Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
4,574 documents
The article describes an MQL5 money management class that combines a one-level Haar wavelet filter with an LSTM network to scale position size in volatile, trend-oriented markets. The wavelet step transforms recent log returns into approximation and detail…
The article introduces parameter search for trading strategies and demonstrates it with a simple moving average crossover. It compares brute-force, grid, and random search in Python, using historical EURUSD daily data over the stated test period, and…
The article presents the first part of an MQL5 Expert Advisor designed to support manual trading across multiple symbols. Using the EasyAndFast GUI library, it lays out a panel with tabs, symbol and position tables, chart display, signal-level and…
The article proposes combining balance-sheet data from the Federal Reserve, European Central Bank, Bank of Japan, and People’s Bank of China into a global liquidity measure for forecasting currency movements. It explains the intuition that balance-sheet…
The article outlines a workflow for retrieving International Monetary Fund data through its SDMX-JSON interface, parsing the nested responses, handling indicators with different reporting intervals, and caching results. It proposes combining measures such as…
The article examines how learning-rate choices affect a simple generative adversarial network used as an MQL5 trading signal. It describes fixed and scheduled rates, including step decay, exponential decay, and cyclical adjustment. In broad terms, a fixed…
This article explains how to integrate MetaTrader 5’s ZigZag indicator into the MQL5 Standard Library style. It contrasts a procedural Expert Advisor that creates an indicator handle and copies buffers with an object-oriented example that creates a CiZigZag…
The article presents a framework for applying currency-cluster indicators to forex pairs. It distinguishes impulse indicators, which signal relative currency changes when lines cross, from trend-following indicators, which provide directional context and…
The article explains how to extend Experts generated by the MQL5 Wizard so they can place orders, stop losses, and take profits at calculated price levels rather than only at fixed distances from the current market. It proposes inheriting from standard…
This article builds a two-model forecasting approach for NZDJPY: an initial model predicts a future close, and a second model estimates the initial model’s residuals to correct its forecast. The author describes collecting minute-level prices, exploring…
This article extends a brute-force method for finding trading patterns by dividing historical quotes into time-based samples. The proposed segments include days of the week and intraday windows, with further discussion of months and years. Segmentation is…
The article shows how to organize multiple ONNX classifiers in MQL5 using a shared base class and model-specific subclasses. The base class stores the trained symbol and timeframe, checks that an expert advisor is using the matching market, creates and…
This article explains how an extended account report can help evaluate automated forex systems trading several currency pairs. It describes added metrics and charts for balance changes, profit and loss, trade counts, holding time, and pair-level outcomes.…
This article describes a system for estimating long-term fair currency values using purchasing power parity rather than short-term price patterns. It reviews absolute and relative PPP, then combines several approaches: international price-level comparisons,…
This article covers an implementation step for SAMformer, a shallow Transformer approach to multivariate time-series forecasting that uses Sharpness-Aware Minimization (SAM). It focuses on adding SAM optimization to a convolutional layer in an MQL5…
The article introduces Superpoint Transformer (SPFormer), an end-to-end method for segmenting individual objects in sparse 3D point clouds. A sparse 3D U-Net first extracts point features, which are pooled into superpoints to reduce the representation size.…
This article describes a custom MQL5 Wizard signal class that pairs four B-Tree-inspired search modes with an optional Bayesian neural network. The proposed modes represent direct lookup, a local range average, a search for the largest recent price change,…
The article explains SEFormer, a Transformer design for 3D point-cloud detection that adds spatial structure to attention. Standard convolution encodes direction and distance through its kernels but aggregates neighbors uniformly; ordinary self-attention can…
The article introduces Quarters Theory as a way to divide a major price interval into four equal large-quarter segments, which are treated as potential support, resistance, pause, or acceleration areas. It describes an MQL5 chart script that locates the…
The article describes pivot points as daily reference levels that traders may interpret as directional guides: price above a pivot is associated with upward bias, and price below it with downward bias. It outlines a classical calculation using the previous…
The article outlines a multi-currency carry approach that seeks positive swap income while offsetting exchange-rate exposure through opposing positions in correlated currency pairs. It proposes using least-squares regression on historical daily prices to…
The article introduces Mamba4Cast, a time-series forecasting framework that combines state-space sequence modeling with Prior-data Fitted Networks. Instead of pretraining on one instrument’s historical prices and then fine-tuning, the approach learns from…
This interview describes an Expert Advisor built around changes in the Bulls Power indicator. The trader looks for a significant shift in its trend and magnitude as a signal of a possible new market direction, then opens a position in that direction. The…
The article examines how to reduce false and delayed signals from a conventional moving average crossover strategy. Its baseline uses fast and slow averages for direction, with ATR-based stop-loss and take-profit levels. A manual refinement adds a…