmt_num(g.CloseRate, 4),
+            _fmt_num(grid_high_limit, 4),
+            _fmt_num(grid_close, 4),
+            str(grid_paused),
+            str(stockPos in stock_list),
+            str(stop_hit),
+            str(profit_hit)
+        ))
+        if stop_hit:
+            order_target_value(stockPos, 0)
+            g.changeYN = 1
+            log.error('止损清仓：%s,当前价=%.2f,成本价=%.2f,收益率=%.2f%%,high_limit=%s,bar.close=%s' % (
+                stockPos,
+                current_price,
+                hold.avg_cost,
+                return_ratio * 100,
+                _fmt_num(grid_high_limit, 4),
+                _fmt_num(grid_close, 4)
+            ))
+        # S3、今日高开、今日未涨停则清仓
+        elif profit_hit:
+            order_target_value(stockPos, 0)
+            g.changeYN = 1
+            log.warn('止盈清仓：%s,当前价=%s,成本价=%s,收益率=%s%%,high_limit=%s,bar.close=%s' % (
+                stockPos,
+                _fmt_num(current_price, 4),
+                _fmt_num(hold.avg_cost, 4),
+                _fmt_num(return_ratio * 100, 2),
+                _fmt_num(grid_high_limit, 4),
+                _fmt_num(grid_close, 4)
+            ))
+        else:
+            g.changeYN = 0
+
+        if g.changeYN == 1:
+            sell_list = list(context.portfolio.positions.keys())
+            replacement_candidates = [stock for stock in stock_list if stockPos != stock and stock not in sell_list]
+            _log_detail_items(
+                '补仓候选[%s][%s]' % (context.current_dt.strftime('%Y-%m-%d'), stockPos),
+                [_describe_stock(stock) for stock in replacement_candidates],
+                limit=min(len(replacement_candidates), g.debug_log_limit),
+                chunk=6
+            )
+            # log.warn('portfoliocash：' + str(context.portfolio.cash))
+            for stock in stock_list:
+                if len(context.portfolio.positions.keys()) < g.stocknum:
+                    ## 获取持仓列表
+                    sell_list = list(context.portfolio.positions.keys())
+                    if stockPos != stock and stock not in sell_list  :
+
+                        ## 分配资金
+                        if len(context.portfolio.positions) < g.stocknum :
+                            Num = g.stocknum - len(context.portfolio.positions)
+                            Cash = context.portfolio.cash * g.TR / Num
+
+                            #gridbuy = get_price(stock, start_date=g.start, end_date=g.today, fields=['open', 'high', 'low_limit', 'close', 'high_limit'])
+
+                            #if gridbuy.open[-1] > gridbuy.low_limit[-1]:
+                            log.info('补仓买入：卖出=%s,买入=%s,Cash=%s,Num=%d,TR=%s,持仓数=%d' % (
+                                stockPos,
+                                stock,
+                                _fmt_num(Cash, 2),
+                                Num,
+                                _fmt_num(g.TR, 4),
+                                len(context.portfolio.positions)
+                            ))
+                            order_value(stock, Cash)
+                            #else :
+                            #    log.warn("忽略跌停股票:" + stock)
+                            break
+                        else:
+                            continue
+
+
+
+    if g.days%g.refresh_rate == 0:
+        log.info('定期调仓触发：日期=%s,g.days=%d,refresh_rate=%d,TR=%s' % (
+            context.current_dt.strftime('%Y-%m-%d'),
+            g.days,
+            g.refresh_rate,
+            _fmt_num(g.TR, 4)
+        ))
+
+        ## 获取持仓列表
+        sell_list = list(context.portfolio.positions.keys())
+        rebalance_sell_list = [stock for stock in sell_list if stock not in stock_list]
+        _log_detail_items(
+            '定期调仓卖出名单',
+            [_describe_stock(stock) for stock in rebalance_sell_list],
+            limit=len(rebalance_sell_list),
+            chunk=8
+        )
+        # 如果有持仓，则卖出
+        if len(sell_list) > 0 :
+            for stock in sell_list:
+                if stock not in stock_list:
+                    log.info('定期调仓卖出：%s' % stock)
+                    order_target_value(stock, 0)
+
+        ## 分配资金
+        if len(context.portfolio.positions) < g.stocknum :
+            Num = g.stocknum - len(context.portfolio.positions)
+            # Cash = context.portfolio.cash/Num * g.TR
+            Cash = context.portfolio.cash * g.TR / g.stocknum
+        else:
+            Cash = 0
+        log.info('定期调仓资金分配：Cash=%s,Num=%s,cash=%s,total_value=%s' % (
+            _fmt_num(Cash, 2),
+            str(Num if len(context.portfolio.positions) < g.stocknum else 0),
+            _fmt_num(context.portfolio.cash, 2),
+            _fmt_num(context.portfolio.total_value, 2)
+        ))
+
+        ## 买入股票
+        for stock in stock_list:
+            if len(context.portfolio.positions.keys()) < g.stocknum:
+                if stock not in sell_list:
+                    log.info('定期调仓买入：%s,Cash=%s' % (stock, _fmt_num(Cash, 2)))
+                    order_value(stock, Cash)
+
+        # 天计数加一
+        g.days = 1
+    else:
+        g.days += 1
+
+# 过滤日期
+# 一月十号到三十一号
+# 四月十号到四月二十九日 期间
+# 八月十日到八月三十一日
+# 十月二十日 到十月三十日
+def validate_date():
+
+    # date = g.todayDT.strftime('%Y-%m-%d')
+    # date = datetime.strptime(g.todayDT, "%Y-%m-%d")
+    date = g.today
+    # 检查是否是4月10日到4月29日之间
+    if date.month == 1 and 15 <= date.day <= 30:
+        g.OpenYN = 0
+    elif date.month == 4 and 15 <= date.day <= 29:
+        g.OpenYN = 0
+    elif date.month == 8 and 15 <= date.day <= 31:
+        g.OpenYN = 0
+    elif date.month == 10 and 20 <= date.day <= 30:
+        g.OpenYN = 0
+    elif date.month == 12 and 20 <= date.day <= 30:
+        g.OpenYN = 0
+    else :
+        g.OpenYN = 1
+
+# 过滤停牌股票
+def filter_paused_stock(stock_list, caller='unknown'):
+    curr_data = get_current_data()
+    raw_count = len(stock_list)
+
+    risk_filtered = []
+    risk_removed = []
+    for stock in stock_list:
+        reasons = []
+        if curr_data[stock].day_open == curr_data[stock].high_limit:
+            reasons.append('涨停开盘')
+        if curr_data[stock].day_open == curr_data[stock].low_limit:
+            reasons.append('跌停开盘')
+        if curr_data[stock].last_price == curr_data[stock].high_limit:
+            reasons.append('当前涨停')
+        if curr_data[stock].last_price == curr_data[stock].low_limit:
+            reasons.append('当前跌停')
+        if curr_data[stock].paused:
+            reasons.append('停牌')
+        if curr_data[stock].is_st:
+            reasons.append('ST')
+        if 'ST' in curr_data[stock].name:
+            reasons.append('名称含ST')
+        if '*' in curr_data[stock].name:
+            reasons.append('名称含*')
+        if '退' in curr_data[stock].name:
+            reasons.append('名称含退')
+        if stock.startswith('688'):
+            reasons.append('科创板')
+
+        if reasons:
+            risk_removed.append(_describe_stock(stock, [
+                '原因=' + '/'.join(reasons),
+                'open=' + _fmt_num(curr_data[stock].day_open, 2),
+                'last=' + _fmt_num(curr_data[stock].last_price, 2),
+                'high_limit=' + _fmt_num(curr_data[stock].high_limit, 2),
+                'low_limit=' + _fmt_num(curr_data[stock].low_limit, 2),
+                'name=' + str(curr_data[stock].name)
+            ]))
+        else:
+            risk_filtered.append(stock)
+
+    log.info('风险过滤[%s]: %d -> %d, 移除=%d' % (
+        caller,
+        raw_count,
+        len(risk_filtered),
+        len(risk_removed)
+    ))
+    _log_detail_items(
+        '风险过滤移除[%s]' % caller,
+        risk_removed,
+        limit=min(len(risk_removed), g.debug_log_limit),
+        chunk=4
+    )
+
+    one_yuan_filtered = []
+    one_yuan_removed = []
+    for stock in risk_filtered:
+        if curr_data[stock].day_open > 1:
+            one_yuan_filtered.append(stock)
+        else:
+            one_yuan_removed.append(_describe_stock(stock, [
+                '原因=1元股过滤',
+                'open=' + _fmt_num(curr_data[stock].day_open, 2),
+                'last=' + _fmt_num(curr_data[stock].last_price, 2)
+            ]))
+
+    log.info('1元股过滤[%s]: %d -> %d, 移除=%d' % (
+        caller,
+        len(risk_filtered),
+        len(one_yuan_filtered),
+        len(one_yuan_removed)
+    ))
+    _log_detail_items(
+        '1元股过滤移除[%s]' % caller,
+        one_yuan_removed,
+        limit=min(len(one_yuan_removed), g.debug_log_limit),
+        chunk=4
+    )
+
+    new_list = []
+    ma_pass_details = {}
+    ma_removed_details = []
+    for stock in one_yuan_filtered:
+        # 获取股票的收盘价
+        close5_data = get_bars(stock, count=5, unit='1d', fields=['close'])
+        # 获取股票的收盘价
+        close10_data = get_bars(stock, count=10, unit='1d', fields=['close'])
+        # 获取股票的收盘价
+        close20_data = get_bars(stock, count=20, unit='1d', fields=['close'])
+        # 取得过去五天的平均价格
+        MA5 = close5_data['close'].mean()
+        # 取得过去十天的平均价格
+        MA10 = close10_data['close'].mean()
+        # 取得过去二十天的平均价格
+        MA20 = close20_data['close'].mean()
+        # 取得上一时间点价格
+        # current_price = close_data['close'][-1]
+        close5_list = [round(float(v), 2) for v in _safe_bar_values(close5_data, 'close')]
+        ma_condition_1 = MA5 > MA10 * g.RSIRate
+        ma_condition_2 = MA10 > MA20
+        detail = _describe_stock(stock, [
+            'close[-5:]=' + str(close5_list),
+            'ma5=' + _fmt_num(MA5, 4),
+            'ma10=' + _fmt_num(MA10, 4),
+            'ma20=' + _fmt_num(MA20, 4),
+            'ma5>ma10*RSIRate=' + str(ma_condition_1),
+            'ma10>ma20=' + str(ma_condition_2)
+        ])
+        if  MA5 > MA10*g.RSIRate> MA20*g.RSIRate:
+            new_list.append(stock)
+            ma_pass_details[stock] = detail
+        else:
+            ma_removed_details.append(detail)
+
+    log.info('均线过滤[%s]: %d -> %d, 移除=%d' % (
+        caller,
+        len(one_yuan_filtered),
+        len(new_list),
+        len(ma_removed_details)
+    ))
+    _log_detail_items(
+        '均线过滤移除[%s]' % caller,
+        ma_removed_details,
+        limit=min(len(ma_removed_details), g.debug_log_limit),
+        chunk=3
+    )
+    ma_boundary_details = [ma_pass_details[stock] for stock in new_list[:min(len(new_list), g.stocknum + g.debug_boundary_window)]]
+    _log_detail_items(
+        '均线通过前段[%s]' % caller,
+        ma_boundary_details,
+        limit=len(ma_boundary_details),
+        chunk=3
+    )
+
+    return new_list