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The provided code represents a trading strategy implemented as a class called "Deneme" that inherits from the "IStrategy" class. Here's a brief description of what the strategy does:
The strategy has three main functions: "populate_indicators," "populate_buy_trend," and "populate_sell_trend."
populate_indicators function:
This function adds several technical analysis (TA) indicators to the given DataFrame, which contains data from the exchange. The indicators added include RSI (Relative Strength Index), Bollinger Bands, BB percent, BB width, SMA (Simple Moving Average) with a time period of 3, and SMA with a time period of 5.
The function returns the DataFrame with all the mandatory indicators for the strategies.
populate_buy_trend function: This function populates the buy signal for the given DataFrame based on the TA indicators.
The buy signal is determined by the following conditions: RSI crossing above a specified buy threshold. SMA3 (Simple Moving Average with a time period of 3) being below the BB (Bollinger Bands) middle band. SMA5 (Simple Moving Average with a time period of 5) being above the previous BB upper band. Volume being greater than 0. The function adds a "buy" column to the DataFrame, setting it to 1 for the rows that meet the buy signal conditions. The function returns the DataFrame with the added "buy" column. populate_sell_trend function: This function populates the sell signal for the given DataFrame based on the TA indicators. The sell signal is determined by the following conditions: RSI crossing above a specified sell threshold. SMA5 being above the BB upper band. RSI being greater than 50. Volume being greater than 0. The function adds a "sell" column to the DataFrame, setting it to 1 for the rows that meet the sell signal conditions. The function returns the DataFrame with the added "sell" column. Overall, this strategy uses various technical indicators such as RSI, Bollinger Bands, and moving averages to generate buy and sell signals based on specific conditions.
The function returns the DataFrame with all the mandatory indicators for the strategies.
populate_buy_trend function: This function populates the buy signal for the given DataFrame based on the TA indicators.
The buy signal is determined by the following conditions: RSI crossing above a specified buy threshold. SMA3 (Simple Moving Average with a time period of 3) being below the BB (Bollinger Bands) middle band. SMA5 (Simple Moving Average with a time period of 5) being above the previous BB upper band. Volume being greater than 0. The function adds a "buy" column to the DataFrame, setting it to 1 for the rows that meet the buy signal conditions. The function returns the DataFrame with the added "buy" column. populate_sell_trend function: This function populates the sell signal for the given DataFrame based on the TA indicators. The sell signal is determined by the following conditions: RSI crossing above a specified sell threshold. SMA5 being above the BB upper band. RSI being greater than 50. Volume being greater than 0. The function adds a "sell" column to the DataFrame, setting it to 1 for the rows that meet the sell signal conditions. The function returns the DataFrame with the added "sell" column. Overall, this strategy uses various technical indicators such as RSI, Bollinger Bands, and moving averages to generate buy and sell signals based on specific conditions.
stoploss: -0.1 timeframe: 1m hash(sha256): 705a8c0c9afd530301361dd70acdf2afcb1d9f403a3e34b51459df2281b7b3af indicators: sma5 bids upper mid lower volume asks bb_width bb_middleband rsi close bb_upperband bb_lowerband sma3 bb_percent best_ask best_bid
No similar strategies found. (based on used indicators)
last change: 2023-08-21 10:50:22