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Seasonality Filtering and time period for Deep Learning ONNX models with python for EA MetaTrader 5
Can we benefit from seasonality when creating models for Deep Learning with python? Does filtering data for the ONNX models help to get better results? What time period should we use? We will cover all of this over this article
Deep Learning GRU model with Python to ONNX with EA, and GRU vs LSTM models MetaTrader 5
We will guide you through the entire process of DL with python to make a GRU ONNX model, culminating in the creation of an Expert Advisor (EA) designed for trading, and subsequently comparing GRU model with LSTN model
Deep Learning Forecast and ordering with Python and MetaTrader5 python package and ONNX model file MetaTrader 5
The project involves using Python for deep learning-based forecasting in financial markets. We will explore the intricacies of testing the model's performance using key metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared (R2) and we will learn how to wrap everything
RSI深三步交易技巧 MetaTrader 5
在MetaTrader 5中展示RSI深三步交易技术。本文基于一系列新的研究，这些研究展示了一些基于RSI的交易技术，RSI是一种技术分析指标，用于衡量股票、货币或商品等证券的强度和动量。
重新审视一种旧时的趋势交易策略：两个随机振荡指标，一个移动平均指标和斐波那契线 MetaTrader 5
旧时的交易策略本文介绍了一种纯技术型的趋势跟踪策略。该策略纯粹是技术性的，使用一些技术指标和工具来传递信号和目标。该策略的组成部分如下：一个周期数为14的随机振荡指标，一个周期数为5的随机振荡指标，一个周期数为200的移动平均指标，一个斐波那契投影工具（用于设定目标）。
Heiken-Ashi指标与移动平均指标组合能够提供好的信号吗？ MetaTrader 5
策略的组合可能会提供更好的机会，我们可以把指标和形态一起使用，或者更进一步，多个指标和形态一起，这样我们可以获得额外的确认因子。移动平均帮我们确认和驾驭趋势，它们是最为人所知的技术指标，这是因为它们的简单性和为分析增加价值的良好记录。
简单均值回归交易策略 MetaTrader 5
均值回归是一种逆势交易，交易者预估价格将返回到某种形式的均衡点位，通常依据均值或其它向心趋势统计值来衡量。