The given code snippet represents a trading strategy implemented as a class called "tesla" that follows the IStrategy interface. Here is a short description of what the strategy does:
The strategy consists of two main methods: "populate_indicators" and "populate_buy_trend" as well as a third method "populate_sell_trend."
populate_indicators: This method is responsible for calculating and populating various indicators based on the provided input dataframe and metadata. It merges informative data from a 15-minute timeframe with the current timeframe, filling any missing values.
populate_buy_trend: This method identifies potential buying opportunities based on several conditions.
It first defines a list of conditions under the variable "dont_buy_conditions" that should not trigger a buy.
Then, it uses various indicators such as RSI (Relative Strength Index), moving averages, and volume to determine when to initiate a buy signal. Multiple conditions are checked, and if met, the "buy" and "buy_tag" columns in the dataframe are updated accordingly. populate_sell_trend: This method determines the selling points based on a set of conditions. It checks indicators such as moving averages, RSI, and volume to identify when to initiate a sell signal. Multiple conditions are checked, and if met, the "sell" column in the dataframe is updated. It's important to note that this description provides a general overview of the strategy's functionality. The specific logic and parameter values used in the strategy would require further examination for a comprehensive understanding.
populate_buy_trend: This method identifies potential buying opportunities based on several conditions.
It first defines a list of conditions under the variable "dont_buy_conditions" that should not trigger a buy.
Then, it uses various indicators such as RSI (Relative Strength Index), moving averages, and volume to determine when to initiate a buy signal. Multiple conditions are checked, and if met, the "buy" and "buy_tag" columns in the dataframe are updated accordingly. populate_sell_trend: This method determines the selling points based on a set of conditions. It checks indicators such as moving averages, RSI, and volume to identify when to initiate a sell signal. Multiple conditions are checked, and if met, the "sell" column in the dataframe is updated. It's important to note that this description provides a general overview of the strategy's functionality. The specific logic and parameter values used in the strategy would require further examination for a comprehensive understanding.
startup_candle_count : 200 hma_50: -0.001% ema_100: 0.014% rsi_slow: 0.002%
stoploss: -0.15 timeframe: 5m hash(sha256): e989d504632d2ec5946c86b0c6a81fb458a7186eec7b3c4c5c617f30353646f1 indicators: rsi_buy sell_custom_stoploss_under_rel_1 EWO sell_custom_stoploss_under_rsi_diff_1 ewo_high ema_200 ewo_low high_offset_2 close sell_custom_under_rsi_2 ewo_high_2 sell_custom_dec_profit_2 sell_signal profit_threshold rsi_fast ma_sell_val ma_buy_val sell_custom_under_profit_3 volume sell_custom_rsi_2 sell_custom_dec_profit_1 sell_custom_under_rsi_1 low_offset retries sell_custom_under_rsi_3 high_offset low_offset_2 base_nb_candles_buy sell_trail_profit_max_1 sma_200 sell_trail_profit_min_2 rsi_fa
Similar Strategies: (based on used indicators)
Strategy: akiva6, Similarity Score: 93.94%
Strategy: AV6_Fix, Similarity Score: 87.88%
last change: 2024-05-02 23:58:38