diff --git a/analyze.py b/analyze.py index 774a900f9..d8b86d945 100644 --- a/analyze.py +++ b/analyze.py @@ -43,15 +43,20 @@ def parse_ticker_dataframe(ticker: list, minimum_date: arrow.Arrow) -> DataFrame .sort_values('date') return df[df['date'].map(arrow.get) > minimum_date] - def populate_indicators(dataframe: DataFrame) -> DataFrame: """ Adds several different TA indicators to the given DataFrame """ - dataframe['ema'] = ta.EMA(dataframe, timeperiod=33) dataframe['sar'] = ta.SAR(dataframe, 0.02, 0.22) dataframe['adx'] = ta.ADX(dataframe) - + stoch = ta.STOCHF(dataframe) + dataframe['fastd'] = stoch['fastd'] + dataframe['fastk'] = stoch['fastk'] + dataframe['blower'] = ta.BBANDS(dataframe, nbdevup=2, nbdevdn=2)['lowerband'] + dataframe['cci'] = ta.CCI(dataframe, timeperiod=5) + dataframe['sma'] = ta.SMA(dataframe, timeperiod=100) + dataframe['tema'] = ta.TEMA(dataframe, timeperiod=4) + dataframe['mfi'] = ta.MFI(dataframe) return dataframe @@ -61,26 +66,14 @@ def populate_buy_trend(dataframe: DataFrame) -> DataFrame: :param dataframe: DataFrame :return: DataFrame with buy column """ - prev_sar = dataframe['sar'].shift(1) - prev_close = dataframe['close'].shift(1) - prev_sar2 = dataframe['sar'].shift(2) - prev_close2 = dataframe['close'].shift(2) - - # wait for stable turn from bearish to bullish market - dataframe.loc[ - (dataframe['close'] > dataframe['sar']) & - (prev_close > prev_sar) & - (prev_close2 < prev_sar2), - 'swap' - ] = 1 - - # consider prices above ema to be in upswing - dataframe.loc[dataframe['ema'] <= dataframe['close'], 'upswing'] = 1 dataframe.loc[ - (dataframe['upswing'] == 1) & - (dataframe['swap'] == 1) & - (dataframe['adx'] > 25), # adx over 25 tells there's enough momentum + (dataframe['close'] < dataframe['sma']) & + (dataframe['cci'] < -100) & + (dataframe['tema'] <= dataframe['blower']) & + (dataframe['mfi'] < 30) & + (dataframe['fastd'] < 20) & + (dataframe['adx'] > 20), 'buy'] = 1 dataframe.loc[dataframe['buy'] == 1, 'buy_price'] = dataframe['close'] @@ -147,12 +140,13 @@ def plot_dataframe(dataframe: DataFrame, pair: str) -> None: ax1.plot(dataframe.index.values, dataframe['sar'], 'g_', label='pSAR') ax1.plot(dataframe.index.values, dataframe['close'], label='close') # ax1.plot(dataframe.index.values, dataframe['sell'], 'ro', label='sell') - ax1.plot(dataframe.index.values, dataframe['ema'], '--', label='EMA(20)') - ax1.plot(dataframe.index.values, dataframe['buy'], 'bo', label='buy') + ax1.plot(dataframe.index.values, dataframe['sma'], '--', label='SMA') + ax1.plot(dataframe.index.values, dataframe['buy_price'], 'bo', label='buy') ax1.legend() - ax2.plot(dataframe.index.values, dataframe['adx'], label='ADX') - ax2.plot(dataframe.index.values, [25] * len(dataframe.index.values)) +# ax2.plot(dataframe.index.values, dataframe['adx'], label='ADX') + ax2.plot(dataframe.index.values, dataframe['mfi'], label='MFI') +# ax2.plot(dataframe.index.values, [25] * len(dataframe.index.values)) ax2.legend() # Fine-tune figure; make subplots close to each other and hide x ticks for diff --git a/config.json.example b/config.json.example index a0b93c455..584fb019d 100644 --- a/config.json.example +++ b/config.json.example @@ -3,13 +3,14 @@ "stake_currency": "BTC", "stake_amount": 0.05, "dry_run": false, - "minimal_roi": { - "2880": 0.005, - "720": 0.01, - "0": 0.02 - }, - "stoploss": -0.10, - "bid_strategy": { + "minimal_roi": { + "60": 0.0, + "40": 0.01, + "20": 0.02, + "0": 0.03 + }, + "stoploss": -0.40, + "bid_strategy": { "ask_last_balance": 0.0 }, "bittrex": { diff --git a/test/test_backtesting.py b/test/test_backtesting.py index ad25e17a8..1bd7fed54 100644 --- a/test/test_backtesting.py +++ b/test/test_backtesting.py @@ -22,11 +22,12 @@ class TestMain(unittest.TestCase): pairs = ['btc-neo', 'btc-eth', 'btc-omg', 'btc-edg', 'btc-pay', 'btc-pivx', 'btc-qtum', 'btc-mtl', 'btc-etc', 'btc-ltc'] conf = { "minimal_roi": { - "2880": 0.005, - "720": 0.01, - "0": 0.02 + "60": 0.0, + "40": 0.01, + "20": 0.02, + "0": 0.03 }, - "stoploss": -0.10 + "stoploss": -0.40 } @classmethod