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The "PumpDetector" strategy is a backtesting strategy that aims to detect potential pump and dump scenarios in trading. Here's a breakdown of what the strategy does:
populate_indicators: This function calculates various indicators based on the input dataframe. These indicators include:
var1: The previous day's low price.
var1_abs: The absolute difference between the current day's low price and the previous day's low price.
var1_max: The positive difference between the current day's low price and the previous day's low price.
var2_test: A function called xsa is applied to var1_abs to calculate a modified version of it. var2: The ratio of var2_test to var1_max, multiplied by 100. var2_10: var2 multiplied by 10. var3: Exponential moving average (EMA) of var2_10 with a time period of 3. var4: The minimum value of the low price over a rolling window of 38 days. var5: The maximum value of var3 over a rolling window of 38 days. var6: A constant value of 1. var7_data: If the low price is less than or equal to var4, the average of var3 and twice var5 divided by 2; otherwise, 0. var7: EMA of var7_data with a time period of 3, divided by 618 and multiplied by var3. var8: The percentage of the difference between the close price and the minimum low price over a rolling window of 21 days, divided by the difference between the maximum high price and the minimum low price over the same window, multiplied by 100. var9: Another modified version of var8 calculated using the function xsa. populate_buy_trend: This function populates the "buy" column of the dataframe based on specific conditions. It sets the value to 1 if the following conditions are met: The value of j (calculated in the populate_indicators function) crosses above 0. The volume is greater than 0. populate_sell_trend: This function populates the "sell" column of the dataframe based on specific conditions. It sets the value to 1 if the following conditions are met: Either j crosses above 90 or j crosses below k and j is greater than 50. The volume is greater than 0. Overall, the strategy uses various indicators and their relationships to identify potential buying and selling signals based on the concept of detecting pump and dump activities.
var1_abs: The absolute difference between the current day's low price and the previous day's low price.
var1_max: The positive difference between the current day's low price and the previous day's low price.
var2_test: A function called xsa is applied to var1_abs to calculate a modified version of it. var2: The ratio of var2_test to var1_max, multiplied by 100. var2_10: var2 multiplied by 10. var3: Exponential moving average (EMA) of var2_10 with a time period of 3. var4: The minimum value of the low price over a rolling window of 38 days. var5: The maximum value of var3 over a rolling window of 38 days. var6: A constant value of 1. var7_data: If the low price is less than or equal to var4, the average of var3 and twice var5 divided by 2; otherwise, 0. var7: EMA of var7_data with a time period of 3, divided by 618 and multiplied by var3. var8: The percentage of the difference between the close price and the minimum low price over a rolling window of 21 days, divided by the difference between the maximum high price and the minimum low price over the same window, multiplied by 100. var9: Another modified version of var8 calculated using the function xsa. populate_buy_trend: This function populates the "buy" column of the dataframe based on specific conditions. It sets the value to 1 if the following conditions are met: The value of j (calculated in the populate_indicators function) crosses above 0. The volume is greater than 0. populate_sell_trend: This function populates the "sell" column of the dataframe based on specific conditions. It sets the value to 1 if the following conditions are met: Either j crosses above 90 or j crosses below k and j is greater than 50. The volume is greater than 0. Overall, the strategy uses various indicators and their relationships to identify potential buying and selling signals based on the concept of detecting pump and dump activities.
startup_candle_count : 30 var2_test: -0.725% var2: -0.436% var2_10: -0.436% var9: -100.000% k: -100.000% d: -100.000% j: -100.000%
stoploss: -0.99 timeframe: 5m hash(sha256): ff86bb0709fad24ece4c18b60e2eb886bd1f3570ee5968f6527a9e4a3964663b indicators: var1_abs var6 close var2_10 volume retxsa var1 var9 var7_data rsv high var2 var3 var8 var1_max var2_test var7 var4 low var5
Similar Strategies: (based on used indicators)
Strategy: PD, Similarity Score: 95.24%
last change: 2023-07-04 00:07:03