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 source combines confirmed high and low fractals with a three-EMA alignment filter. It calculates exponential averages over 10, 20, and 100 periods, then defines bullish alignment when they rise in that order and bearish alignment when they fall in that…
This XAUUSD strategy uses RSI threshold crossings to identify possible reversals: a move below the oversold level opens a long position, while a move above the overbought level opens a short. Its parameters include an RSI period, threshold levels, trailing…
This intraday system compares the New York 08:00 open with the 18:00 close to classify the day’s direction, then uses the prior day’s direction to decide whether to reverse that signal. It places a limit order at the day’s low for a long or the day’s high…
This short-term strategy combines Bollinger Bands, RSI, and ADX to trade forex price gaps. Its stated setting is major currency pairs on one- to fifteen-minute charts, with low trading costs. Entries use a band break alongside an RSI reversal through a…
This short-term signal system combines a 3-period exponential moving average, the Bollinger Band middle line, and the Awesome Oscillator. A bullish alert occurs when the fast average crosses above the middle line while the oscillator is rising toward or…
The strategy uses a fast 20-period EMA and a slower 50-period EMA to generate directional signals: crossing upward opens a long, while crossing downward opens a short. It pairs those entries with a fixed profit target of 300 points and stop of 150 points,…
The article explains a workflow for training a machine-learning model in Python, exporting it through ONNX, and running it from an MQL5 trading program. Its example is a regression model using open, high, and low prices as inputs and close price as the…
The article describes the Volume Boundary Oscillator, which transforms raw or tick volume into a bounded signal for easier comparison and threshold-based use. It first scales volume with either a rolling z-score style normalization or a logarithm, then…
The article shows how to modify an Expert Advisor generated by MetaTrader 5’s MQL5 Wizard by adding a customized signal filter based on a standard indicator class. It uses RSI and moving average filters as examples of Wizard-generated components, then…
This article explains how to turn a weekend gap indicator into an MQL5 Expert Advisor. The indicator exposes buffers for buy and sell signals and their associated stop-loss and take-profit levels. The EA creates an indicator handle, reads those outputs,…
The article outlines a MetaTrader 5 approach that selects currency pairs using Pearson correlation and cointegration tests, then combines a negatively correlated pair with a trading system framed around Nash equilibrium. It explains Nash equilibrium as a…
The article explains an MQL5 Expert Advisor that uses RSI thresholds to open trades and a zone recovery process to respond when price moves against an initial position. It defines zone boundaries and profit targets around the entry, then opens an opposing…
The article describes a market-neutral limit-order grid built from historical return distributions rather than a directional forecast. It calculates rolling returns from price data, sorts them, and uses empirical percentiles to estimate levels at which…
This article compares seven moving average types: standard simple, exponential, smoothed and linear-weighted variants, plus adaptive, double exponential, fractal adaptive, triple exponential, variable index dynamic and Nick Rypock averages. It describes how…
This tutorial walks through preparing MetaTrader 5 for automated trading with MQL5. It covers downloading and installing the platform, connecting a broker demo account, adjusting chart and Expert Advisor settings, and using the built-in Strategy Tester. It…
The document explains On-Balance Volume (OBV), a cumulative indicator that adds volume when the close rises and subtracts it when the close falls. It describes volume as a way to assess whether price moves and breakouts have support, and walks through how…
The article presents Mamba4Cast as a time-series encoder within an Actor-Director-Critic trading agent. Its described encoder processes market features, applies normalization with noise, adds hourly and daily time embeddings, uses multi-window convolutions…
This document presents a reusable diagnostic survey for financial datasets, covering index integrity, duplicates, missingness, outliers, calendar gaps, and domain-specific anomalies. It checks time types, ordering and uniqueness, including per-symbol…
This notebook measures how changing proportional transaction costs affects one validation-selected FX strategy per return label. It first selects a parent from signal, allocation, and risk-overlay candidates, then varies only the aggregate cost per traded…
This exploratory analysis profiles a four-hour OANDA panel of 20 currency pairs and explains how to interpret its data. It distinguishes direct, indirect, and cross pairs by the dollar’s position, showing why direct quotes must be inverted before combining…
This notebook sets up an LSTM forecasting run for an FX-pairs case study. The model carries a hidden state through a lookback sequence, and the notebook resolves architecture and training settings through the shared configuration and study-planning tools. It…
The document describes a validation-stage comparison of fixed and trailing stop rules for FX strategies. For each return label, it selects a parent strategy from a sealed cohort of signal and allocation results, then varies the declared position-level risk…
This notebook examines linear-model regularization for a universe of currency pairs whose returns are linked because each pair is a quote between shared currencies. It distinguishes feature collinearity, which ridge, lasso, and elastic net can address, from…
This notebook describes a one-feature-at-a-time screen for candidate signals across 20 currency pairs. It computes each feature’s daily cross-sectional rank agreement with the next-session return using only walk-forward validation windows. The evaluation…