simulate for this 12 straegies method by using my signals provided: 1. Price action trading 2. Range trading strategy 3.Trend trading strategy 4. Position trading 5. Day trading strategy 6. Scalping strategy 7. Swing trading 8. Carry trade strategy 9. Breakout strategy 10. News trading 11. Retracement trading 12. Grid trading To simulate these 12
Space Time...
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okin now on the way of building from above we’re talking. i’m listig all signals that i have on SQX for you: ADX, Arron, ATR, ATR Percent Rank, AVG Volume, Awesome Oscillator, Bear power, Bull power, BH Ergodic, Bollinger Bands, Candle Pattern, CCI, Choppiness Idex, Connor RSI, CSSA Market Regime, Demarker, DEMA, Didi index, Directional
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then i got 400 from builds type : Exit everday 23:00, Exit on Friday 23:40, Exit Rules no fix exit day or time but hold not over 10 day and Repeat/Duplicate orders trade. from base H1/H4 TF, so can i use Sequantial optimization by +30% -30% with 10 step for another TF like M30/H4 M15/H4
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A Sharpe ratio greater than 1 is a positive indicator for a trading strategy, but when it’s over 2, it signifies even better performance. Here’s a breakdown: Sharpe Ratio > 1: Indicates that the strategy is generating more returns than the risk it’s taking. A ratio above 1 means the excess returns (returns above the risk-free rate) are higher
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i just building and got some prototype but i asking u: Profit factor, Ret/DD ratio, Stability, Fitness, Open DD%, Win/Loss ratio and CAGR/Max DD%. Rank these values from most important to least important that I should consider, including the analysis of both IS and OOS at each stage. When evaluating a trading strategy, especially in StrategyQuant
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i use M1 data and 20yrs old of data range. too high or its ok? cuz i need to build once and leave it ran live a long period Using M1 data and a 20-year range for backtesting in StrategyQuant X is a solid choice, especially if your goal is to build a strategy that will run live for a long
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SQX has too many signal and indicators in it. so if i let it generating by genetic evolution. what do ya think? just about only Exit Type. Using genetic evolution in StrategyQuant X (SQX) to optimize your strategy, especially for the Exit Type, is a smart approach. The genetic algorithm in SQX will explore various combinations of parameters and strategies,
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do it your best with my need to build on main TF H1, sub chart H4. H1 for active signal H4 for confirmation. basse on 0.01 : 100$ and Risk % on account. To build your strategy in StrategyQuant X with the main TF (H1) for active signals and H4 for confirmation, along with risk management based on 0.01 lots per
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in SQX, Exit type contain Exit After Bars, Move SL 2 BE (+ SL 2 BE Add Pips), Profit target, Stop Loss, Trailing Stop (+ Trailing Activation) and Exit Rule. which one can made more Open and close as many orders as necessary for gold. In StrategyQuant X (SQX), the exit type you choose plays a
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lets talk about Strategy Quant, can u analysis .CFX file for SQX It seems like you’re referring to StrategyQuant (SQX), a software platform used for creating, testing, and optimizing trading strategies, specifically for algorithmic trading. The .CFX file you mentioned might be a specific file format related to StrategyQuant X that holds strategy configuration or data, though .CFX isn’t a commonly known