ZJTJ-SAR指标计算器

基于A股行情数据计算SAR抛物线指标，并用机构资金流向近似替代ZJTJ庄家抬轿指标，实现四维选股策略。

Security Scan

The skill's code and runtime instructions are coherent with its stated purpose (computing SAR and approximating ZJTJ using AkShare); it requests no credentials or unusual system access.

Purpose & Capability

Name/description match the provided instructions and code: the SKILL.md contains Python code to compute SAR, fetch market and fund-flow data via AkShare, and apply a four-dimension screener. Nothing required or requested is unrelated to a stock analysis tool.

Instruction Scope

Instructions import akshare/pandas/numpy and fetch data from AkShare (network calls). This is expected for a market-data tool. The SKILL.md does not instruct reading local secrets or unrelated files. It uses broad try/except blocks (which can hide errors) and hardcoded numeric thresholds — these are design choices, not hostile behavior.

Install Mechanism

This is an instruction-only skill with no install spec. That minimizes install risk, but the code depends on external Python packages (akshare, pandas, numpy) which are not listed in an install section or pinned — the user should ensure these are installed from trusted sources and preferably pinned to specific versions.

Credentials

The skill declares no environment variables, credentials, or config paths and the code does not attempt to read secrets or unrelated system configuration. Network access to AkShare is the only external dependency, which is appropriate for its purpose.

Persistence & Privilege

The skill does not request persistent/always-on privileges (always: false) and does not modify other skills or system-wide configuration. Default autonomous invocation is allowed by platform policy but is not combined with other red flags here.

Assessment

This skill appears internally consistent and implements what it says: SAR calculation plus an approximate ZJTJ signal using AkShare data. Before installing/run it: 1) Ensure akshare, pandas, numpy are installed from trusted sources and pin versions (use a virtualenv). 2) Be aware the code performs network requests to AkShare—verify you are comfortable with that data flow. 3) Review and test the numeric thresholds and try/except usage (they may hide errors or need tuning for your market/data). 4) If you need reproducible results, ask the author to provide an explicit dependency/install spec (requirements.txt) and sample data. 5) Remember this is a screening tool — it makes heuristic approximations and should not be treated as financial advice.

ZJTJ + SAR 指标计算工具

本工具通过Python计算SAR指标，并用机构资金流向近似替代ZJTJ，帮助实现四维选股策略。

核心功能

1. SAR指标计算

SAR（抛物线转向指标）计算逻辑：

def calculate_sar(high_prices, low_prices, close_prices, af_start=0.02, af_increment=0.02, af_max=0.2):
    """
    计算SAR指标
    
    参数:
    - high_prices: 最高价列表
    - low_prices: 最低价列表
    - close_prices: 收盘价列表
    - af_start: 初始加速因子 (默认0.02)
    - af_increment: 加速因子增量 (默认0.02)
    - af_max: 最大加速因子 (默认0.2)
    
    返回:
    - sar_values: SAR值列表
    - trend: 趋势方向 (1=上涨, -1=下跌)
    """
    n = len(high_prices)
    if n < 2:
        return [], 0
    
    # 初始化
    sar = [low_prices[0]]
    trend = 1  # 假设初始为上涨
    af = af_start
    ep = high_prices[0]  # 极值点
    
    for i in range(1, n):
        if trend == 1:  # 上涨趋势
            sar_val = sar[-1] + af * (ep - sar[-1])
            
            if low_prices[i] < sar_val:  # 趋势反转
                trend = -1
                sar.append(low_prices[i])
                ep = low_prices[i]
                af = af_start
            else:
                sar.append(sar_val)
                if high_prices[i] > ep:
                    ep = high_prices[i]
                    af = min(af + af_increment, af_max)
        else:  # 下跌趋势
            sar_val = sar[-1] + af * (ep - sar[-1])
            
            if high_prices[i] > sar_val:  # 趋势反转
                trend = 1
                sar.append(high_prices[i])
                ep = high_prices[i]
                af = af_start
            else:
                sar.append(sar_val)
                if low_prices[i] < ep:
                    ep = low_prices[i]
                    af = min(af + af_increment, af_max)
    
    return sar, trend

2. ZJTJ近似替代方案

由于ZJTJ是通达信付费指标，用以下免费数据近似：

替代指标	数据来源	说明
机构资金净流入	AkShare stock_individual_fund_flow	大单/超大单净流入
股东人数变化	股东人数数据	股东减少=筹码集中
户均持股	股东数据	户均持股增加=控盘增强
持仓机构数	机构持股数据	机构越多越靠谱

3. 综合选股函数

import akshare as ak
import pandas as pd
import numpy as np

def get_stock_data(stock_code, days=60):
    """获取个股K线数据"""
    df = ak.stock_zh_a_hist(
        symbol=stock_code,
        period="daily",
        start_date=(pd.Timestamp.now() - pd.Timedelta(days=days)).strftime("%Y%m%d"),
        end_date=pd.Timestamp.now().strftime("%Y%m%d"),
        adjust="qfq"
    )
    return df

def calculate_zjtj_signal(stock_code):
    """
    计算ZJTJ近似信号
    返回: 信号强度 (0-100), 信号颜色
    """
    try:
        # 获取资金流向数据
        fund_flow = ak.stock_individual_fund_flow(stock=stock_code, market="sh")
        
        # 计算大单净流入占比
        if len(fund_flow) > 0:
            net_inflow = fund_flow.iloc[-1].get('大单净流入', 0)
            # 简化逻辑：净流入>0说明有主力关注
            if net_inflow > 100000000:  # 1亿+
                return 80, "紫色"  # 高度控盘
            elif net_inflow > 50000000:  # 5000万+
                return 60, "红色"  # 有庄
            elif net_inflow > 10000000:  # 1000万+
                return 30, "黄色"  # 开始控盘
            else:
                return 0, "白色"  # 无庄
    except:
        return 0, "白色"

def analyze_stock(stock_code):
    """
    综合分析一只股票
    返回: 选股建议
    """
    # 获取数据
    df = get_stock_data(stock_code)
    if df is None or len(df) < 30:
        return None
    
    # 计算SAR
    highs = df['最高'].values
    lows = df['最低'].values
    closes = df['收盘'].values
    
    sar_values, trend = calculate_sar(highs, lows, closes)
    
    # 获取ZJTJ近似信号
    zjtj_score, zjtj_color = calculate_zjtj_signal(stock_code)
    
    # 获取成交量
    volume_today = df.iloc[-1]['成交量']
    volume_yesterday = df.iloc[-2]['成交量'] if len(df) > 1 else volume_today
    volume_ratio = volume_today / volume_yesterday if volume_yesterday > 0 else 1
    
    # 整理结果
    result = {
        'code': stock_code,
        'sar_trend': '上涨' if trend == 1 else '下跌',
        'sar_value': sar_values[-1] if sar_values else None,
        'price_above_sar': closes[-1] > sar_values[-1] if sar_values else False,
        'zjtj_signal': zjtj_color,
        'zjtj_score': zjtj_score,
        'volume_ratio': volume_ratio,
        'volume_increasing': volume_ratio > 1.3,
    }
    
    # 判断是否符合四维选股条件
    conditions = []
    if zjtj_color in ['黄色', '红色', '紫色']:
        conditions.append("✅ ZJTJ有庄")
    if trend == 1:
        conditions.append("✅ SAR上涨趋势")
    if volume_ratio > 1.3:
        conditions.append("✅ 成交量放量")
    
    result['conditions'] = conditions
    result['recommend'] = len(conditions) >= 2
    
    return result

def batch_screener(stock_list):
    """
    批量选股
    stock_list: 股票代码列表
    """
    results = []
    for code in stock_list:
        try:
            result = analyze_stock(code)
            if result and result['recommend']:
                results.append(result)
        except Exception as e:
            print(f"Error processing {code}: {e}")
    
    # 按ZJTJ分数排序
    results.sort(key=lambda x: x['zjtj_score'], reverse=True)
    return results

使用示例

单只股票分析

# 分析一只股票
result = analyze_stock("000001")
print(f"股票: {result['code']}")
print(f"SAR趋势: {result['sar_trend']}")
print(f"价格在SAR上方: {result['price_above_sar']}")
print(f"ZJTJ信号: {result['zjtj_signal']}")
print(f"成交量放大: {result['volume_increasing']}")
print(f"选股条件: {result['conditions']}")
print(f"推荐买入: {result['recommend']}")

批量选股

# 热门股票列表
stocks = ["000001", "600519", "300750", "002594", "600036"]

# 批量筛选
candidates = batch_screener(stocks)

# 打印结果
for stock in candidates:
    print(f"{stock['code']}: ZJTJ={stock['zjtj_signal']}, SAR={stock['sar_trend']}, 放量={stock['volume_increasing']}")

四维选股判断逻辑

维度	条件	得分
ZJTJ	黄色/红色/紫色	+30
SAR	上涨趋势 + 价格在SAR上方	+30
成交量	今日量/昨日量 > 1.3	+20
市场情绪	涨停20-80家	+20

总分 >= 60分 → 建议买入

注意事项

1. 数据来源：AkShare（免费API），可能不稳定
2. ZJTJ为近似替代，与通达信原版有差异
3. SAR计算参数可调整（af_start, af_max等）
4. 建议结合其他分析方法综合判断

依赖安装

pip install akshare pandas numpy

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触发场景

• "计算SAR指标"
• "ZJTJ指标"
• "四维选股"
• "帮我分析股票"