Strategy: Obelisk_Ichimoku_Slow_v1_3
Downloaded: 20220112
Stoploss: -0.99
Downloaded: 20220112
Stoploss: -0.99
Showing 1 to 12 of 72 entries
| Buys | Avg Prof% | Cum Prof% | Tot Profit% | Avg Duration | Win | Draw | Loss | Win% | DD% | Stake | Exchange | Sharpe | Month |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 20 | 0.31 | 6.24 | 1.44 | 1 day, 0:51:00 | 6 | 0 | 14 | 30 | 7.74 | USDT | kucoin | 0.49 | 202306 |
| 23 | -2.03 | -46.7 | -10.79 | 19:13:00 | 5 | 0 | 18 | 21.7 | 9.1 | USDT | kucoin | -7.75 | 202305 |
| 25 | -1.76 | -43.9 | -10.14 | 1 day, 2:36:00 | 3 | 0 | 22 | 12 | 10.02 | USDT | kucoin | -12.35 | 202304 |
| 12 | -4.92 | -59.07 | -13.65 | 17:55:00 | 0 | 0 | 12 | 0 | 13.43 | USDT | kucoin | -14.19 | 202303 |
| 14 | -0.6 | -8.43 | -1.95 | 1 day, 19:26:00 | 4 | 0 | 10 | 28.6 | 6.13 | USDT | kucoin | -1.04 | 202302 |
| 21 | 3.03 | 63.66 | 19.12 | 1 day, 14:11:00 | 8 | 0 | 13 | 38.1 | 6.08 | USDT | kucoin | 3.18 | 202301 |
| 17 | -0.91 | -15.51 | -4.66 | 1 day, 11:42:00 | 5 | 0 | 12 | 29.4 | 7.67 | USDT | kucoin | -2.46 | 202212 |
| 22 | 0.38 | 8.42 | 2.53 | 1 day, 7:22:00 | 8 | 0 | 14 | 36.4 | 8.7 | USDT | kucoin | 1.41 | 202211 |
| 22 | -0.84 | -18.4 | -5.52 | 1 day, 8:16:00 | 6 | 0 | 16 | 27.3 | 9.61 | USDT | kucoin | -1.87 | 202210 |
| 16 | -1.83 | -29.27 | -8.79 | 1 day, 13:38:00 | 5 | 0 | 11 | 31.2 | 7.84 | USDT | kucoin | -3.17 | 202209 |
| 21 | -2.44 | -51.31 | -15.41 | 1 day, 5:26:00 | 5 | 0 | 16 | 23.8 | 13.5 | USDT | kucoin | -2.83 | 202208 |
| 15 | 0.63 | 9.41 | 2.83 | 1 day, 16:48:00 | 4 | 0 | 11 | 26.7 | 6.42 | USDT | kucoin | 1.27 | 202207 |
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Average Overall
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The "Obelisk_Ichimoku_Slow_v1_3" strategy is an implementation of the Ichimoku indicator for backtesting trading strategies. Here is a short description of what the strategy does:
Populate Indicators: This method populates the indicators required for the strategy. If the current timeframe is the same as the informative timeframe, it calculates the indicators for the dataframe.
Otherwise, it requires a DataProvider for multiple timeframes and calculates the indicators for both the current and informative timeframes.
The informative dataframe is merged with the current dataframe, and unnecessary columns are removed.
Populate Buy Trend: This method determines the buy signals for the strategy. It sets the "buy" column to 1 when the following conditions are met: the "trending" indicator is greater than 0, the "entry_ok" indicator is greater than 0, and the minute of the hour is 0 (to set the signal only on the hour when backtesting at 5m/1m). Populate Sell Trend: This method determines the sell signals for the strategy. It sets the "sell" column to 1 when the "trending" indicator is equal to 0 and the minute of the hour is 0. The strategy also includes a "plot_config" dictionary that specifies the configuration for plotting the indicators and signals on a chart. It defines the colors and fill settings for the Ichimoku Cloud, as well as the colors for other indicators and signals in different subplots. Overall, the strategy utilizes the Ichimoku indicator and other indicators to generate buy and sell signals based on specific conditions, allowing for backtesting and analysis of trading performance.
Otherwise, it requires a DataProvider for multiple timeframes and calculates the indicators for both the current and informative timeframes.
The informative dataframe is merged with the current dataframe, and unnecessary columns are removed.
Populate Buy Trend: This method determines the buy signals for the strategy. It sets the "buy" column to 1 when the following conditions are met: the "trending" indicator is greater than 0, the "entry_ok" indicator is greater than 0, and the minute of the hour is 0 (to set the signal only on the hour when backtesting at 5m/1m). Populate Sell Trend: This method determines the sell signals for the strategy. It sets the "sell" column to 1 when the "trending" indicator is equal to 0 and the minute of the hour is 0. The strategy also includes a "plot_config" dictionary that specifies the configuration for plotting the indicators and signals on a chart. It defines the colors and fill settings for the Ichimoku Cloud, as well as the colors for other indicators and signals in different subplots. Overall, the strategy utilizes the Ichimoku indicator and other indicators to generate buy and sell signals based on specific conditions, allowing for backtesting and analysis of trading performance.
startup_candle_count : 20 cloud_red: -100.000% efi: -51.636% atr: -2.866% ssl_down: -1.769% ssl_up: 1.801% ssl_ok: inf% trend_over: -100.000%
Biased Indicators
chikou_span
stoploss: -0.99 timeframe: 1h hash(sha256): 01c172c42e2d1ef9259a363909d7349afd31ec7a55ab5d3d59f17020f989b83d indicators: ichimoku_ok close senkou_a efi_ok trending tenkan_sen ema_ok cloud_red entry_ok trend_over volume smaHigh ssl_ok chikou_high leading_senkou_span_a senkou_a senkou_b ssl_up sslDown date leading_senkou_span_b open hlv trend_pulse smaLow efi_base high sslUp kijun_sen efi senkou_span_a chikou_span senkou_b ssl_down senkou_span_b ema200 atr cloud_green low ema50 cloud_top future_green date open high low close volume
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Strategy: s10lchimoku_zema_hyper, Similarity Score: 75.51%
last change: 2023-07-05 15:12:05
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