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The BinHV27_short strategy is a trading strategy that uses various indicators to identify potential entry and exit points for trades. Here is a breakdown of what the strategy does:
In the populate_indicators method:
It calculates several indicators such as RSI, EMA, ADX, MINUS_DI, PLUS_DI, and various moving averages based on the input dataframe. It creates additional columns in the dataframe to store the calculated indicator values.
It performs certain calculations and comparisons to determine the values of other columns, such as 'bigup', 'bigdown', 'trend', 'preparechangetrend', 'continueup', 'delta', 'slowingdown', 'rmi', 'rmi-up', 'rmi-down-trend', 'sroc', 'ssl-dir', 'candle-up', and 'candle-down-trend'.
In the populate_entry_trend method: It defines different conditions for potential entry points for trades based on various indicators and their values.
It checks these conditions and assigns a tag to each potential entry point in the 'enter_tag' column of the dataframe. In the populate_exit_trend method: It initializes the 'exit_short' and 'exit_tag' columns as 0 and 'short_out', respectively. It initializes the 'exit_long' and 'exit_tag' columns as 0 and 'long_out', respectively. The proposed_leverage method: It takes certain inputs and returns the value of self.leverage_num.value. The custom_stoploss method: It calculates the trade duration and checks the current profit of a trade. It applies a custom stop-loss strategy based on certain conditions and returns a stop-loss percentage. The custom_sell method: It calculates the trade duration, maximum profit, and pullback value. It applies a custom selling strategy based on certain conditions and returns a sell signal. Overall, the strategy uses a combination of indicators and predefined conditions to generate potential entry and exit points for trades, as well as custom stop-loss and selling strategies.
It performs certain calculations and comparisons to determine the values of other columns, such as 'bigup', 'bigdown', 'trend', 'preparechangetrend', 'continueup', 'delta', 'slowingdown', 'rmi', 'rmi-up', 'rmi-down-trend', 'sroc', 'ssl-dir', 'candle-up', and 'candle-down-trend'.
In the populate_entry_trend method: It defines different conditions for potential entry points for trades based on various indicators and their values.
It checks these conditions and assigns a tag to each potential entry point in the 'enter_tag' column of the dataframe. In the populate_exit_trend method: It initializes the 'exit_short' and 'exit_tag' columns as 0 and 'short_out', respectively. It initializes the 'exit_long' and 'exit_tag' columns as 0 and 'long_out', respectively. The proposed_leverage method: It takes certain inputs and returns the value of self.leverage_num.value. The custom_stoploss method: It calculates the trade duration and checks the current profit of a trade. It applies a custom stop-loss strategy based on certain conditions and returns a stop-loss percentage. The custom_sell method: It calculates the trade duration, maximum profit, and pullback value. It applies a custom selling strategy based on certain conditions and returns a sell signal. Overall, the strategy uses a combination of indicators and predefined conditions to generate potential entry and exit points for trades, as well as custom stop-loss and selling strategies.
stoploss: -0.99 timeframe: 5m hash(sha256): 3933e10110154de0f6de58e36e7c345b6ebe7852273721b92b21eac5e05b3be0 indicators: static decay step preparechangetrend candledowntrend close zema lowsma emaDec exit_long exit_tag roc time any none ema1 maxdown delta candleup ema90 smaHigh trend btc_usdt_ema90_1d ATR minusdi sslDown maxup slowingdown continueup open hlv low_change highsma slowsma rmi smaLow close_change high sslUp high_change bigdown ssldir emarsi bigup hadtrend btc_usdt_close_1d sroc ema2 minusdiema adx plusdi fastsma preparechangetrendconfirm rmi ssl candle any none rsi enter_long enter_tag rmiup rmidowntren
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last change: 2024-11-01 23:43:34