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Zeus Strategy is a trading strategy designed for backtesting purposes. It is the first generation of the GodStra Strategy and aims to maximize the average and mid profit in USDT. The strategy is authored by @Mablue (Masoud Azizi) and can be found on GitHub at https://github.com/mablue/.
To run the strategy, it is important to install the "ta" library before execution.
The strategy utilizes various libraries such as pandas, ta, qtpylib, and numpy for data manipulation and technical analysis calculations.
The strategy, named Zeus1, implements specific parameters for buying and selling. The buy parameters include a categorical parameter ("buy_cat") and a real parameter ("buy_real"). The sell parameters include a categorical parameter ("sell_cat") and a real parameter ("sell_real"). These parameters determine the conditions for executing buy and sell orders based on comparison operators and predefined values. Additionally, the strategy defines a minimal return on investment (ROI) table, which specifies the target returns at different time intervals. It also sets a stop loss value to limit potential losses. The strategy uses the 4-hour timeframe for analyzing market data. It implements technical indicators such as the Ichimoku Base Line and the Know Sure Thing (KST) indicator. The populate_indicators() function calculates these indicators and normalizes their values. The populate_buy_trend() and populate_sell_trend() functions define the buying and selling conditions based on the calculated indicators and the predefined parameters. Overall, the Zeus Strategy aims to optimize trading decisions by utilizing technical analysis indicators and predefined parameters for buying and selling. It is designed for backtesting trading strategies on a website.
To run the strategy, it is important to install the "ta" library before execution.
The strategy utilizes various libraries such as pandas, ta, qtpylib, and numpy for data manipulation and technical analysis calculations.
The strategy, named Zeus1, implements specific parameters for buying and selling. The buy parameters include a categorical parameter ("buy_cat") and a real parameter ("buy_real"). The sell parameters include a categorical parameter ("sell_cat") and a real parameter ("sell_real"). These parameters determine the conditions for executing buy and sell orders based on comparison operators and predefined values. Additionally, the strategy defines a minimal return on investment (ROI) table, which specifies the target returns at different time intervals. It also sets a stop loss value to limit potential losses. The strategy uses the 4-hour timeframe for analyzing market data. It implements technical indicators such as the Ichimoku Base Line and the Know Sure Thing (KST) indicator. The populate_indicators() function calculates these indicators and normalizes their values. The populate_buy_trend() and populate_sell_trend() functions define the buying and selling conditions based on the calculated indicators and the predefined parameters. Overall, the Zeus Strategy aims to optimize trading decisions by utilizing technical analysis indicators and predefined parameters for buying and selling. It is designed for backtesting trading strategies on a website.
stoploss: -0.99 timeframe: 4h hash(sha256): c59f3a8df681b59469a4b698e5df20e8e18b2ed7108c34a37fc46f066e03e700 indicators: high trend_ichimoku_base trend_kst_dif close low trend_kst_diff
No similar strategies found. (based on used indicators)
last change: 2024-04-29 13:03:19