The given code represents a trading strategy called "emacrossover" that can be used for backtesting on a trading platform. Here's a breakdown of what the strategy does:
The strategy is based on the concept of exponential moving average (EMA) crossover, which involves comparing two different EMAs of a trading instrument's price data. The strategy uses four parameters: buy_fastema, buy_slowema, sell_fastema, and sell_slowema.
These parameters represent the time periods for calculating the EMAs used in the strategy.
The strategy has a predefined minimal ROI (Return on Investment) table, which specifies the expected returns at different time intervals.
For example, after 0 time units, the expected ROI is 0.16412. The strategy also has a stop loss value of -0.32523, which indicates the maximum acceptable loss before exiting a trade. The timeframe used for the strategy is set to 15 minutes. The strategy has two main functions: populate_buy_trend and populate_sell_trend. These functions are responsible for generating buy and sell signals based on the specified conditions. In the populate_buy_trend function, the strategy checks if the fast EMA is greater than the slow EMA. If this condition is met, a buy signal is generated. In the populate_sell_trend function, the strategy checks if the fast EMA is less than the slow EMA. If this condition is met, a sell signal is generated. Both functions modify the input dataframe by adding a 'buy' or 'sell' column with binary values (1 indicating a signal and 0 indicating no signal) based on the specified conditions. Overall, the emacrossover strategy aims to identify potential entry and exit points for trades based on the crossover of exponential moving averages.
These parameters represent the time periods for calculating the EMAs used in the strategy.
The strategy has a predefined minimal ROI (Return on Investment) table, which specifies the expected returns at different time intervals.
For example, after 0 time units, the expected ROI is 0.16412. The strategy also has a stop loss value of -0.32523, which indicates the maximum acceptable loss before exiting a trade. The timeframe used for the strategy is set to 15 minutes. The strategy has two main functions: populate_buy_trend and populate_sell_trend. These functions are responsible for generating buy and sell signals based on the specified conditions. In the populate_buy_trend function, the strategy checks if the fast EMA is greater than the slow EMA. If this condition is met, a buy signal is generated. In the populate_sell_trend function, the strategy checks if the fast EMA is less than the slow EMA. If this condition is met, a sell signal is generated. Both functions modify the input dataframe by adding a 'buy' or 'sell' column with binary values (1 indicating a signal and 0 indicating no signal) based on the specified conditions. Overall, the emacrossover strategy aims to identify potential entry and exit points for trades based on the crossover of exponential moving averages.
stoploss: -0.325 timeframe: 15m hash(sha256): 55926ec1836c80e07dda8864498257dbe7aea82aceb71b6bdeb97f892a1a8c1f
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last change: 2024-04-28 04:33:53