{ "cells": [ { "cell_type": "markdown", "id": "c46a0b87", "metadata": { "papermill": { "duration": 0.001108, "end_time": "2026-10-29T21:45:23.714051+00:00", "exception": false, "start_time": "2026-10-29T21:45:23.712943+00:00", "status": "completed" }, "tags": [] }, "source": [ "# 찌짐이 방지 — 저점매수 / 매수금지 점수\n", "\n", "**용도**: 관심 종목별 저점매수(매도금지) 점수와 과열 매수금지 점수를 비교합니다.\n", "**종목 리스트**: `bottom_tickers.json` (웹 UI '🧾 저점 종목' 버튼으로 편집)\n" ] }, { "cell_type": "code", "execution_count": 1, "id": "470e6ba9", "metadata": { "execution": { "iopub.execute_input": "2026-10-29T21:45:23.715961Z", "iopub.status.busy": "2026-10-29T21:45:23.715867Z", "iopub.status.idle": "2026-10-29T21:45:23.747547Z", "shell.execute_reply": "2026-10-29T21:45:23.747203Z" }, "papermill": { "duration": 0.033242, "end_time": "2026-10-29T21:45:23.747977+00:00", "exception": false, "start_time": "2026-10-29T21:45:23.714735+00:00", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[CONFIG] /Users/loonshots/룬샤시_공시정리/태버지/bottom_tickers.json\n" ] } ], "source": [ "import json, sys\n", "from pathlib import Path\n", "\n", "TICKERS_FILE = Path('/Users/loonshots/룬샤시_공시정리/태버지/bottom_tickers.json')\n", "DEFAULT_GROUPS = {\n", " '지수': [\n", " {'ticker': '^KS11', 'name': 'KOSPI'},\n", " {'ticker': '^KQ11', 'name': 'KOSDAQ'},\n", " ],\n", " '국장': [\n", " {'ticker': '005930', 'name': '삼성전자'},\n", " {'ticker': '000660', 'name': 'SK하이닉스'},\n", " {'ticker': '009150', 'name': '삼성전기'},\n", " ],\n", " '해외': [],\n", "}\n", "\n", "sys.path.insert(0, '/Users/loonshots/projects/predict/OHLCV 기반')\n", "try:\n", " from stock_map import resolve_stock, code_to_name\n", "except Exception:\n", " resolve_stock = None\n", " def code_to_name(code):\n", " return code\n", "\n", "print(f'[CONFIG] {TICKERS_FILE}')\n" ] }, { "cell_type": "code", "execution_count": 2, "id": "be32c9ec", "metadata": { "execution": { "iopub.execute_input": "2026-10-29T21:45:23.749783Z", "iopub.status.busy": "2026-10-29T21:45:23.749717Z", "iopub.status.idle": "2026-10-29T21:45:24.202275Z", "shell.execute_reply": "2026-10-29T21:45:24.201982Z" }, "papermill": { "duration": 0.454158, "end_time": "2026-10-29T21:45:24.202925+00:00", "exception": false, "start_time": "2026-10-29T21:45:23.748767+00:00", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "분석 종목:\n" ] }, { "data": { "text/html": [ "
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groupnameticker
0지수KOSPI^KS11
1지수KOSDAQ^KQ11
2국장삼성전자005930
3국장SK하이닉스000660
4국장삼성전기009150
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" ], "text/plain": [ " group name ticker\n", "0 지수 KOSPI ^KS11\n", "1 지수 KOSDAQ ^KQ11\n", "2 국장 삼성전자 005930\n", "3 국장 SK하이닉스 000660\n", "4 국장 삼성전기 009150" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import yfinance as yf\n", "import pandas as pd\n", "import numpy as np\n", "from IPython.display import display\n", "\n", "pd.set_option('display.max_columns', None)\n", "pd.set_option('display.width', 200)\n", "\n", "def load_ticker_groups():\n", " if not TICKERS_FILE.exists():\n", " return DEFAULT_GROUPS\n", " try:\n", " data = json.loads(TICKERS_FILE.read_text(encoding='utf-8'))\n", " return data if isinstance(data, dict) else DEFAULT_GROUPS\n", " except Exception as exc:\n", " print(f'[WARN] bottom_tickers.json 로드 실패: {exc}')\n", " return DEFAULT_GROUPS\n", "\n", "def normalize_entry(entry, group_name=''):\n", " if isinstance(entry, str):\n", " ticker, name = entry.strip(), entry.strip()\n", " elif isinstance(entry, dict):\n", " ticker = str(entry.get('ticker') or '').strip()\n", " name = str(entry.get('name') or '').strip()\n", " else:\n", " return None\n", " if not ticker:\n", " return None\n", "\n", " upper = ticker.upper()\n", " raw_code = upper[:-3] if upper.endswith(('.KS', '.KQ')) else upper\n", " if raw_code.isdigit() and len(raw_code) == 6:\n", " return {'input': ticker, 'ticker': raw_code, 'name': name or code_to_name(raw_code), 'group': group_name}\n", " if resolve_stock and not upper.startswith('^') and not ticker.isascii():\n", " code = resolve_stock(ticker)\n", " if code:\n", " return {'input': ticker, 'ticker': code, 'name': name or code_to_name(code), 'group': group_name}\n", " return {'input': ticker, 'ticker': upper, 'name': name or upper, 'group': group_name}\n", "\n", "def flatten_ticker_groups(groups):\n", " entries = []\n", " seen = set()\n", " for group_name, items in groups.items():\n", " if not isinstance(items, list):\n", " continue\n", " for item in items:\n", " entry = normalize_entry(item, group_name)\n", " if not entry:\n", " continue\n", " key = entry['ticker'].upper()\n", " if key in seen:\n", " continue\n", " seen.add(key)\n", " entries.append(entry)\n", " return entries\n", "\n", "def yahoo_candidates(entry):\n", " ticker = entry['ticker'].strip().upper()\n", " if ticker.startswith('^'):\n", " return [ticker]\n", " if ticker.endswith(('.KS', '.KQ')):\n", " code, suffix = ticker[:-3], ticker[-3:]\n", " other = '.KQ' if suffix == '.KS' else '.KS'\n", " return [ticker, code + other]\n", " if ticker.isdigit() and len(ticker) == 6:\n", " return [ticker + '.KS', ticker + '.KQ']\n", " return [ticker]\n", "\n", "ticker_groups = load_ticker_groups()\n", "ticker_entries = flatten_ticker_groups(ticker_groups)\n", "print('분석 종목:')\n", "display(pd.DataFrame(ticker_entries)[['group', 'name', 'ticker']] if ticker_entries else pd.DataFrame(columns=['group', 'name', 'ticker']))\n" ] }, { "cell_type": "code", "execution_count": 3, "id": "31b866a1", "metadata": { "execution": { "iopub.execute_input": "2026-10-29T21:45:24.205016Z", "iopub.status.busy": "2026-10-29T21:45:24.204909Z", "iopub.status.idle": "2026-10-29T21:45:24.208864Z", "shell.execute_reply": "2026-10-29T21:45:24.208477Z" }, "papermill": { "duration": 0.005435, "end_time": "2026-10-29T21:45:24.209252+00:00", "exception": false, "start_time": "2026-10-29T21:45:24.203817+00:00", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "def percentile_score(value, history, lower_is_better=True):\n", " history = history.dropna()\n", " if len(history) == 0:\n", " return np.nan\n", " rank = (history < value).mean() * 100\n", " return 100 - rank if lower_is_better else rank\n", "\n", "def atr(df, period=14):\n", " tr = pd.concat([\n", " df['High'] - df['Low'],\n", " (df['High'] - df['Close'].shift()).abs(),\n", " (df['Low'] - df['Close'].shift()).abs()\n", " ], axis=1).max(axis=1)\n", " return tr.rolling(period).mean()" ] }, { "cell_type": "code", "execution_count": 4, "id": "13bdcb1a", "metadata": { "execution": { "iopub.execute_input": "2026-10-29T21:45:24.211407Z", "iopub.status.busy": "2026-10-29T21:45:24.211350Z", "iopub.status.idle": "2026-10-29T21:45:24.218811Z", "shell.execute_reply": "2026-10-29T21:45:24.218398Z" }, "papermill": { "duration": 0.009142, "end_time": "2026-10-29T21:45:24.219264+00:00", "exception": false, "start_time": "2026-10-29T21:45:24.210122+00:00", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "def download_first_available(entry):\n", " last_error = None\n", " for yahoo_ticker in yahoo_candidates(entry):\n", " try:\n", " df = yf.download(yahoo_ticker, period='1y', auto_adjust=True, progress=False)\n", " if df is not None and not df.empty:\n", " return yahoo_ticker, df\n", " except Exception as exc:\n", " last_error = exc\n", " if last_error:\n", " raise last_error\n", " return None, pd.DataFrame()\n", "\n", "def analyze_ticker(entry):\n", " yahoo_ticker, df = download_first_available(entry)\n", " if df.empty:\n", " return None\n", " if isinstance(df.columns, pd.MultiIndex):\n", " df.columns = df.columns.get_level_values(0)\n", " df['MA5'] = df['Close'].rolling(5).mean()\n", " df['MA30'] = df['Close'].rolling(30).mean()\n", " df['MA50'] = df['Close'].rolling(50).mean()\n", " df['DIS30'] = df['Close'] / df['MA30'] * 100\n", " df['DIS50'] = df['Close'] / df['MA50'] * 100\n", " df['ATR14'] = atr(df)\n", " df['HIGH120'] = df['Close'].rolling(120).max()\n", " df['DROP_FROM_120H_PCT'] = (df['Close'] / df['HIGH120'] - 1) * 100\n", " df['DOWN_ATR30'] = (df['Close'] - df['MA30']) / df['ATR14']\n", " df['VOL_MA5'] = df['Volume'].rolling(5).mean()\n", " df['VOL_MA20'] = df['Volume'].rolling(20).mean()\n", " df['VOL_RATIO'] = df['Volume'] / df['VOL_MA20']\n", " df['RET3'] = df['Close'].pct_change(3)\n", " df['DAY_RETURN'] = (df['Close'] - df['Open']) / df['Open']\n", " df = df.dropna()\n", " if df.empty:\n", " return None\n", " latest = df.iloc[-1]\n", "\n", " # 1. 저점매수(=매도금지) 점수\n", " score_dis30 = percentile_score(latest['DIS30'], df['DIS30'], True) * 0.30\n", " score_dis50 = percentile_score(latest['DIS50'], df['DIS50'], True) * 0.20\n", " score_high120 = percentile_score(latest['DROP_FROM_120H_PCT'], df['DROP_FROM_120H_PCT'], True) * 0.20\n", " score_down_atr30 = percentile_score(latest['DOWN_ATR30'], df['DOWN_ATR30'], True) * 0.10\n", " score_vol_dry = 10 if latest['VOL_MA5'] < latest['VOL_MA20'] else 0\n", " score_vol_rebound = 10 if (latest['Volume'] > latest['VOL_MA5'] and latest['Volume'] > df['Volume'].shift(1).iloc[-1]) else 0\n", " bottom_score = min(score_dis30 + score_dis50 + score_high120 + score_down_atr30 + score_vol_dry + score_vol_rebound, 100)\n", "\n", " # 2. 매수금지(과열) 점수\n", " buy_stop_score = 0\n", " if latest['DIS30'] > df['DIS30'].quantile(0.95): buy_stop_score += 25\n", " elif latest['DIS30'] > df['DIS30'].quantile(0.90): buy_stop_score += 20\n", " elif latest['DIS30'] > df['DIS30'].quantile(0.80): buy_stop_score += 10\n", " if latest['DIS50'] > df['DIS50'].quantile(0.95): buy_stop_score += 15\n", " elif latest['DIS50'] > df['DIS50'].quantile(0.90): buy_stop_score += 10\n", " elif latest['DIS50'] > df['DIS50'].quantile(0.80): buy_stop_score += 5\n", " if latest['DOWN_ATR30'] > 3: buy_stop_score += 20\n", " elif latest['DOWN_ATR30'] > 2: buy_stop_score += 15\n", " elif latest['DOWN_ATR30'] > 1: buy_stop_score += 10\n", " if latest['RET3'] > 0.10: buy_stop_score += 15\n", " elif latest['RET3'] > 0.07: buy_stop_score += 10\n", " elif latest['RET3'] > 0.05: buy_stop_score += 5\n", " if latest['VOL_RATIO'] > 2.5: buy_stop_score += 15\n", " elif latest['VOL_RATIO'] > 2.0: buy_stop_score += 10\n", " elif latest['VOL_RATIO'] > 1.5: buy_stop_score += 5\n", " if latest['DAY_RETURN'] > 0.05: buy_stop_score += 10\n", " elif latest['DAY_RETURN'] > 0.03: buy_stop_score += 7\n", " elif latest['DAY_RETURN'] > 0.02: buy_stop_score += 5\n", " buy_stop_score = min(buy_stop_score, 100)\n", "\n", " if bottom_score >= 80: bottom_signal = '저점매수 후보 / 비중축소 금지'\n", " elif bottom_score >= 65: bottom_signal = '매도 보류 / 분할매수 관심'\n", " elif bottom_score >= 50: bottom_signal = '절반만 축소 / 관찰'\n", " else: bottom_signal = '기존 원칙 적용'\n", " if buy_stop_score >= 80: buy_signal = '신규매수 금지'\n", " elif buy_stop_score >= 65: buy_signal = '추격매수 자제'\n", " elif buy_stop_score >= 50: buy_signal = '일부만 매수'\n", " else: buy_signal = '과열 아님'\n", "\n", " return {\n", " '그룹': entry.get('group', ''), '종목': entry['name'], '입력': entry['input'], 'Yahoo티커': yahoo_ticker,\n", " '현재가': round(latest['Close'], 2),\n", " '30일이격도': round(latest['DIS30'], 2), '50일이격도': round(latest['DIS50'], 2),\n", " '120일고점대비(%)': round(latest['DROP_FROM_120H_PCT'], 2),\n", " '30일선대비ATR': round(latest['DOWN_ATR30'], 2),\n", " '3일수익률(%)': round(latest['RET3'] * 100, 2),\n", " '당일수익률(%)': round(latest['DAY_RETURN'] * 100, 2),\n", " '거래량비율': round(latest['VOL_RATIO'], 2),\n", " '거래량감소': bool(latest['VOL_MA5'] < latest['VOL_MA20']),\n", " '거래량재증가': bool(latest['Volume'] > latest['VOL_MA5']),\n", " '저점매수점수': round(bottom_score, 1), '매도금지점수': round(bottom_score, 1),\n", " '매수금지점수': round(buy_stop_score, 1),\n", " '판단': bottom_signal, '매수판단': buy_signal,\n", " }\n" ] }, { "cell_type": "code", "execution_count": 5, "id": "1587729a", "metadata": { "execution": { "iopub.execute_input": "2026-10-29T21:45:24.221322Z", "iopub.status.busy": "2026-10-29T21:45:24.221255Z", "iopub.status.idle": "2026-10-29T21:45:26.891666Z", "shell.execute_reply": "2026-10-29T21:45:26.890951Z" }, "papermill": { "duration": 2.672514, "end_time": "2026-10-29T21:45:26.892537+00:00", "exception": false, "start_time": "2026-10-29T21:45:24.220023+00:00", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
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그룹종목입력Yahoo티커현재가30일이격도50일이격도120일고점대비(%)30일선대비ATR3일수익률(%)당일수익률(%)거래량비율거래량감소거래량재증가저점매수점수매도금지점수매수금지점수판단매수판단
0국장삼성전자005930005930.KS232000.0094.0891.67-35.93-0.958.92-3.731.39TrueTrue80.480.410저점매수 후보 / 비중축소 금지과열 아님
1지수KOSPI^KS11^KS116012.4494.1891.69-34.03-1.288.334.310.85TrueTrue80.280.217저점매수 후보 / 비중축소 금지과열 아님
2지수KOSDAQ^KQ11^KQ11771.2893.7693.57-36.45-1.412.611.901.05TrueTrue72.472.40매도 보류 / 분할매수 관심과열 아님
3국장삼성전기009150009150.KS1293000.0094.7693.81-43.04-0.6815.65-1.301.56FalseTrue68.568.520매도 보류 / 분할매수 관심과열 아님
4국장SK하이닉스000660000660.KS1526000.0096.5893.77-47.71-0.5019.690.991.27FalseTrue64.864.815절반만 축소 / 관찰과열 아님
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" ], "text/plain": [ " 그룹 종목 입력 Yahoo티커 현재가 30일이격도 50일이격도 120일고점대비(%) 30일선대비ATR 3일수익률(%) 당일수익률(%) 거래량비율 거래량감소 거래량재증가 저점매수점수 매도금지점수 매수금지점수 판단 매수판단\n", "0 국장 삼성전자 005930 005930.KS 232000.00 94.08 91.67 -35.93 -0.95 8.92 -3.73 1.39 True True 80.4 80.4 10 저점매수 후보 / 비중축소 금지 과열 아님\n", "1 지수 KOSPI ^KS11 ^KS11 6012.44 94.18 91.69 -34.03 -1.28 8.33 4.31 0.85 True True 80.2 80.2 17 저점매수 후보 / 비중축소 금지 과열 아님\n", "2 지수 KOSDAQ ^KQ11 ^KQ11 771.28 93.76 93.57 -36.45 -1.41 2.61 1.90 1.05 True True 72.4 72.4 0 매도 보류 / 분할매수 관심 과열 아님\n", "3 국장 삼성전기 009150 009150.KS 1293000.00 94.76 93.81 -43.04 -0.68 15.65 -1.30 1.56 False True 68.5 68.5 20 매도 보류 / 분할매수 관심 과열 아님\n", "4 국장 SK하이닉스 000660 000660.KS 1526000.00 96.58 93.77 -47.71 -0.50 19.69 0.99 1.27 False True 64.8 64.8 15 절반만 축소 / 관찰 과열 아님" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "results = []\n", "for entry in ticker_entries:\n", " try:\n", " r = analyze_ticker(entry)\n", " if r:\n", " results.append(r)\n", " else:\n", " print(f\"{entry['name']} ({entry['ticker']}) 데이터 없음\")\n", " except Exception as e:\n", " print(f\"{entry['name']} ({entry['ticker']}) 오류: {e}\")\n", "\n", "result_df = pd.DataFrame(results)\n", "if not result_df.empty:\n", " result_df = result_df.sort_values(['저점매수점수','매수금지점수'], ascending=[False, True]).reset_index(drop=True)\n", " display(result_df)\n", "else:\n", " print('결과 없음 — 티커/네트워크 확인')\n" ] } ], "metadata": { "kernelspec": { "display_name": ".venv", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.13" }, "papermill": { "default_parameters": {}, "duration": 4.216117, "end_time": "2026-10-29T21:45:27.111954+00:00", "environment_variables": {}, "exception": null, "input_path": "/Users/seog-yejun/룬샤시_공시정리/태버지/10. 찌짐이 방지 (저점매수·매수금지 점수).ipynb", "output_path": "/Users/seog-yejun/룬샤시_공시정리/태버지/10. 찌짐이 방지 (저점매수·매수금지 점수).ipynb", "parameters": {}, "start_time": "2026-10-29T21:45:22.895837+00:00", "version": "2.7.0" } }, "nbformat": 4, "nbformat_minor": 5 }