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DAX Keltner Channel Breaker MT4

The DE_30_803015187_S_Ke_CF_SQX is an algorithmic trading strategy for MetaTrader, tested on DAX using the M30 timeframe from December 7, 2017, to June 2, 2023. There is no need to set up parameters, all settings are already optimized and fine-tuned.


Recommended broker RoboForex because of EET timezone.


You can find the strategy source code for StrategyQuant at the link: http://quantmonitor.net/listing/dax-keltner-channel-breaker/


Key details are:


MagicNumber: 803015187 Main Chart: Current symbol and timeframe

Trading Options
Weekend Trading: Allowed (Friday 00:38 – Sunday 00:38)
Daily Exit: Disabled (15:00)
Friday Exit: Enabled at 19:00
Max Trades/Day: No limit Stop Loss (SL) and Profit Target (PT): No predefined limits

Entry Signals
Long Entry: Triggered when the Open is below the lower band of Bollinger Bands (period 10, deviation 2) after opening above it.
Short Entry: Triggered when the Open is below the lower band of Bollinger Bands (period 4, deviation 1.9) after opening above it.

Entry Rules
Long Entry: Opens long orders at the upper band of the Keltner Channel (period 252, factor 3.35) plus 0.5 times the smallest range of the last 170 bars, with a SL of 0.5% and moves SL to break-even at 2.3 times the ATR(117), valid for 111 bars. Exit after 65 bars.
Short Entry: Opens short orders at the upper band of the Keltner Channel (period 124, factor 4.76) minus 0.1 times the biggest range of the last 144 bars, with a SL of 0.5% and moves SL to break-even at 3.6 times the ATR(189), valid for 111 bars. Exit after 80 bars.

Exit Rules
Long Exit: Closes full position if market is long and no LongEntrySignal is active.
Short Exit: Closes full position if market is short and no ShortEntrySignal is active.

Features

  • Each deal is protected by stop orders (Stop Loss and Take Profit).
  • AI based strategy
  • Both a fixed lot and a free margin percentage are used.
  • No martingale, no grid, no scalp.
  • No excessive consumption of CPU resources.
  • User-friendly settings.
  • All settings optimized, ready for real trading.
  • Long-term strategy. - you need patinet, startegy makes a few trades per month and picks up only the best opportunities on the market


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4.78 (478)
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AW Trading Software Limited
3.67 (3)
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Mohamed Hassan
5 (13)
Current price of $50 for 2  more copies! Next price is: $85 Live Signal : Click here  -- Don't buy a fake backtest, get a real strategy on a real signal!  After purchase, If you genuinely like this robot, you can receive EA Interceptor for Free ! Contact me for more information regarding this BONUS ! EA TOP G  is a multi-currency expert advisor  based on trend following . It uses a hedge system with a very good risk management. It's an ideal candidate for CENT accounts and big balances. It
Sinal ao Vivo-1: Clique aqui Versão MT5: Clique aqui Obtenha o Quantum Pip   gratuitamente (para 2 contas de negociação) -> entre em contato comigo após a compra Bem-vindo ao Nasdaq Algo Trading Este EA (Advisor Especialista) é criado e projetado por uma equipe com mais de 13 anos de experiência em programação e negociação. O EA se concentra no desenvolvimento de um sistema que possa fornecer lucros estáveis e de longo prazo. Ele utiliza estratégias sem risco, evitando métodos como Martinga
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Inrexea Limited
5 (2)
The OP Trading Robot , a cutting-edge development by OpenEA, is a fully automated 4th generation InrexEA DB system designed to excel in the dynamic forex market. Leveraging advanced algorithms, this robot is adept at learning from market trends, particularly focusing on the EURUSD and GBPUSD pairs. Drawing inspiration from the best features of the retired Ea YOLO Diamond Hands, it offers enhanced trade quality protection. Remarkably versatile, the OverPower Trading Robot is compatible with any
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5 (12)
Você já se perguntou por que a maioria dos consultores especializados não é eficaz nas negociações ao vivo, apesar de seu desempenho perfeito nos testes retrospectivos? A resposta mais provável é over-fitting. Muitos EAs são criados para 'aprender' e se adaptar perfeitamente aos dados históricos disponíveis, mas falham em prever o futuro devido à falta de generalização no modelo construído. Alguns desenvolvedores simplesmente não sabem da existência do over-fitting, ou sabem, mas não têm uma
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