The NostalgiaForInfinityNextGen strategy is a backtesting strategy for trading. It performs several tasks to populate indicators and determine buy signals. Here's a breakdown of what the strategy does:
Populating Indicators:
The strategy fetches Bitcoin (BTC) price data at different timeframes (5 minutes, 1 hour, and daily) and merges it with the main dataframe.
It calculates various indicators for each timeframe, such as moving averages (EMA and SMA), volume, and price levels.
The strategy removes unnecessary columns from the dataframe.
Informative Timeframe: The strategy checks if an informative timeframe (1 day or 1 hour) is specified. If so, it calculates informative indicators for that timeframe and merges them with the main dataframe. It removes unnecessary columns from the dataframe. Resampled Timeframe: The strategy checks if a resampled timeframe is specified. If so, it resamples the dataframe to the specified timeframe and calculates resampled indicators. The resampled data is merged with the main dataframe, and the column names are adjusted. Unnecessary columns related to the resampled timeframe are removed. Normal Timeframe Indicators: The strategy calculates additional indicators for the normal timeframe (5 minutes) on the main dataframe. These indicators can include exponential moving averages (EMA), simple moving averages (SMA), and percentage changes. Populating Buy Trend: The strategy defines conditions for determining buy signals. It iterates through a set of buy protection parameters and evaluates various conditions based on these parameters. Conditions can include checks on moving averages, close price levels, rising trends, and safe dips/pumps. If a condition is met, the corresponding item in the buy protection list is set to True. A 'buy_tag' column is added to the dataframe to mark buy signals. The strategy performs these steps to populate indicators and generate buy signals for backtesting trading strategies.
It calculates various indicators for each timeframe, such as moving averages (EMA and SMA), volume, and price levels.
The strategy removes unnecessary columns from the dataframe.
Informative Timeframe: The strategy checks if an informative timeframe (1 day or 1 hour) is specified. If so, it calculates informative indicators for that timeframe and merges them with the main dataframe. It removes unnecessary columns from the dataframe. Resampled Timeframe: The strategy checks if a resampled timeframe is specified. If so, it resamples the dataframe to the specified timeframe and calculates resampled indicators. The resampled data is merged with the main dataframe, and the column names are adjusted. Unnecessary columns related to the resampled timeframe are removed. Normal Timeframe Indicators: The strategy calculates additional indicators for the normal timeframe (5 minutes) on the main dataframe. These indicators can include exponential moving averages (EMA), simple moving averages (SMA), and percentage changes. Populating Buy Trend: The strategy defines conditions for determining buy signals. It iterates through a set of buy protection parameters and evaluates various conditions based on these parameters. Conditions can include checks on moving averages, close price levels, rising trends, and safe dips/pumps. If a condition is met, the corresponding item in the buy protection list is set to True. A 'buy_tag' column is added to the dataframe to mark buy signals. The strategy performs these steps to populate indicators and generate buy signals for backtesting trading strategies.
stoploss: -0.5 timeframe: 15m hash(sha256): b19ddf6f8e48637ee4c0b32ed56712c4d32bd4f8cfb9d0880026a21480a757ec indicators: sma_200_1h upper open_sha_1d close res1 low_s ema_25 ema_200_1h ewo sma200_rising_val r_480_1h volume sma_200_dec_20 sup_level_1h f"global_buy_protection_paramsclose_under_pivot_type_1d tg_dataframe hl_pct_change_6 ema_20 ewo_ema_1h momdiv_coh hl_pct_change_48_1h rsi_14 high top_grossing_updated close_sha_1d hl_pct_change_36_1h tpct_change_2 close_over_pivot_offset r_480 cci sup_level_1d crossed_below_ema_12_26 vma_20 openclosehighlow bb20_2_mid momdiv_col ema_12 tpct_change_12 btc_not_downtrend
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last change: 2024-05-02 20:01:45