implement StochRSI buy signal handler

analyze.py

@@ -0,0 +1,127 @@
+from datetime import timedelta
+import time
+import arrow
+import matplotlib
+import logging
+
+matplotlib.use("Qt5Agg")
+import matplotlib.pyplot as plt
+import requests
+from pandas.io.json import json_normalize
+from stockstats import StockDataFrame
+
+logging.basicConfig(level=logging.DEBUG,
+                    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+logger = logging.getLogger(__name__)
+
+
+def get_ticker_dataframe(pair):
+    """
+    Analyses the trend for the given pair
+    :param pair: pair as str in format BTC_ETH or BTC-ETH
+    :return: StockDataFrame
+    """
+    minimum_date = arrow.now() - timedelta(hours=2)
+    url = 'https://bittrex.com/Api/v2.0/pub/market/GetTicks'
+    params = {
+        'marketName': pair.replace('_', '-'),
+        'tickInterval': 'OneMin',
+        '_': minimum_date.timestamp * 1000
+    }
+    data = requests.get(url, params).json()
+    if not data['success']:
+        raise RuntimeError('BITTREX: {}'.format(data['message']))
+
+    data = [{
+        'close': t['C'],
+        'volume': t['V'],
+        'open': t['O'],
+        'high': t['H'],
+        'low': t['L'],
+        'date': t['T'],
+    } for t in data['result'] if arrow.get(t['T']) > minimum_date]
+    dataframe = StockDataFrame(json_normalize(data))
+
+    # calculate StochRSI
+    rsi = dataframe['rsi_{}'.format(14)]
+    rolling = rsi.rolling(window=14, center=False)
+    low = rolling.min()
+    high = rolling.max()
+    dataframe['stochrsi'] = (rsi - low) / (high - low)
+    return dataframe
+
+
+def populate_trends(dataframe):
+    """
+    Populates the trends for the given dataframe
+    :param dataframe: StockDataFrame
+    :return: StockDataFrame with populated trends
+    """
+    #dataframe.loc[
+    #    (dataframe['stochrsi'] < 0.20)
+    #    & (dataframe['close_12_ema'] <= dataframe['close_26_ema']),
+    #    'bullish'
+    #] = 1
+    dataframe.loc[
+        (dataframe['stochrsi'] < 0.20), 'underpriced'
+    ] = 1
+    dataframe.loc[dataframe['underpriced'] == 1, 'buy'] = dataframe['close']
+    return dataframe
+
+
+def get_buy_signal(pair):
+    """
+    Calculates a buy signal based on StochRSI indicator
+    :param pair: pair in format BTC_ANT or BTC-ANT
+    :return: True if pair is underpriced, False otherwise
+    """
+    dataframe = get_ticker_dataframe(pair)
+    dataframe = populate_trends(dataframe)
+    latest = dataframe.iloc[-1]
+    signal = latest['underpriced'] == 1
+    logger.debug('buy_trigger: {} (pair={}, signal={})'.format(latest['date'], pair, signal))
+    return signal
+
+
+def plot_dataframe(dataframe, pair):
+    """
+    Plots the given dataframe
+    :param dataframe: StockDataFrame
+    :param pair: pair as str
+    :return: None
+    """
+
+    # Three subplots sharing x axe
+    f, (ax1, ax2, ax3) = plt.subplots(3, sharex=True)
+    f.suptitle(pair, fontsize=14, fontweight='bold')
+    ax1.plot(dataframe.index.values, dataframe['close'], label='close')
+    ax1.plot(dataframe.index.values, dataframe['close_12_ema'], label='EMA(12)')
+    ax1.plot(dataframe.index.values, dataframe['close_26_ema'], label='EMA(26)')
+    # ax1.plot(dataframe.index.values, dataframe['sell'], 'ro', label='sell')
+    ax1.plot(dataframe.index.values, dataframe['buy'], 'bo', label='buy')
+    ax1.legend()
+
+    ax2.plot(dataframe.index.values, dataframe['macd'], label='MACD')
+    ax2.plot(dataframe.index.values, dataframe['macds'], label='MACDS')
+    ax2.plot(dataframe.index.values, dataframe['macdh'], label='MACD Histogram')
+    ax2.plot(dataframe.index.values, [0] * len(dataframe.index.values))
+    ax2.legend()
+
+    ax3.plot(dataframe.index.values, dataframe['stochrsi'], label='StochRSI')
+    ax3.plot(dataframe.index.values, [0.80] * len(dataframe.index.values))
+    ax3.plot(dataframe.index.values, [0.20] * len(dataframe.index.values))
+    ax3.legend()
+
+    # Fine-tune figure; make subplots close to each other and hide x ticks for
+    # all but bottom plot.
+    f.subplots_adjust(hspace=0)
+    plt.setp([a.get_xticklabels() for a in f.axes[:-1]], visible=False)
+    plt.show()
+
+
+if __name__ == '__main__':
+    while True:
+        pair = 'BTC_ANT'
+        for pair in ['BTC_ANT', 'BTC_ETH', 'BTC_GNT', 'BTC_ETC']:
+            get_buy_signal(pair)
+        time.sleep(60)

main.py

@@ -11,6 +11,8 @@ from requests import ConnectionError
 
 from wrapt import synchronized
 
+from analyze import get_buy_signal
+
 logging.basicConfig(level=logging.DEBUG,
                     format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
 logger = logging.getLogger(__name__)
@@ -203,9 +205,18 @@ def create_trade(stake_amount: float, exchange):
     if not whitelist:
         raise ValueError('No pair in whitelist')
 
-    # Pick random pair and execute trade
-    idx = random.randint(0, len(whitelist) - 1)
-    pair = whitelist[idx]
+    ## Pick random pair and execute trade
+    #idx = random.randint(0, len(whitelist) - 1)
+    #pair = whitelist[idx]
+    pair = None
+    # Pick pair based on StochRSI buy signals
+    for p in whitelist:
+        if get_buy_signal(p):
+            pair = p
+            break
+    else:
+        raise ValueError('No buy signal from pairs: {}'.format(','.join(whitelist)))
+
     open_rate = api_wrapper.get_ticker(pair)['ask']
     amount = stake_amount / open_rate
     exchange = exchange

requirements.txt

@@ -6,3 +6,9 @@ arrow==0.10.0
 requests==2.14.2
 urllib3==1.20
 wrapt==1.10.10
+pandas==0.20.1
+matplotlib==2.0.0
+PYQT5==5.8
+scikit-learn==0.18.1
+scipy==0.18.1
+stockstats==0.2.0