also use MACD indicator; minor changes

analyze.py

@@ -1,10 +1,7 @@
+import time
 from datetime import timedelta
 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
@@ -68,7 +65,8 @@ def populate_trends(dataframe):
     ] = 1
     """
     dataframe.loc[
-        dataframe['stochrsi'] < 0.20,
+        (dataframe['stochrsi'] < 0.20)
+        & (dataframe['macd'] > dataframe['macds']),
         'underpriced'
     ] = 1
     dataframe.loc[dataframe['underpriced'] == 1, 'buy'] = dataframe['close']
@@ -103,27 +101,32 @@ def plot_dataframe(dataframe, pair):
     :return: None
     """
 
+    import matplotlib
+
+    matplotlib.use("Qt5Agg")
+    import matplotlib.pyplot as plt
+
     # Three subplots sharing x axe
-    f, (ax1, ax2) = plt.subplots(2, sharex=True)
+    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_60_ema'], label='EMA(60)')
+    ax1.plot(dataframe.index.values, dataframe['close_30_ema'], label='EMA(60)')
-    ax1.plot(dataframe.index.values, dataframe['close_120_ema'], label='EMA(120)')
+    ax1.plot(dataframe.index.values, dataframe['close_90_ema'], label='EMA(120)')
     # 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['macd'], label='MACD')
-    #ax2.plot(dataframe.index.values, dataframe['macds'], label='MACDS')
+    ax2.plot(dataframe.index.values, dataframe['macds'], label='MACDS')
-    #ax2.plot(dataframe.index.values, dataframe['macdh'], label='MACD Histogram')
+    ax2.plot(dataframe.index.values, dataframe['macdh'], label='MACD Histogram')
-    #ax2.plot(dataframe.index.values, [0] * len(dataframe.index.values))
+    ax2.plot(dataframe.index.values, [0] * len(dataframe.index.values))
-    #ax2.legend()
-
-    ax2.plot(dataframe.index.values, dataframe['stochrsi'], label='StochRSI')
-    ax2.plot(dataframe.index.values, [0.80] * len(dataframe.index.values))
-    ax2.plot(dataframe.index.values, [0.20] * 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)
@@ -134,10 +137,9 @@ def plot_dataframe(dataframe, pair):
 if __name__ == '__main__':
     while True:
         pair = 'BTC_ANT'
-        for pair in ['BTC_ANT', 'BTC_ETH', 'BTC_GNT', 'BTC_ETC']:
+        #for pair in ['BTC_ANT', 'BTC_ETH', 'BTC_GNT', 'BTC_ETC']:
-            get_buy_signal(pair)
+        #   get_buy_signal(pair)
-        #dataframe = get_ticker_dataframe(pair)
+        dataframe = get_ticker_dataframe(pair)
-        #dataframe = populate_trends(dataframe)
+        dataframe = populate_trends(dataframe)
-        #plot_dataframe(dataframe, pair)
+        plot_dataframe(dataframe, pair)
-        #time.sleep(60)
+        time.sleep(60)
-

exchange.py

@@ -169,3 +169,14 @@ class ApiWrapper(object):
                 'amount': entry['Quantity'],
                 'remaining': entry['QuantityRemaining'],
             } for entry in data['result']]
+
+    def get_pair_detail_url(self, pair):
+        """
+        Returns the market detail url for the given pair
+        :param pair: pair as str, format: BTC_ANT
+        :return: url as str
+        """
+        if self.exchange == Exchange.POLONIEX:
+            raise NotImplemented('Not implemented')
+        elif self.exchange == Exchange.BITTREX:
+            return 'https://bittrex.com/Market/Index?MarketName={}'.format(pair.replace('_', '-'))

main.py

@@ -1,7 +1,6 @@
 #!/usr/bin/env python
 import json
 import logging
-import random
 import threading
 import time
 import traceback
@@ -167,9 +166,10 @@ def handle_trade(trade):
                 trade.close_date = datetime.utcnow()
                 trade.open_order_id = order_id
 
-                message = '*{}:* Selling {} at rate `{:f} (profit: {}%)`'.format(
+                message = '*{}:* Selling [{}]({}) at rate `{:f} (profit: {}%)`'.format(
                     trade.exchange.name,
                     trade.pair.replace('_', '/'),
+                    api_wrapper.get_pair_detail_url(trade.pair),
                     trade.close_rate,
                     round(current_profit, 2)
                 )
@@ -206,9 +206,6 @@ 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 pair based on StochRSI buy signals
     for p in whitelist:
         if get_buy_signal(p):
@@ -223,7 +220,12 @@ def create_trade(stake_amount: float, exchange):
     order_id = api_wrapper.buy(pair, open_rate, amount)
 
     # Create trade entity and return
-    message = '*{}:* Buying {} at rate `{:f}`'.format(exchange.name, pair.replace('_', '/'), open_rate)
+    message = '*{}:* Buying [{}]({}) at rate `{:f}`'.format(
+        exchange.name,
+        pair.replace('_', '/'),
+        api_wrapper.get_pair_detail_url(pair),
+        open_rate
+    )
     logger.info(message)
     TelegramHandler.send_msg(message)
     return Trade(pair=pair,

rpc/telegram.py

@@ -70,7 +70,7 @@ class TelegramHandler(object):
                 order = orders[0] if orders else None
                 message = """
 *Trade ID:* `{trade_id}`
-*Current Pair:* [{pair}](https://bittrex.com/Market/Index?MarketName={pair})
+*Current Pair:* [{pair}]({market_url})
 *Open Since:* `{date}`
 *Amount:* `{amount}`
 *Open Rate:* `{open_rate}`
@@ -81,7 +81,8 @@ class TelegramHandler(object):
 *Open Order:* `{open_order}`
                         """.format(
                     trade_id=trade.id,
-                    pair=trade.pair.replace('_', '-'),
+                    pair=trade.pair,
+                    market_url=api_wrapper.get_pair_detail_url(trade.pair),
                     date=arrow.get(trade.open_date).humanize(),
                     open_rate=trade.open_rate,
                     close_rate=trade.close_rate,
@@ -114,11 +115,11 @@ class TelegramHandler(object):
         durations_hours = [(t.close_date - t.open_date).total_seconds() / 3600.0 for t in trades]
         avg_duration = sum(durations_hours) / float(len(durations_hours))
         markdown_msg = """
-*ROI:* `{profit_btc} BTC ({profit}%)`
+*ROI:* `{profit_btc} ({profit}%)`
 *Trade Count:* `{trade_count}`
 *First Trade completed:* `{first_trade_date}`
 *Latest Trade completed:* `{latest_trade_date}`
-*Avg. Stake Amount:* `{avg_stake_amount} BTC`
+*Avg. Stake Amount:* `{avg_stake_amount}`
 *Avg. Duration:* `{avg_duration}` 
     """.format(
             profit_btc=round(profit_amount, 8),