- Capital líquido
- Rebaixamento
Distribuição
Símbolo | Operações | Sell | Buy | |
---|---|---|---|---|
GOLD | 57 | |||
10
20
30
40
50
60
|
10
20
30
40
50
60
|
10
20
30
40
50
60
|
Símbolo | Lucro bruto, USD | Loss, USD | Lucro, USD | |
---|---|---|---|---|
GOLD | 697 | |||
250
500
750
1K
1.3K
1.5K
1.8K
2K
2.3K
2.5K
2.8K
3K
|
250
500
750
1K
1.3K
1.5K
1.8K
2K
2.3K
2.5K
2.8K
3K
|
250
500
750
1K
1.3K
1.5K
1.8K
2K
2.3K
2.5K
2.8K
3K
|
Símbolo | Lucro bruto, pips | Loss, pips | Lucro, pips | |
---|---|---|---|---|
GOLD | 2K | |||
2.5K
5K
7.5K
10K
13K
15K
18K
20K
23K
25K
28K
30K
|
2.5K
5K
7.5K
10K
13K
15K
18K
20K
23K
25K
28K
30K
|
2.5K
5K
7.5K
10K
13K
15K
18K
20K
23K
25K
28K
30K
|
- Depósito carregado
- Rebaixamento
A slippage média baseada em estatísticas de contas real de diferentes corretoras é especificada em pontos. Depende da diferença entre as cotações do provedor de "XMGlobal-MT5 13" e do assinante, bem como de atrasos na execução de ordens. Quanto menor o valor, melhor a qualidade da cópia.
Sem dados
ATFNet is an advanced deep learning model specifically crafted for long-term time series forecasting by seamlessly integrating time and frequency domain modules. Developed by Reza Yazdanfar, this innovative model introduces a unique weighting mechanism that adjusts weights according to periodicity, enhances the Discrete Fourier Transform, and employs a Complex-valued Spectrum Attention mechanism for identifying intricate relationships. ATFNet is designed to surpass existing methods in long-term time series forecasting by effectively addressing the challenge of mixed periodic properties in real-world time series data.
ATFNet, a model leveraging the Advanced Discrete Fourier Transform, offers significant benefits in Forex trading:
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In-Depth Time Series Analysis: ATFNet provides a more thorough analysis of time series data by accounting for the frequency characteristics of input data, leading to more accurate modeling and prediction of market trends.
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Enhanced Forecasting Precision: Utilizing the Advanced Discrete Fourier Transform, ATFNet improves the accuracy of market movement predictions, resulting in more efficient trading decisions.
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Versatility: ATFNet is adaptable to various tasks, including market movement forecasting, trend identification, and generating trading signals.
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Quicker Market Response: ATFNet's ability to quickly react to market changes allows traders to promptly address market fluctuations and maximize profits.
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Improved Noise Resistance: With enhanced resistance to noise in market data, ATFNet increases model stability under uncertain conditions, leading to more reliable forecasts.
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Multi-Strategy Capability: ATFNet supports simultaneous trading across multiple strategies, enabling traders to diversify their portfolios and boost profitability.
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Consistency in Backtesting and Live Trading: ATFNet ensures that backtesting results are aligned with real trading performance, helping traders evaluate strategy effectiveness and achieve better returns.