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The Nemesis4 strategy is a trading strategy that involves the use of various indicators for decision-making. Here is a brief description of what the strategy does:
In the populate_indicators method:
The MACD (Moving Average Convergence Divergence) indicator is calculated and its components (macd, macdsignal, macdhist) are added to the dataframe. The minimum closing price of the last 500 periods is stored in the columns 0 and a.
The difference between a and 0 is calculated and stored in the column diff0A.
The values of diff0A are multiplied by different constants (0.5, 0.441, 0.382, 0.233) and stored in columns 500gkl, 559gkl, 618gkl, 667gkl, respectively.
Several other columns (b, c, zl1618, zl1809, zl2, diffBC, 500bc, 559bc, 618bc, 667bc, sequenceActivated) are initialized with zeros or False. The modified dataframe is returned. In the populate_buy_trend method: The method checks if the current closing price is lower than the minimum closing price of the last 500 periods. If so, it updates the values of 0 and the gkl columns. It also checks if the current closing price is higher than the maximum closing price of the last 500 periods and if b is not set. If so, it updates the values of a, the gkl columns, and sets b. If the closing price is between 500gkl and 667gkl and b is not set, it sets b as the current closing price. If b is set and the closing price is lower than b, it updates b with the current closing price. If b is set and the closing price is higher than a, it sets sequenceActivated as True and calculates the values of c, zl1618, zl1809, and zl2 based on a, 0, and b. It also updates the bc columns. If the closing price is lower than b and higher than 667gkl, it sets sequenceActivated as False and updates b. Finally, if sequenceActivated is True and the closing price is less than or equal to 500bc, it sets the buy column as 1. The modified dataframe is returned. In the populate_sell_trend method: The method checks if the current closing price is higher than or equal to c. If so, it sets the sell column as 1. The modified dataframe is returned. Overall, the strategy uses indicators such as MACD and price levels (gkl) to identify potential buying opportunities (buy signal) and selling opportunities (sell signal) in the market.
The difference between a and 0 is calculated and stored in the column diff0A.
The values of diff0A are multiplied by different constants (0.5, 0.441, 0.382, 0.233) and stored in columns 500gkl, 559gkl, 618gkl, 667gkl, respectively.
Several other columns (b, c, zl1618, zl1809, zl2, diffBC, 500bc, 559bc, 618bc, 667bc, sequenceActivated) are initialized with zeros or False. The modified dataframe is returned. In the populate_buy_trend method: The method checks if the current closing price is lower than the minimum closing price of the last 500 periods. If so, it updates the values of 0 and the gkl columns. It also checks if the current closing price is higher than the maximum closing price of the last 500 periods and if b is not set. If so, it updates the values of a, the gkl columns, and sets b. If the closing price is between 500gkl and 667gkl and b is not set, it sets b as the current closing price. If b is set and the closing price is lower than b, it updates b with the current closing price. If b is set and the closing price is higher than a, it sets sequenceActivated as True and calculates the values of c, zl1618, zl1809, and zl2 based on a, 0, and b. It also updates the bc columns. If the closing price is lower than b and higher than 667gkl, it sets sequenceActivated as False and updates b. Finally, if sequenceActivated is True and the closing price is less than or equal to 500bc, it sets the buy column as 1. The modified dataframe is returned. In the populate_sell_trend method: The method checks if the current closing price is higher than or equal to c. If so, it sets the sell column as 1. The modified dataframe is returned. Overall, the strategy uses indicators such as MACD and price levels (gkl) to identify potential buying opportunities (buy signal) and selling opportunities (sell signal) in the market.
stoploss: -1 timeframe: 5m hash(sha256): f15975e8c9dc59519cf33cb7bb329d0b0c8857a1b74639bd970336aa4f9c3b24
Was not able to fetch indicators from Strategyfile.
last change: 2023-07-06 07:23:18