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The Scotty strategy is a trading strategy that uses various technical analysis indicators to make trading decisions. The strategy first populates the given DataFrame with different indicators, including Bollinger Bands, Stochastic Fast, RSI (Relative Strength Index), EMA (Exponential Moving Average), and others. The Bollinger Bands indicator is used to identify price volatility, with the lower and upper bands indicating potential support and resistance levels.
The Stochastic Fast indicator helps determine overbought and oversold conditions in the market.
The RSI measures the strength and speed of price movements.
The EMA is a type of moving average that gives more weight to recent price data. Additionally, the strategy creates supports by calculating the EMA of the typical price and using it to determine the Entry Support Averages (ESA) and Divergence Extension (DE). The strategy also calculates the Weighted Thermostat (WT) values based on the ESA and DE. The day of the week is recorded, and a zero value is added to the DataFrame. The strategy also includes custom logic for stop-loss and trade adjustment. The stop-loss logic calculates a stop-loss price based on the support level and a sell support margin percentage. If the stop-loss price is below the current rate, the strategy returns a new stop-loss value relative to the current rate. Otherwise, it returns 1, indicating no change to the stop-loss. The trade adjustment logic is used to determine the stake amount that should be increased or decreased for a trade. This allows for additional buy or sell orders with extra fees. The logic considers various parameters such as the current rate, profit, stake limits, and entry/exit pricing. If the strategy doesn't implement trade adjustment logic, it returns None. Overall, the Scotty strategy combines multiple indicators and custom logic to make trading decisions, including identifying support and resistance levels, overbought/oversold conditions, and potential profit-taking or stop-loss levels.
The Stochastic Fast indicator helps determine overbought and oversold conditions in the market.
The RSI measures the strength and speed of price movements.
The EMA is a type of moving average that gives more weight to recent price data. Additionally, the strategy creates supports by calculating the EMA of the typical price and using it to determine the Entry Support Averages (ESA) and Divergence Extension (DE). The strategy also calculates the Weighted Thermostat (WT) values based on the ESA and DE. The day of the week is recorded, and a zero value is added to the DataFrame. The strategy also includes custom logic for stop-loss and trade adjustment. The stop-loss logic calculates a stop-loss price based on the support level and a sell support margin percentage. If the stop-loss price is below the current rate, the strategy returns a new stop-loss value relative to the current rate. Otherwise, it returns 1, indicating no change to the stop-loss. The trade adjustment logic is used to determine the stake amount that should be increased or decreased for a trade. This allows for additional buy or sell orders with extra fees. The logic considers various parameters such as the current rate, profit, stake limits, and entry/exit pricing. If the strategy doesn't implement trade adjustment logic, it returns None. Overall, the Scotty strategy combines multiple indicators and custom logic to make trading decisions, including identifying support and resistance levels, overbought/oversold conditions, and potential profit-taking or stop-loss levels.
stoploss: -0.9 timeframe: 30m hash(sha256): 2fbc7b2220ed068f0e7c149aeb164d75968206011a77eb6991d55777cc063d98
Was not able to fetch indicators from Strategyfile.
last change: 2022-12-12 23:24:07