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The "NostalgiaForInfinityNext" strategy is a trading strategy that involves populating indicators and determining buy trends for trading. Here is a breakdown of what the strategy does:
Populating Indicators:
The strategy retrieves data for the BTC (Bitcoin) pair in different timeframes (5 minutes, 1 hour, 1 day) depending on the stake currency. Various indicators are calculated and added to the dataframes, such as moving averages (EMA and SMA), volume, and price-related indicators.
The strategy merges the informative dataframes with the main dataframe, filling missing values and dropping unnecessary columns.
Resampling to a different timeframe (if specified) is performed, and the resampled indicators are added to the main dataframe.
Determining Buy Trends: Conditions for buying are defined based on user-configurable parameters. The strategy iterates over the defined buy protection parameters and evaluates multiple conditions for each parameter. The conditions include comparisons between different indicators (EMA, close price, SMA) and predefined thresholds. Additional conditions related to safe dips, safe pumps, BTC trend, and pivot points are considered. Buy tags are assigned to the data points that meet the specified conditions. The strategy aims to provide a systematic approach to backtesting trading strategies by generating indicators and identifying potential buy trends based on specified conditions.
The strategy merges the informative dataframes with the main dataframe, filling missing values and dropping unnecessary columns.
Resampling to a different timeframe (if specified) is performed, and the resampled indicators are added to the main dataframe.
Determining Buy Trends: Conditions for buying are defined based on user-configurable parameters. The strategy iterates over the defined buy protection parameters and evaluates multiple conditions for each parameter. The conditions include comparisons between different indicators (EMA, close price, SMA) and predefined thresholds. Additional conditions related to safe dips, safe pumps, BTC trend, and pivot points are considered. Buy tags are assigned to the data points that meet the specified conditions. The strategy aims to provide a systematic approach to backtesting trading strategies by generating indicators and identifying potential buy trends based on specified conditions.
stoploss: -0.5 timeframe: 5m hash(sha256): ec92980caa22854f9a16c64c273eb7f5216bde53a6b5755cc756eea6caf8f3d8 indicators: sma_200_1h upper safe_pump_type safe_pump_24_30 leading_senkou_span_b_1h close ema_15 res1 senkou_a sell_pump_36_2 sell_pump_24_1_1h sma_5 low_s safe_pump_period ema_25 ema_200_1h tenkan_sen 39 sma200_rising_val r_480_1h safe_pump_24_100 volume rsi_4 sma_200_dec_20 leading_senkou_span_a f"global_buy_protection_paramsclose_under_pivot_type_1d 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 to
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last change: 2023-08-16 00:04:53