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Gbpjpy Macd Trader

The GJ_H1_220100009_S_HD_CF_SQX_SL20 is an algorithmic trading strategy for MetaTrader, tested on GBPJPY using the H1 timeframe from April 1, 2004, to April 24, 2024. 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/gbpjpy-macd-trader/


Key details are:


Parameters
MagicNumber: 220100009
Main Chart: Current symbol and timeframe

Trading Options
Weekend Trading: Allowed
Daily Exit: Disabled
Friday Exit: Enabled at 20:00
Signal Time Range: Not limited
Max Trades/Day: No limit
Stop Loss (SL) and Profit Target (PT): No predefined limits

Entry Signals
Long Entry: Triggered when the MACD (12, 26, 16) crosses below 0.
Short Entry: Triggered when the MACD (12, 26, 16) crosses above 0.

Entry Rules
Long Entry: Opens long orders at the daily high plus 2.60 times the smallest range of the last 50 bars with a SL of 190 pips and a profit target of 260 pips. Order is valid for 17 bars and exits after 22 bars.

Short Entry: Opens short orders at the daily low minus 2.60 times the smallest range of the last 50 bars with a SL of 190 pips and a profit target of 260 pips. Order is valid for 17 bars and exits after 22 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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4.71 (28)
Have you ever wondered why most expert advisors are not effective in live trading, despite their perfect backtest performance? The most likely answer is   Over-fitting . Many EAs are created to ‘learn’ and adapt perfectly to the available historical data, but they fail to predict the future due to a lack of generalizability in the constructed model. Some developers simply don't know about the existence of over-fitting, or they know but don't have a way to prevent it. Others exploit it as a tool
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Niki Ai
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The UJ_H1_170100007_S_OD_CF_SQX is an algorithmic trading strategy for MetaTrader, tested on USDJPY using the H1 timeframe from April 1, 2004, to April 24, 2024.   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/usdjpy-osma-impulse/ Key details are: Parameters MagicNumber: 170100007 Main
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Dax Ai
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Daw Ai
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Daq Ai
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Sap Ai
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