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Strategy: Persia
Downloaded: 20220113
Stoploss: -0.19


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The Persia strategy is a backtesting strategy implemented as a class in Python. It has three main methods: populate_indicators, populate_buy_trend, and populate_sell_trend. In the populate_indicators method, the strategy calculates various technical indicators based on the input dataframe using the ta library.

The indicators are calculated for different timeframes, specified in the timeframes list.

The calculated indicators are added as new columns to the dataframe.

The populate_buy_trend method populates the buy signals of the strategy. It iterates over a number of conditions specified by CONDITIONS. For each condition, it retrieves the indicator, crossed indicator, timeframe, crossed timeframe, and formula values from the corresponding attributes of the class. It creates a DataFrame df using the retrieved values and evaluates the formula to determine if the condition is met. If any of the conditions are met, the corresponding rows in the dataframe are marked with a value of 1 in the 'buy' column. The populate_sell_trend method is similar to the populate_buy_trend method but is used to populate the sell signals of the strategy. It iterates over the conditions specified by CONDITIONS and evaluates the formula to determine if the conditions are met. If any of the conditions are met, the corresponding rows in the dataframe are marked with a value of 1 in the 'sell' column. Overall, the Persia strategy calculates technical indicators for different timeframes and generates buy and sell signals based on predefined conditions and formulas.

stoploss: -0.19
timeframe: 5m
hash(sha256): 33ccafd6fae4d8191d8c3dd957cd21b300833457c0aca9c4d00aa1260ce249e6
indicators:
indicatortf_idx SMA EMA TEMA DEMA

No similar strategies found. (based on used indicators)

last change: 2024-04-29 02:35:00