You will be redirected to the original Strategy in 15 seconds.
The S07 strategy is a backtesting strategy that calculates and populates indicators based on specified conditions for buying and selling. Here's a breakdown of how it works:
populate_indicators method: This method is responsible for calculating indicators for all time periods and optimizing the strategy. However, in this particular strategy, the indicators are only calculated within the buy and sell strategy populator methods when needed.
The populate_indicators method mainly calculates default values of hyperoptable parameters, but it doesn't provide significant benefits compared to calculating usable things inside the buy and sell trend populators.
populate_buy_trend method: This method populates the buy trend by evaluating multiple conditions.
It retrieves the values of indicators, crossed indicators, operators, and real numbers for buying from specific variables (e.g., buy_indicator0, buy_crossed_indicator0, etc.). It then generates a condition using the condition_generator function and appends it to the list of conditions. This process is repeated for each set of indicators (up to three sets in this case). If there are any conditions, the strategy marks the corresponding rows in the dataframe as a buy signal. populate_sell_trend method: This method populates the sell trend by following a similar process as the populate_buy_trend method. It retrieves the values of indicators, crossed indicators, operators, and real numbers for selling from specific variables (e.g., sell_indicator0, sell_crossed_indicator0, etc.). It generates conditions using the condition_generator function and appends them to the list of conditions. This process is repeated for each set of indicators (up to three sets). If there are any conditions, the strategy marks the corresponding rows in the dataframe as a sell signal. In summary, the S07 strategy calculates and populates indicators based on specified conditions for buying and selling. It evaluates multiple sets of indicators and conditions, marking the corresponding rows in the dataframe as buy or sell signals if the conditions are met.
The populate_indicators method mainly calculates default values of hyperoptable parameters, but it doesn't provide significant benefits compared to calculating usable things inside the buy and sell trend populators.
populate_buy_trend method: This method populates the buy trend by evaluating multiple conditions.
It retrieves the values of indicators, crossed indicators, operators, and real numbers for buying from specific variables (e.g., buy_indicator0, buy_crossed_indicator0, etc.). It then generates a condition using the condition_generator function and appends it to the list of conditions. This process is repeated for each set of indicators (up to three sets in this case). If there are any conditions, the strategy marks the corresponding rows in the dataframe as a buy signal. populate_sell_trend method: This method populates the sell trend by following a similar process as the populate_buy_trend method. It retrieves the values of indicators, crossed indicators, operators, and real numbers for selling from specific variables (e.g., sell_indicator0, sell_crossed_indicator0, etc.). It generates conditions using the condition_generator function and appends them to the list of conditions. This process is repeated for each set of indicators (up to three sets). If there are any conditions, the strategy marks the corresponding rows in the dataframe as a sell signal. In summary, the S07 strategy calculates and populates indicators based on specified conditions for buying and selling. It evaluates multiple sets of indicators and conditions, marking the corresponding rows in the dataframe as buy or sell signals if the conditions are met.
stoploss: -0.128 timeframe: 4h hash(sha256): 2be4cd8c72322aed48d76dacd2466e2379e7f42e70ed9f4f7e07dd474cd46947
Was not able to fetch indicators from Strategyfile.
last change: 2023-02-05 17:23:31