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The Uptrend strategy is a trading strategy that aims to identify and take advantage of upward trends in the market. Here's a breakdown of what the strategy does:
populate_indicators function:
Calculates the average of the high and low prices (hl2) for each data point. Computes the MESA Adaptive Moving Average (MAMA) and the Fractal Adaptive Moving Average (FAMA) based on the hl2 values.
Calculates the difference between MAMA and FAMA (mama_diff) and the ratio of mama_diff to hl2 (mama_diff_ratio).
Adds a column of zeros (zero).
Calculates the Relative Strength Index (RSI) based on the closing prices. Computes the 50-day exponential moving average (EMA50) and the 200-day exponential moving average (EMA200) of the closing prices. Returns the updated dataframe with the added indicators. populate_buy_trend function: Identifies buy signals based on specific conditions: RSI is less than 80. MAMA is greater than FAMA, indicating an uptrend. mama_diff_ratio is greater than 0.04. Volume is greater than 0. Sets the 'buy' column to 1 for the data points that meet the buy conditions. Returns the updated dataframe. populate_sell_trend function: Identifies sell signals based on the condition that mama_diff_ratio is less than 0.01 and volume is greater than 0. Sets the 'sell' column to 1 for the data points that meet the sell conditions. Returns the updated dataframe. The SuperBuy class extends the Uptrend strategy and introduces additional functionality. It overrides the populate_buy_trend function to generate a "super buy" signal based on specific conditions. The conditions vary depending on the runmode configuration. In the 'backtest' mode, common buy tags are obtained from the parent strategy and used to filter the data. In the 'hyperopt' mode, new buy signals are tested based on additional checks and conditions. Please note that the code provided is a simplified representation of the strategy, and there may be additional details and considerations not mentioned in the description.
Calculates the difference between MAMA and FAMA (mama_diff) and the ratio of mama_diff to hl2 (mama_diff_ratio).
Adds a column of zeros (zero).
Calculates the Relative Strength Index (RSI) based on the closing prices. Computes the 50-day exponential moving average (EMA50) and the 200-day exponential moving average (EMA200) of the closing prices. Returns the updated dataframe with the added indicators. populate_buy_trend function: Identifies buy signals based on specific conditions: RSI is less than 80. MAMA is greater than FAMA, indicating an uptrend. mama_diff_ratio is greater than 0.04. Volume is greater than 0. Sets the 'buy' column to 1 for the data points that meet the buy conditions. Returns the updated dataframe. populate_sell_trend function: Identifies sell signals based on the condition that mama_diff_ratio is less than 0.01 and volume is greater than 0. Sets the 'sell' column to 1 for the data points that meet the sell conditions. Returns the updated dataframe. The SuperBuy class extends the Uptrend strategy and introduces additional functionality. It overrides the populate_buy_trend function to generate a "super buy" signal based on specific conditions. The conditions vary depending on the runmode configuration. In the 'backtest' mode, common buy tags are obtained from the parent strategy and used to filter the data. In the 'hyperopt' mode, new buy signals are tested based on additional checks and conditions. Please note that the code provided is a simplified representation of the strategy, and there may be additional details and considerations not mentioned in the description.
startup_candle_count : 200 mama_diff: -0.001% mama_diff_ratio: -0.001%
stoploss: -0.1 timeframe: 5m hash(sha256): db33d69c36222899fc489a2b77eca0f05c4e06969b26e9d205e272910e2dbd9f indicators: best_point_percent close shifted_index bad_point_percent res1 rsi_fast_lower_20 ema_26_lin zero select_parameter_if_in_more_than_x_percent_of_best_points part_of_best_points_percent ema_50_lin volume higher_high_close_ratio buy_rsi_uplimit itemcolumn not_res1_1h min_close_hh_ratio r_14_lower_minus_80 fama select_prameter_if_prop_is_x_percent_higher_in_best_points " left_elt " value mama_diff_ratio candles_after_dip_to_buy sma_15 ema_50_1h hl2 high higher_high bad_points ratio_dif " column "
No similar strategies found. (based on used indicators)
last change: 2023-07-05 12:14:19