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The Heracles strategy is a trading strategy designed for backtesting. It uses technical indicators to generate buy signals and does not include specific sell conditions. Here are the key components of the strategy:
The strategy requires the installation of the ta library before running.
It operates on the '4h' timeframe.
The strategy calculates two volatility indicators: Keltner Channel Width Band (volatility_kcw) and Donchian Channel P Band (volatility_dcp).
In the populate_buy_trend function, the strategy defines buy conditions based on the calculated indicators. It uses parameters such as buy_div_min, buy_div_max, buy_indicator_shift, and buy_crossed_indicator_shift to determine the buy signals. The buy conditions are applied to the dataframe, and rows that meet the conditions are assigned a value of 1 in the 'buy' column. The populate_sell_trend function sets the 'sell' column to 0 for all rows, indicating that there are no specific sell conditions defined in this strategy. The strategy provides hyperparameters (buy_params and sell_params) and a minimal ROI table (minimal_roi) that can be customized for optimization. Overall, the Heracles strategy aims to generate buy signals based on the calculated indicators and can be further customized and optimized using hyperparameters.
It operates on the '4h' timeframe.
The strategy calculates two volatility indicators: Keltner Channel Width Band (volatility_kcw) and Donchian Channel P Band (volatility_dcp).
In the populate_buy_trend function, the strategy defines buy conditions based on the calculated indicators. It uses parameters such as buy_div_min, buy_div_max, buy_indicator_shift, and buy_crossed_indicator_shift to determine the buy signals. The buy conditions are applied to the dataframe, and rows that meet the conditions are assigned a value of 1 in the 'buy' column. The populate_sell_trend function sets the 'sell' column to 0 for all rows, indicating that there are no specific sell conditions defined in this strategy. The strategy provides hyperparameters (buy_params and sell_params) and a minimal ROI table (minimal_roi) that can be customized for optimization. Overall, the Heracles strategy aims to generate buy signals based on the calculated indicators and can be further customized and optimized using hyperparameters.
startup_candle_count : 50 Recursive Analysis found no issues while using 50 startup_candle_count
Biased Entry Signals:
1
Traceback (most recent call last): File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connection.py", line 203, 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) TimeoutError: timed out 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 790, in urlopen response = self._make_request( ^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connectionpool.py", line 491, in _make_request raise new_e File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connectionpool.py", line 467, in _make_request self._validate_conn(conn) File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connectionpool.py", line 1092, in _validate_conn conn.connect() File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connection.py", line 611, in connect self.sock = sock = self._new_conn() ^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/urllib3/connection.py", line 212, in _new_conn raise ConnectTimeoutError( urllib3.exceptions.ConnectTimeoutError: (, 'Connection to api.kucoin.com timed out. (connect timeout=10)') 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 844, 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: HTTPSConnectionPool(host='api.kucoin.com', port=443): Max retries exceeded with url: /api/v3/currencies (Caused by ConnectTimeoutError( , 'Connection to api.kucoin.com timed out. (connect timeout=10)')) During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/home/ftuser/.local/lib/python3.11/site-packages/ccxt/base/exchange.py", line 584, in fetch response = self.session.request( ^^^^^^^^^^^^^^^^^^^^^ 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 507, in send raise ConnectTimeout(e, request=request) requests.exceptions.ConnectTimeout: HTTPSConnectionPool(host='api.kucoin.com', port=443): Max retries exceeded with url: /api/v3/currencies (Caused by ConnectTimeoutError( , 'Connection to api.kucoin.com timed out.
(connect timeout=10)')) The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/freqtrade/freqtrade/exchange/exchange.py", line 480, in _load_markets self._markets = self._api.load_markets(params={}) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/ccxt/base/exchange.py", line 1443, in load_markets currencies = self.fetch_currencies() ^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/ccxt/kucoin.py", line 1009, in fetch_currencies promises.append(self.publicGetCurrencies(params)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/ccxt/base/types.py", line 26, in unbound_method return _self.request(self.path, self.api, self.method, params, config=self.config) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/ccxt/base/exchange.py", line 3051, in request return self.fetch2(path, api, method, params, headers, body, config) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/ccxt/base/exchange.py", line 3048, in fetch2 return self.fetch(request['url'], request['method'], request['headers'], request['body']) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/ccxt/base/exchange.py", line 614, in fetch raise RequestTimeout(details) from e ccxt.base.errors.RequestTimeout: kucoin GET https://api.kucoin.com/api/v3/currencies
stoploss: -0.256 timeframe: 4h hash(sha256): 1aa6d736e6812aad437c7e1070e076b98b9af2404abc6718d018221f61bb226e indicators: high close volatility_kcw volatility_dcp low
No similar strategies found. (based on used indicators)
last change: 2023-10-24 20:11:57