mirror of
https://github.com/freqtrade/freqtrade.git
synced 2024-09-20 09:31:12 +00:00
also use MACD indicator; minor changes
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gcarq
parent
0f5e00618b
commit
029072c9af
50
analyze.py
50
analyze.py
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@ -1,10 +1,7 @@
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import time
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from datetime import timedelta
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import arrow
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import matplotlib
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import logging
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matplotlib.use("Qt5Agg")
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import matplotlib.pyplot as plt
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import requests
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from pandas.io.json import json_normalize
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from stockstats import StockDataFrame
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@ -68,7 +65,8 @@ def populate_trends(dataframe):
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] = 1
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"""
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dataframe.loc[
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dataframe['stochrsi'] < 0.20,
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(dataframe['stochrsi'] < 0.20)
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& (dataframe['macd'] > dataframe['macds']),
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'underpriced'
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] = 1
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dataframe.loc[dataframe['underpriced'] == 1, 'buy'] = dataframe['close']
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@ -103,27 +101,32 @@ def plot_dataframe(dataframe, pair):
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:return: None
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"""
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import matplotlib
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matplotlib.use("Qt5Agg")
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import matplotlib.pyplot as plt
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# Three subplots sharing x axe
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f, (ax1, ax2) = plt.subplots(2, sharex=True)
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f, (ax1, ax2, ax3) = plt.subplots(3, sharex=True)
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f.suptitle(pair, fontsize=14, fontweight='bold')
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ax1.plot(dataframe.index.values, dataframe['close'], label='close')
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ax1.plot(dataframe.index.values, dataframe['close_60_ema'], label='EMA(60)')
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ax1.plot(dataframe.index.values, dataframe['close_120_ema'], label='EMA(120)')
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ax1.plot(dataframe.index.values, dataframe['close_30_ema'], label='EMA(60)')
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ax1.plot(dataframe.index.values, dataframe['close_90_ema'], label='EMA(120)')
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# ax1.plot(dataframe.index.values, dataframe['sell'], 'ro', label='sell')
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ax1.plot(dataframe.index.values, dataframe['buy'], 'bo', label='buy')
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ax1.legend()
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#ax2.plot(dataframe.index.values, dataframe['macd'], label='MACD')
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#ax2.plot(dataframe.index.values, dataframe['macds'], label='MACDS')
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#ax2.plot(dataframe.index.values, dataframe['macdh'], label='MACD Histogram')
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#ax2.plot(dataframe.index.values, [0] * len(dataframe.index.values))
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#ax2.legend()
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ax2.plot(dataframe.index.values, dataframe['stochrsi'], label='StochRSI')
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ax2.plot(dataframe.index.values, [0.80] * len(dataframe.index.values))
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ax2.plot(dataframe.index.values, [0.20] * len(dataframe.index.values))
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ax2.plot(dataframe.index.values, dataframe['macd'], label='MACD')
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ax2.plot(dataframe.index.values, dataframe['macds'], label='MACDS')
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ax2.plot(dataframe.index.values, dataframe['macdh'], label='MACD Histogram')
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ax2.plot(dataframe.index.values, [0] * len(dataframe.index.values))
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ax2.legend()
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ax3.plot(dataframe.index.values, dataframe['stochrsi'], label='StochRSI')
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ax3.plot(dataframe.index.values, [0.80] * len(dataframe.index.values))
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ax3.plot(dataframe.index.values, [0.20] * len(dataframe.index.values))
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ax3.legend()
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# Fine-tune figure; make subplots close to each other and hide x ticks for
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# all but bottom plot.
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f.subplots_adjust(hspace=0)
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@ -134,10 +137,9 @@ def plot_dataframe(dataframe, pair):
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if __name__ == '__main__':
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while True:
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pair = 'BTC_ANT'
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for pair in ['BTC_ANT', 'BTC_ETH', 'BTC_GNT', 'BTC_ETC']:
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get_buy_signal(pair)
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#dataframe = get_ticker_dataframe(pair)
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#dataframe = populate_trends(dataframe)
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#plot_dataframe(dataframe, pair)
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#time.sleep(60)
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#for pair in ['BTC_ANT', 'BTC_ETH', 'BTC_GNT', 'BTC_ETC']:
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# get_buy_signal(pair)
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dataframe = get_ticker_dataframe(pair)
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dataframe = populate_trends(dataframe)
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plot_dataframe(dataframe, pair)
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time.sleep(60)
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11
exchange.py
11
exchange.py
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@ -169,3 +169,14 @@ class ApiWrapper(object):
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'amount': entry['Quantity'],
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'remaining': entry['QuantityRemaining'],
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} for entry in data['result']]
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def get_pair_detail_url(self, pair):
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"""
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Returns the market detail url for the given pair
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:param pair: pair as str, format: BTC_ANT
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:return: url as str
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"""
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if self.exchange == Exchange.POLONIEX:
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raise NotImplemented('Not implemented')
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elif self.exchange == Exchange.BITTREX:
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return 'https://bittrex.com/Market/Index?MarketName={}'.format(pair.replace('_', '-'))
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14
main.py
14
main.py
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@ -1,7 +1,6 @@
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#!/usr/bin/env python
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import json
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import logging
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import random
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import threading
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import time
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import traceback
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@ -167,9 +166,10 @@ def handle_trade(trade):
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trade.close_date = datetime.utcnow()
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trade.open_order_id = order_id
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message = '*{}:* Selling {} at rate `{:f} (profit: {}%)`'.format(
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message = '*{}:* Selling [{}]({}) at rate `{:f} (profit: {}%)`'.format(
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trade.exchange.name,
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trade.pair.replace('_', '/'),
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api_wrapper.get_pair_detail_url(trade.pair),
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trade.close_rate,
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round(current_profit, 2)
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)
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@ -206,9 +206,6 @@ def create_trade(stake_amount: float, exchange):
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if not whitelist:
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raise ValueError('No pair in whitelist')
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## Pick random pair and execute trade
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#idx = random.randint(0, len(whitelist) - 1)
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#pair = whitelist[idx]
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# Pick pair based on StochRSI buy signals
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for p in whitelist:
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if get_buy_signal(p):
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@ -223,7 +220,12 @@ def create_trade(stake_amount: float, exchange):
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order_id = api_wrapper.buy(pair, open_rate, amount)
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# Create trade entity and return
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message = '*{}:* Buying {} at rate `{:f}`'.format(exchange.name, pair.replace('_', '/'), open_rate)
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message = '*{}:* Buying [{}]({}) at rate `{:f}`'.format(
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exchange.name,
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pair.replace('_', '/'),
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api_wrapper.get_pair_detail_url(pair),
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open_rate
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)
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logger.info(message)
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TelegramHandler.send_msg(message)
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return Trade(pair=pair,
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@ -70,7 +70,7 @@ class TelegramHandler(object):
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order = orders[0] if orders else None
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message = """
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*Trade ID:* `{trade_id}`
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*Current Pair:* [{pair}](https://bittrex.com/Market/Index?MarketName={pair})
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*Current Pair:* [{pair}]({market_url})
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*Open Since:* `{date}`
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*Amount:* `{amount}`
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*Open Rate:* `{open_rate}`
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@ -81,7 +81,8 @@ class TelegramHandler(object):
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*Open Order:* `{open_order}`
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""".format(
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trade_id=trade.id,
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pair=trade.pair.replace('_', '-'),
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pair=trade.pair,
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market_url=api_wrapper.get_pair_detail_url(trade.pair),
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date=arrow.get(trade.open_date).humanize(),
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open_rate=trade.open_rate,
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close_rate=trade.close_rate,
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@ -114,11 +115,11 @@ class TelegramHandler(object):
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durations_hours = [(t.close_date - t.open_date).total_seconds() / 3600.0 for t in trades]
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avg_duration = sum(durations_hours) / float(len(durations_hours))
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markdown_msg = """
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*ROI:* `{profit_btc} BTC ({profit}%)`
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*ROI:* `{profit_btc} ({profit}%)`
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*Trade Count:* `{trade_count}`
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*First Trade completed:* `{first_trade_date}`
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*Latest Trade completed:* `{latest_trade_date}`
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*Avg. Stake Amount:* `{avg_stake_amount} BTC`
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*Avg. Stake Amount:* `{avg_stake_amount}`
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*Avg. Duration:* `{avg_duration}`
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""".format(
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profit_btc=round(profit_amount, 8),
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