Not Enough Data to display!
Average Overall
| Not Enough Data! / Avg statistics not populated yet. |
|---|
The "DoesNothing" strategy is a simple skeleton strategy that doesn't perform any actual trading. It serves as a basic template or starting point for developing more complex trading strategies. The strategy has the following key components:
Minimal ROI: The strategy defines a minimal return on investment (ROI) of 0.01, indicating that it aims for a minimum profit of 1%.
This value can be adjusted based on market conditions.
Stoploss: The strategy sets a stoploss of -0.25, indicating that if a trade's value drops by 25%, it will trigger a sell order to limit potential losses.
Timeframe: The strategy operates on a 1-hour timeframe, meaning it analyzes price data and makes trading decisions based on hourly intervals. populate_indicators(): This function is responsible for populating any additional technical indicators that the strategy may require. However, in this case, it doesn't implement any specific indicators and simply returns the input dataframe unchanged. populate_buy_trend(): This function is responsible for identifying buy signals in the market. However, in this strategy, it doesn't implement any specific conditions for buying and simply sets the 'buy' column to 1 for all rows in the dataframe. populate_sell_trend(): This function is responsible for identifying sell signals in the market. Similar to the buy trend function, it doesn't implement any specific conditions for selling and sets the 'sell' column to 1 for all rows in the dataframe. Overall, this strategy is a basic framework that can be customized and built upon to create more sophisticated trading strategies.
This value can be adjusted based on market conditions.
Stoploss: The strategy sets a stoploss of -0.25, indicating that if a trade's value drops by 25%, it will trigger a sell order to limit potential losses.
Timeframe: The strategy operates on a 1-hour timeframe, meaning it analyzes price data and makes trading decisions based on hourly intervals. populate_indicators(): This function is responsible for populating any additional technical indicators that the strategy may require. However, in this case, it doesn't implement any specific indicators and simply returns the input dataframe unchanged. populate_buy_trend(): This function is responsible for identifying buy signals in the market. However, in this strategy, it doesn't implement any specific conditions for buying and simply sets the 'buy' column to 1 for all rows in the dataframe. populate_sell_trend(): This function is responsible for identifying sell signals in the market. Similar to the buy trend function, it doesn't implement any specific conditions for selling and sets the 'sell' column to 1 for all rows in the dataframe. Overall, this strategy is a basic framework that can be customized and built upon to create more sophisticated trading strategies.
stoploss: -0.25 timeframe: 1h hash(sha256): 4f2a3ead0c2d45babe4ef33bf3fc90eafb636a25a6055d0aa53036a8bd93c4e0
Was not able to fetch indicators from Strategyfile.
last change: 2023-06-30 12:09:54