Strategy: BinMfiBTCv4
Downloaded: 20220113
Stoploss: -0.095

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The BinMfiBTCv4 strategy is designed for backtesting trading strategies on a website. Here's a breakdown of what the strategy does: populate_indicators: This function calculates various technical indicators based on the input dataframe, such as Bollinger Bands, Moving Average Convergence Divergence (MACD), Money Flow Index (MFI), Relative Strength Index (RSI), and others. It returns the modified dataframe with these additional indicators.

populate_buy_trend: This function determines the conditions for entering a "buy" trade.

It uses different parameters to define both loose and strict conditions for entering a trade.

The conditions include checking the presence of a bullish or bearish trend, MFI values, Bollinger Bands, closing price changes, and other factors. If any of the defined conditions are met, the function sets the corresponding row in the "buy" column of the dataframe to 1. populate_sell_trend: This function prepares the dataframe for the sell trend analysis by initializing the "sell" column with 0 values. It doesn't perform any specific calculations or conditions for selling. should_sell: This method determines whether a sell trade should be executed based on certain conditions. It receives parameters such as the trading pair, time frame, sell reason, and additional arguments. If the sell reason is "roi" (return on investment), it checks the values of RSI, EWO, and closing prices to decide whether to sell or not. Overall, the strategy uses a combination of technical indicators and predefined conditions to generate "buy" signals, while the selling decision depends on various factors such as ROI, RSI, and EWO.

stoploss: -0.095
timeframe: 5m
hash(sha256): 2593f1bd5399e9d615186e5fb4213e2973562523f4f636dbb1a10fc98e35dbc9
3close EWO close btc_sma_delta tail
mfi bbdelta closedelta bear_100 sma100
bull_100 hl2 high lower sma25
btcroc rsi low date open
high low close volume

Similar Strategies: (based on used indicators)

Strategy: BinMfiBTCv42, Similarity Score: 88%

last change: 2023-07-01 16:17:33