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dsyoon
2025-08-06 14:39:43 +09:00
parent 872cf788dd
commit f7870381bf
6 changed files with 362 additions and 380 deletions
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420
stock_monitor.py
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@@ -1,7 +1,6 @@
import pandas as pd
from HTS2 import HTS
import pandas as pd
from dateutil.relativedelta import relativedelta
from datetime import datetime, timedelta
import telegram
import time
@@ -12,9 +11,11 @@ from multiprocessing import Pool
import schedule
from config import *
import FinanceDataReader as fdr
import numpy as np
hts = HTS()
BUY_AMOUNT = 100000
BUY_AMOUNT = 10000
def send_coin_msg(text):
coin_client = telegram.Bot(token=COIN_TELEGRAM_BOT_TOKEN)
@@ -38,10 +39,11 @@ def send_coin_telegram_message(message_list, header):
return
def buy_ticker(buy_ticker_list):
for buy_ticker in buy_ticker_list:
ticker_code = buy_ticker['symbol']
_ = hts.buyCoinMarket(ticker_code, BUY_AMOUNT)
def buy_ticker(symbole):
try:
_ = hts.buyCoinMarket(symbole, BUY_AMOUNT)
except Exception as e:
print(f"Error buying {symbole}: {str(e)}")
return
@@ -69,232 +71,101 @@ def send_stock_telegram_message(message_list, header):
return
def calculate_bollinger_bands(data):
data['MA'] = data['Close'].rolling(window=BOLLINGER_PERIOD).mean()
data['STD'] = data['Close'].rolling(window=BOLLINGER_PERIOD).std()
data['Upper'] = data['MA'] + (BOLLINGER_STD * data['STD'])
data['Lower'] = data['MA'] - (BOLLINGER_STD * data['STD'])
return data
def normalize_data(data):
"""데이터 정규화 함수 - 모든 코인에 동일하게 적용"""
# Min-Max 정규화를 위한 컬럼
columns_to_normalize = ['Open', 'High', 'Low', 'Close', 'Volume']
normalized_data = data.copy()
# 각 컬럼별 정규화 (20일 롤링 윈도우 사용)
for column in columns_to_normalize:
min_val = data[column].rolling(window=20).min()
max_val = data[column].rolling(window=20).max()
# 0으로 나누기 방지
denominator = max_val - min_val
normalized_data[f'{column}_Norm'] = np.where(
denominator != 0,
(data[column] - min_val) / denominator,
0.5 # 기본값 설정
)
return normalized_data
def calculate_technical_indicators(data):
# 볼린저 밴드 계산
data = calculate_bollinger_bands(data)
# RSI 계산 (14일 기준)
delta = data['Close'].diff()
gain = (delta.where(delta > 0, 0)).rolling(window=14).mean()
loss = (-delta.where(delta < 0, 0)).rolling(window=14).mean()
rs = gain / loss
data['RSI'] = 100 - (100 / (1 + rs))
# MACD 계산
exp1 = data['Close'].ewm(span=12, adjust=False).mean()
exp2 = data['Close'].ewm(span=26, adjust=False).mean()
data['MACD'] = exp1 - exp2
data['Signal'] = data['MACD'].ewm(span=9, adjust=False).mean()
data['MACD_Hist'] = data['MACD'] - data['Signal']
# 이동평균선
"""기술적 지표 계산 - 모든 코인에 동일하게 적용"""
# 데이터 정규화
data = normalize_data(data)
# 이동평균선 계산
data['MA5'] = data['Close'].rolling(window=5).mean()
data['MA20'] = data['Close'].rolling(window=20).mean()
data['MA40'] = data['Close'].rolling(window=40).mean()
data['MA60'] = data['Close'].rolling(window=60).mean()
data['MA120'] = data['Close'].rolling(window=120).mean()
data['MA200'] = data['Close'].rolling(window=200).mean()
data['MA240'] = data['Close'].rolling(window=240).mean()
data['MA720'] = data['Close'].rolling(window=720).mean()
data['MA1440'] = data['Close'].rolling(window=1440).mean()
# 거래량 이동평균
data['Volume_MA5'] = data['Volume'].rolling(window=5).mean()
# 매수 타이밍을 이동평균선으로 결정
# 골든크로스: 단기 이동평균선이 장기 이동평균선을 상향 돌파할 때 매수
data['golden_cross'] = (data['MA5'] > data['MA20']) & (data['MA5'].shift(1) <= data['MA20'].shift(1))
# 볼린저 밴드 계산
data['MA'] = data['Close'].rolling(window=20).mean()
data['STD'] = data['Close'].rolling(window=20).std()
data['Upper'] = data['MA'] + (2 * data['STD'])
data['Lower'] = data['MA'] - (2 * data['STD'])
return data
def check_buy_signals(symbol, data):
if len(data) < 60: # 최소 60일치 데이터 필요
return None
def check_buy_point(data, simulation=None):
latest = data.iloc[-1]
prev = data.iloc[-2]
# 8월 3일 이후의 데이터만 고려
if latest.name <= pd.Timestamp('2025-08-03'):
return None
# 볼린저 밴드 신호
bb_signal = False
if isinstance(latest['Upper'], float):
upper_band = latest['Upper']
lower_band = latest['Lower']
current_price = latest['Close']
# 매수 포인트 탐지 및 표시
if simulation:
recent_data = data
else:
upper_band = latest['Upper'].iloc[0]
lower_band = latest['Lower'].iloc[0]
current_price = latest['Close'].iloc[0]
recent_data = data.tail(10)
distance = (current_price - lower_band) / (upper_band - lower_band)
bb_signal = distance < BOLLINGER_THRESHOLD
recent_data['buy_point'] = 0
for i in range(1, len(recent_data)):
if all(recent_data[f'MA{n}'].iloc[i] < recent_data['MA720'].iloc[i] for n in [5, 20, 40, 120, 200, 240]) and \
all(recent_data[f'MA{n}'].iloc[i] > recent_data[f'MA{n}'].iloc[i-1] for n in [5, 20, 40, 120, 200, 240]) and \
recent_data['MA720'].iloc[i] < recent_data['MA1440'].iloc[i]:
recent_data.at[recent_data.index[i], 'buy_point'] = 1
# U자 반등 후 이전 고점 돌파 여부 계산 (BREAKOUT)
breakout_signal = False
if len(data) >= max(BREAKOUT_LOOKBACK, BREAKOUT_WEEK_LOOKBACK) + 1:
# ① U자 형태 확인
window_close = data['Close'].iloc[-BREAKOUT_LOOKBACK - 1:-1]
prev_high = window_close.max()
prev_low = window_close.min()
if not simulation:
if recent_data['buy_point'][-10:-1].sum() > 0:
recent_data['buy_point'][-1] = 1
# ② 1주일(42캔들) 전 가격 대비 5% 이상 상승하지 않았는지 체크
price_week_ago = data['Close'].iloc[-BREAKOUT_WEEK_LOOKBACK - 1]
if price_week_ago > 0:
week_change = (current_price - price_week_ago) / price_week_ago
else:
week_change = 1 # 값이 0이면 조건 불충족 처리
return recent_data
# ③ 조건 종합: U자+돌파 && 주간 상승률 ≤ 5%
if (
prev_high > 0 and (prev_high - prev_low) / prev_high > BUY_THRESHOLD and current_price > prev_high
and week_change <= BREAKOUT_WEEK_LIMIT
):
breakout_signal = True
# 장기간 저항선 돌파 여부 계산 (LONG RESISTANCE BREAKOUT)
long_breakout_signal = False
if len(data) >= RESISTANCE_LOOKBACK + 1:
resistance_level = data['Close'].iloc[-RESISTANCE_LOOKBACK - 1:-1].max()
previous_closes = data['Close'].iloc[-RESISTANCE_LOOKBACK - 1:-1]
# 과거 구간에서 저항선 이상으로 종가가 한번도 올라가지 않은 경우 + 현재 가격이 저항선 돌파
if (previous_closes <= resistance_level * (1 + RESISTANCE_BREAK_THRESHOLD)).all() and \
current_price > resistance_level * (1 + RESISTANCE_BREAK_THRESHOLD):
long_breakout_signal = True
# RSI 과매도 신호 (RSI < 30)
if not isinstance(latest['Upper'], float):
rsi_signal = latest['RSI'].iloc[0] < 30
# MACD 신호 (MACD가 시그널 라인을 상향 돌파)
macd_signal = (prev['MACD'].iloc[0] < prev['Signal'].iloc[0]) and (
latest['MACD'].iloc[0] > latest['Signal'].iloc[0])
# 이동평균선 골든크로스 임박 또는 발생
ma_signal = (prev['MA5'].iloc[0] < prev['MA20'].iloc[0]) and (latest['MA5'].iloc[0] >= latest['MA20'].iloc[0])
# 거래량 증가 신호 (5일 평균 대비 150% 이상)
volume_signal = latest['Volume'].iloc[0] > (latest['Volume_MA5'].iloc[0] * 1.5)
# 종합 신호
buy_signals = {
'bb_signal': bb_signal,
'rsi_signal': rsi_signal,
'macd_signal': macd_signal,
'ma_signal': ma_signal,
'volume_signal': volume_signal,
'breakout_signal': breakout_signal,
'long_breakout_signal': long_breakout_signal
}
# 최소 3개 이상의 신호가 동시에 발생할 때 매수 신호로 간주
signal_count = sum(1 for signal in buy_signals.values() if signal)
return {
'symbol': symbol,
'price': current_price,
'lower_band': lower_band,
'distance': distance,
'rsi': latest['RSI'].iloc[0],
'macd': latest['MACD'].iloc[0],
'signal_line': latest['Signal'].iloc[0],
'buy_signals': buy_signals,
'signal_count': signal_count,
'buy': long_breakout_signal or breakout_signal or (
(bb_signal and rsi_signal) or (signal_count >= 2 and (bb_signal or rsi_signal)))
}
else:
rsi_signal = latest['RSI'] < 30
# MACD 신호 (MACD가 시그널 라인을 상향 돌파)
macd_signal = (prev['MACD'] < prev['Signal']) and (latest['MACD'] > latest['Signal'])
# 이동평균선 골든크로스 임박 또는 발생
ma_signal = (prev['MA5'] < prev['MA20']) and (latest['MA5'] >= latest['MA20'])
# 거래량 증가 신호 (5일 평균 대비 150% 이상)
volume_signal = latest['Volume'] > (latest['Volume_MA5'] * 1.5)
# 종합 신호
buy_signals = {
'bb_signal': bb_signal,
'rsi_signal': rsi_signal,
'macd_signal': macd_signal,
'ma_signal': ma_signal,
'volume_signal': volume_signal,
'breakout_signal': breakout_signal,
'long_breakout_signal': long_breakout_signal
}
# 최소 3개 이상의 신호가 동시에 발생할 때 매수 신호로 간주
signal_count = sum(1 for signal in buy_signals.values() if signal)
return {
'symbol': symbol,
'price': current_price,
'lower_band': lower_band,
'distance': distance,
'rsi': latest['RSI'],
'macd': latest['MACD'],
'signal_line': latest['Signal'],
'buy_signals': buy_signals,
'signal_count': signal_count,
'buy': long_breakout_signal or breakout_signal or (
(bb_signal and rsi_signal) or (signal_count >= 2 and (bb_signal or rsi_signal)))
}
def format_message(info, market_type):
message = ""
if info['buy']:
message += '🛒 '
message += f"[{market_type}] {info['name']} ({info['symbol']}) "
message += f"현재가: {'$' if market_type == 'US' else '₩'}{info['price']:.2f}, "
# 매수 신호 상세 정보
count = 0
if any(info['buy_signals'].values()):
message += "📊신호 ({count}):"
if info['buy_signals']['bb_signal']:
message += "- 볼린저 밴드 하단 근접 (근접도: {:.1f}%),".format(info['distance'] * 100)
count += 1
if info['buy_signals']['rsi_signal']:
message += f"- RSI 과매도 구간 (RSI: {info['rsi']:.1f}),"
count += 1
if info['buy_signals']['macd_signal']:
message += "- MACD 골든크로스,"
count += 1
if info['buy_signals']['ma_signal']:
message += "- 이동평균선 골든크로스,"
count += 1
if info['buy_signals']['volume_signal']:
message += "- 거래량 급증"
count += 1
if info['buy_signals'].get('breakout_signal'):
message += "- U자 반등 돌파"
count += 1
if info['buy_signals'].get('long_breakout_signal'):
message += "- 장기 저항 돌파"
count += 1
message += "\n"
message = message.replace("{count}", str(count))
def format_message(market_type, symbol, symbol_name, close):
message = f"매수 [{market_type}] {symbol_name} ({symbol}) "
message += f"현재가: {'$' if market_type == 'US' else '₩'}{close:.2f}, "
return message
def format_ma_message(info, market_type):
"""MA 알림 메시지 생성"""
prefix = '📈 ' if info.get('alert') else ''
prefix = '상승 ' if info.get('alert') else ''
message = prefix + f"[{market_type}] {info['name']} ({info['symbol']}) "
message += f"현재가: {'$' if market_type == 'US' else '₩'}{info['price']:.2f} \n"
return message
def get_coin_data(symbol, interval=240, retries=3):
def get_coin_data(symbol, interval=240, to=None, retries=3):
for attempt in range(retries):
try:
url = "https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=3000".format(interval, symbol)
#url = "https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=3000".format(interval, symbol)
if to is None:
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
else:
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
#url = 'https://api.bithumb.com/v1/candles/minutes/60?market=KRW-ADA&count=200'
#url = 'https://api.bithumb.com/v1/candles/minutes/minutes/60?market=KRW-ADA&count=200&to=2025-08-06 10:38:38'
headers = {"accept": "application/json"}
response = requests.get(url, headers=headers)
json_data = json.loads(response.text)
@@ -328,6 +199,27 @@ def get_coin_data(symbol, interval=240, retries=3):
continue
return None
def get_coin_more_data(symbol, interval, bong_count=3000):
# 코인 데이터 1500개 봉 가져오기
to = datetime.now()
data = None
while data is None or len(data) < bong_count:
if data is None:
data = get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
else:
df = get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
data = pd.concat([data, df], ignore_index=True)
time.sleep(0.3)
to = to - relativedelta(minutes=interval * 200)
data = data.set_index('datetime')
data = data.sort_index()
data = data.drop_duplicates(keep='first')
data["datetime"] = data.index
# 코인 데이터 1500개 봉 가져오기
return data
def get_kr_stock_data(symbol, retries=3):
for attempt in range(retries):
@@ -368,14 +260,11 @@ def monitor_us_stocks():
if data is not None and not data.empty:
try:
data = calculate_technical_indicators(data)
info = detect_turnaround_signal(symbol, data, 0)
if info is None:
recent_data = check_buy_point(data) # Changed to check_buy_point
if recent_data['buy_point'][-1] != 1:
continue
info['name'] = US_STOCKS[symbol]
print(f" - {info['name']} ({symbol}): {info['price']:.2f} -> {info['alert']}")
if info['alert']:
message_list.append(format_ma_message(info, 'US'))
print(f" - {US_STOCKS[symbol]} ({symbol}): {recent_data['Close'][-1]:.2f}")
message_list.append(format_message('US', symbol, US_STOCKS[symbol], recent_data['Close'][-1]))
except Exception as e:
print(f"Error processing data for {symbol}: {str(e)}")
time.sleep(0.5)
@@ -402,14 +291,11 @@ def monitor_kr_stocks():
if data is not None and not data.empty:
try:
data = calculate_technical_indicators(data)
info = detect_turnaround_signal(symbol, data, 0)
if info is None:
recent_data = check_buy_point(data) # Changed to check_buy_point
if recent_data['buy_point'][-1] != 1:
continue
info['name'] = KR_ETFS[symbol]
print(f" - {info['name']} ({symbol}): {info['price']:.2f} -> {info['alert']}")
if info['alert']:
message_list.append(format_ma_message(info, 'KR'))
print(f" - {KR_ETFS[symbol]} ({symbol}): {recent_data['Close'][-1]:.2f}")
message_list.append(format_message('KR', symbol, US_STOCKS[symbol], recent_data['Close'][-1]))
except Exception as e:
print(f"Error processing data for {symbol}: {str(e)}")
@@ -434,25 +320,25 @@ def monitor_kr_stocks():
def monitor_coins():
message_list = []
buy_ticker_list = []
print("KRW COINs {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
for symbol in KR_COINS:
# 1시간
interval = 60
data = get_coin_data(symbol, interval=interval)
data = get_coin_more_data(symbol, interval)
if data is not None and not data.empty:
try:
data = calculate_technical_indicators(data)
info = detect_turnaround_signal(symbol, data, interval)
if info is None:
recent_data = check_buy_point(data) # Changed to check_buy_point
if recent_data['buy_point'][-1] != 1:
continue
info['name'] = KR_COINS[symbol]
print(f" - {info['name']} ({symbol}): {info['price']:.2f} -> {info['alert']} ({info['details']['interval']})")
print(f" - {KR_ETFS[symbol]} ({symbol}): {recent_data['Close'][-1]:.2f}")
message_list.append(format_message('COIN', symbol, US_STOCKS[symbol], recent_data['Close'][-1]))
# buy
buy_ticker(symbol)
if info['alert']:
message_list.append(format_ma_message(info, 'KR'))
buy_ticker_list.append(info)
except Exception as e:
print(f"Error processing data for {symbol}: {str(e)}")
else:
@@ -461,18 +347,19 @@ def monitor_coins():
# 4시간
interval = 240
data = get_coin_data(symbol, interval=interval)
data = get_coin_more_data(symbol, interval, bong_count=1500)
if data is not None and not data.empty:
try:
data = calculate_technical_indicators(data)
info = detect_turnaround_signal(symbol, data, interval)
info = check_buy_point(data, simulation=True) # Changed to check_buy_point
if info is None:
continue
info['name'] = KR_COINS[symbol]
print(f" - {info['name']} ({symbol}): {info['price']:.2f} -> {info['alert']} ({info['details']['interval']})")
print(f" - {info['name']} ({symbol}): {info['price']:.2f} -> {info['buy']}")
if info['alert']:
message_list.append(format_ma_message(info, 'KR'))
if info['buy']:
message_list.append(format_message(info, 'KR'))
except Exception as e:
print(f"Error processing data for {symbol}: {str(e)}")
else:
@@ -481,8 +368,6 @@ def monitor_coins():
if len(message_list) > 0:
try:
# buy
buy_ticker(buy_ticker_list)
# send message
send_coin_telegram_message(message_list, header="[KRW-COIN]")
except Exception as e:
@@ -494,70 +379,19 @@ def monitor_coins():
# Turnaround Detector v6
# ----------------------
def detect_turnaround_signal(symbol, data, interval=0):
def detect_turnaround_signal(symbol, data, interval=0, params=None):
if len(data) < 7:
return None
cur = data.iloc[-1]
# 이동평균을 기반으로 매수 신호 결정
cur = data.iloc[-1]
prev = data.iloc[-2]
recent = data.iloc[-7:-1]
# ①~② 국지 바닥 + 하단 터치
is_bottom = prev.Low == recent['Low'].min()
touch_lower = prev.Close <= prev.Lower * 1.01
# ③ 첫 반등 + MA5 돌파
rebound = (cur.Close >= prev.Close * 1.005) and (cur.Close >= cur.Lower * 1.01)
ma5_break = (prev.Close <= prev.MA5) and (cur.Close > cur.MA5)
ma20_below = cur.Close < cur.MA20
# ④ RSI 회복
rsi_recover = (prev.RSI < 40) and (cur.RSI > 40) and (cur.RSI > prev.RSI)
# ⑤ MACD 히스토그램 양전환
hist_cross = (prev.MACD_Hist <= 0) and (cur.MACD_Hist > 0)
# ⑥ MA5-MA20 골든크로스 (이번 봉) (or DMI 사용)
cross_ma = (prev.MA5 <= prev.MA20) and (cur.MA5 > cur.MA20)
# ⑦ 장기 추세 아직 하락
down_trend = cur.MA20 < cur.MA40
# 최근 저점 탐지 강화
recent_low = data['Low'].iloc[-10:].min()
is_recent_low = cur.Low <= recent_low * 1.005
# 추가 조건: MA5가 MA20을 상향 돌파
ma5_cross_ma20 = (prev.MA5 <= prev.MA20) and (cur.MA5 > cur.MA20)
# 매수 신호 조건 (저점 + 단기 MA 돌파 + RSI 회복)
# 볼린저 밴드 포지션
distance = (cur.Close - cur.Lower) / (cur.Upper - cur.Lower)
# 매수 신호 조건: 전봉 하단 밴드 터치 + 반등 + MA5 돌파 + RSI 회복 + 밴드 위치 ≤ 0.35
alert = touch_lower and rebound and ma5_break and rsi_recover and (distance <= 0.35)
return {
"symbol": symbol,
"price": float(cur.Close),
"alert": alert,
"details": {
"interval": interval,
"is_bottom": is_bottom,
"touch": touch_lower,
"rebound": rebound,
"ma5_break": ma5_break,
"ma20_below": ma20_below,
"rsi_recover": rsi_recover,
"hist_cross": hist_cross,
"cross_ma": cross_ma,
"down_trend": down_trend,
},
}
return None
def run_schedule():
monitor_coins()
# 코인 모니터링 스케줄 (매시간 1분, 11분, 21분, 31분, 41분, 51분)
for minute in [4, 14, 24, 34, 44, 54]:
schedule.every().hour.at(f":{minute:02d}").do(monitor_coins)