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The NfiNextModded strategy is designed to backtest trading strategies using various indicators and timeframes. Here is a brief description of what the strategy does:
It populates indicators for BTC (Bitcoin) using different timeframes (5 minutes, 1 hour, and daily). If the stake currency is a fiat currency, it retrieves informative BTC price data using the stake currency pair.
Otherwise, it uses BTC/USDT pair as the default.
It merges the informative BTC data with the strategy's main dataframe for the daily timeframe, removing duplicate columns.
If configured, it retrieves informative BTC price data for the strategy's timeframe (5 minutes) and merges it with the main dataframe, again removing duplicate columns. If configured, it retrieves informative BTC price data for the strategy's timeframe and indicators are calculated based on it. If configured, the strategy resamples the data to another timeframe and calculates indicators based on the resampled data. Finally, it calculates indicators for the normal timeframe (5 minutes) using the main dataframe. In terms of trading decisions: The populate_buy_trend method sets the 'buy' signal when the close price is less than or equal to the minimum of the previous low prices and the volume is greater than zero. The populate_sell_trend method does not set any 'sell' signal. The should_sell method is not implemented, so by default, it returns True (always confirming the sell order). Please note that this description provides a general overview of the strategy based on the code provided. Additional details may be present in other parts of the strategy that are not shown here.
Otherwise, it uses BTC/USDT pair as the default.
It merges the informative BTC data with the strategy's main dataframe for the daily timeframe, removing duplicate columns.
If configured, it retrieves informative BTC price data for the strategy's timeframe (5 minutes) and merges it with the main dataframe, again removing duplicate columns. If configured, it retrieves informative BTC price data for the strategy's timeframe and indicators are calculated based on it. If configured, the strategy resamples the data to another timeframe and calculates indicators based on the resampled data. Finally, it calculates indicators for the normal timeframe (5 minutes) using the main dataframe. In terms of trading decisions: The populate_buy_trend method sets the 'buy' signal when the close price is less than or equal to the minimum of the previous low prices and the volume is greater than zero. The populate_sell_trend method does not set any 'sell' signal. The should_sell method is not implemented, so by default, it returns True (always confirming the sell order). Please note that this description provides a general overview of the strategy based on the code provided. Additional details may be present in other parts of the strategy that are not shown here.
Biased Indicators
chikou_span_1h
stoploss: -0.5 timeframe: 5m hash(sha256): 5f128dbf53ffdd9e1fa7af3020e33e5f0c210d5712cd3afc27b8746c5c29c82c indicators: USDT BUSD USDC DAI TUSD PAX USD EUR GBP upper safe_pump_24_30 close ema_15 res1 senkou_a sell_pump_36_2 sell_pump_24_1_1h sma_5 low_s ema_25 tenkan_sen 39 safe_pump_24_100 volume rsi_4 sma_200_dec_20 leading_senkou_span_a senkou_a senkou_b safe_pump_24_120 tg_dataframe sell_pump_36_1_1h ema_20 source safe_pump_48_30 momdiv_coh oc_pct_change_48 rsi_14 sell_pump_48_1_1h high top_grossing_updated tpct_change_2 r_480 cci chikou_span sell_pump_48_3 safe_pump_48_10 crossed_below_ema_12_26 final_ub low
No similar strategies found. (based on used indicators)
last change: 2023-07-03 23:38:18