The TA_Collector_v1 strategy is a trading strategy that involves collecting and analyzing technical indicators to make buying and selling decisions. Here is a brief description of what the strategy does:
populate_indicators: This method populates the strategy's indicators by gathering data from different timeframes (1-hour and 5-minute) and merging them with the main timeframe data. It also includes normal timeframe indicators.
The collected data is then sent to a specific endpoint using a POST request.
populate_buy_trend and populate_sell_trend: These methods initialize the "buy" and "sell" columns in the dataframe to 0, indicating no buying or selling signals at the beginning.
Parameter calculations: The strategy involves calculating various parameters such as period, multiplier, length, MAtype, and src (source). These parameters are used in subsequent calculations. Moving Average (MA) calculations: Based on the selected MAtype and length, the strategy calculates the moving average value (mavalue) using different types of moving averages, such as EMA, DEMA, T3, SMA, VIDYA, TEMA, WMA, VWMA, and ZEMA. ATR (Average True Range) calculation: The strategy calculates the Average True Range using the ATR function. Upper and lower bounds calculation: The strategy calculates the upper and lower bounds based on the mavalue and ATR. These bounds help determine potential buy or sell signals. Final upper and lower bounds calculation: The strategy calculates the final upper and lower bounds, considering the previous values and comparing them with mavalue. Parameter array calculation: The strategy calculates the pm_arr (parameter array) based on the final upper and lower bounds and mavalue. The pm_arr determines the buy or sell signal or remains 0 if no signal is present. Parameter direction calculation: The strategy determines the direction (up or down) based on the relationship between pm_arr and mavalue. Momentum calculation: The strategy calculates the momentum using the MOM function. Bollinger Bands calculation: The strategy calculates the upperband, middleband, and lowerband using the BBANDS function based on the momentum values. Buy and sell signals calculation: The strategy determines buy signals when the momentum crosses below the lowerband and sell signals when the momentum crosses above the upperband. Rolling High and Low calculation: The strategy calculates rolling high (hh) and low (ll) based on the specified lookback period. Condition calculation: The strategy checks if the high values are greater than or equal to the rolling high (coh) and if the low values are less than or equal to the rolling low (col). Dataframe creation: The strategy creates a new dataframe including the calculated indicators and signals. T3 Average calculation: The strategy applies the T3 Average calculation, which involves multiple iterations of EMA calculations. Overall, the TA_Collector_v1 strategy collects and analyzes technical indicators, calculates various parameters, and generates buy and sell signals based on moving averages, bounds, momentum, Bollinger Bands, and T3 Average.
The collected data is then sent to a specific endpoint using a POST request.
populate_buy_trend and populate_sell_trend: These methods initialize the "buy" and "sell" columns in the dataframe to 0, indicating no buying or selling signals at the beginning.
Parameter calculations: The strategy involves calculating various parameters such as period, multiplier, length, MAtype, and src (source). These parameters are used in subsequent calculations. Moving Average (MA) calculations: Based on the selected MAtype and length, the strategy calculates the moving average value (mavalue) using different types of moving averages, such as EMA, DEMA, T3, SMA, VIDYA, TEMA, WMA, VWMA, and ZEMA. ATR (Average True Range) calculation: The strategy calculates the Average True Range using the ATR function. Upper and lower bounds calculation: The strategy calculates the upper and lower bounds based on the mavalue and ATR. These bounds help determine potential buy or sell signals. Final upper and lower bounds calculation: The strategy calculates the final upper and lower bounds, considering the previous values and comparing them with mavalue. Parameter array calculation: The strategy calculates the pm_arr (parameter array) based on the final upper and lower bounds and mavalue. The pm_arr determines the buy or sell signal or remains 0 if no signal is present. Parameter direction calculation: The strategy determines the direction (up or down) based on the relationship between pm_arr and mavalue. Momentum calculation: The strategy calculates the momentum using the MOM function. Bollinger Bands calculation: The strategy calculates the upperband, middleband, and lowerband using the BBANDS function based on the momentum values. Buy and sell signals calculation: The strategy determines buy signals when the momentum crosses below the lowerband and sell signals when the momentum crosses above the upperband. Rolling High and Low calculation: The strategy calculates rolling high (hh) and low (ll) based on the specified lookback period. Condition calculation: The strategy checks if the high values are greater than or equal to the rolling high (coh) and if the low values are less than or equal to the rolling low (col). Dataframe creation: The strategy creates a new dataframe including the calculated indicators and signals. T3 Average calculation: The strategy applies the T3 Average calculation, which involves multiple iterations of EMA calculations. Overall, the TA_Collector_v1 strategy collects and analyzes technical indicators, calculates various parameters, and generates buy and sell signals based on moving averages, bounds, momentum, Bollinger Bands, and T3 Average.
Traceback (most recent call last): File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connection.py", line 198, in _new_conn sock = connection.create_connection( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/util/connection.py", line 85, in create_connection raise err File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/util/connection.py", line 73, in create_connection sock.connect(sa) OSError: [Errno 113] No route to host The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connectionpool.py", line 793, in urlopen response = self._make_request( ^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connectionpool.py", line 496, in _make_request conn.request( File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connection.py", line 400, in request self.endheaders() File "/usr/local/lib/python3.11/http/client.py", line 1293, in endheaders self._send_output(message_body, encode_chunked=encode_chunked) File "/usr/local/lib/python3.11/http/client.py", line 1052, in _send_output self.send(msg) File "/usr/local/lib/python3.11/http/client.py", line 990, in send self.connect() File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connection.py", line 238, in connect self.sock = self._new_conn() ^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connection.py", line 213, in _new_conn raise NewConnectionError( urllib3.exceptions.NewConnectionError:: Failed to establish a new connection: [Errno 113] No route to host The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/home/ftuser/.local/lib/python3.11/site-packages/requests/adapters.py", line 486, in send resp = conn.urlopen( ^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connectionpool.py", line 847, in urlopen retries = retries.increment( ^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/util/retry.py", line 515, in increment raise MaxRetryError(_pool, url, reason) from reason # type: ignore[arg-type] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ urllib3.exceptions.MaxRetryError: HTTPConnectionPool(host='192.168.1.7', port=9000): Max retries exceeded with url: /data-gateway/submit-data (Caused by NewConnectionError(' : Failed to establish a new connection: [Errno 113] No route to host')) During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/freqtrade/freqtrade/main.py", line 42, in main return_code = args['func'](args) ^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/commands/optimize_commands.py", line 58, in start_backtesting backtesting.start() File "/freqtrade/freqtrade/optimize/backtesting.py", line 1401, in start min_date, max_date = self.backtest_one_strategy(strat, data, timerange) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/optimize/backtesting.py", line 1318, in backtest_one_strategy preprocessed = self.strategy.advise_all_indicators(data) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1378, in advise_all_indicators return {pair: self.advise_indicators(pair_data.copy(), {'pair': pair}).copy() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1378, in return {pair: self.advise_indicators(pair_data.copy(), {'pair': pair}).copy() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1410, in advise_indicators return self.populate_indicators(dataframe, metadata) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/user_data/strategies/TA_Collector_v1_0.py", line 795, in populate_indicators requests.post('http://192.168.1.7:9000/data-gateway/submit-data', json=postData) File "/home/ftuser/.local/lib/python3.11/site-packages/requests/api.py", line 115, in post return request("post", url, data=data, json=json, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/requests/api.py", line 59, in request return session.request(method=method, url=url, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/requests/sessions.py", line 589, in request resp = self.send(prep, **send_kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/requests/sessions.py", line 703, in send r = adapter.send(request, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/requests/adapters.py", line 519, in send raise ConnectionError(e, request=request) requests.exceptions.ConnectionError: HTTPConnectionPool(host='192.168.1.7', port=9000): Max retries exceeded with url: /data-gateway/submit-data (Caused by NewConnectionError(' : Failed to establish a new connection: [Errno 113] No route to host'))
stoploss: -0.99 timeframe: 1m hash(sha256): 49218b4d8e64060a1d1fd90e44250aee6a14d60e3ffdaebe98885e694905b826 indicators: upper rsi_20_1m sma_volume_28 close stoch_slowd_1m cmf_1m ha_obv ema_volume_12_1m sma_20_1m bb_upperband3_1m volume ema_volume_8_1m sma_volume_9_1m rsi_4 ema_volume_4_1m ema_obv_20_1m xe1 ema_4_1m sma_50 ema_20 rsi_14 bb_upperband2 high ema_volume_4 ema_8 ema_obv_12 ema_obv_4_1m bb_lowerband3 xe6 macd_histogram_1m final_ub sma_volume_20_1m ema_volume_16 ha_high sma_75_1m ema_12 ha_low_1m sma_28 T3Average ema_26 stoch_fastd_1m ema_200_1m basic_ub obv sma_volume_30 rsi_20 stoch_slowd bb_middleband
No similar strategies found. (based on used indicators)
last change: 2024-04-29 20:10:06