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.
3,012 documents
The article describes an automated options risk-management framework using Black-Scholes Delta and Gamma calculations. Its proposed system combines an option position with trades in the underlying instrument, monitoring portfolio Delta and rebalancing when…
The article introduces the Chaikin Oscillator as a measure of momentum in the Accumulation/Distribution Line, calculated as the difference between fast and slow exponential moving averages of that line. It explains the money flow multiplier and volume…
The article explains the structure of Head and Shoulders and inverted Head and Shoulders patterns as potential trend reversal signals. It describes the head, two shoulders, and neckline, then outlines a possible market narrative in which a weakening trend…
This article turns the eigenvalue spectrum of a portfolio covariance matrix into a normalized diversification measure. It computes log returns for the instruments, builds a covariance matrix, extracts and sorts its eigenvalues, and converts them into shares…
The article presents a preprocessing method for training an LSTM to forecast intraday currency prices. It encodes clock time as a fraction of the day and scales each day’s open, high, low, and close relative to the expanding intraday low and high. These…
This article explains how to assemble a MetaTrader 5 Expert Advisor from reusable functions and configurable inputs. Its constructor approach centralizes trade execution checks, indicator setup, signal handling, and position or pending order management. A…
This article describes a small change to a MetaTrader 5 replay and simulation system so its simulated trading display agrees more closely with live trading behavior. The original setup assigned a custom symbol digit property for chart display and also used…
This article describes changes to a reusable MQL5 strategy engine to support pending orders and hedging accounts. It adds methods for retrieving normalized Ask, Bid, and Last prices for the strategy’s working symbol, plus an overridden Digits method to avoid…
The article adapts Self-Supervised Waypoint Noise Prediction (SSWNP) to financial trajectory forecasting. The method creates clean and noise-augmented versions of observed trajectories, then trains a prediction model on both so their forecasts remain…
This article discusses practical steps for deploying machine-learning models through ONNX in MQL5, with attention to scaling, dimensionality reduction, and time-series inputs. It explains why features on different scales can impair distance calculations,…
This article extends a MetaTrader 5 history navigator with named bookmarks that preserve a chart’s symbol, timeframe, timestamp, and optional notes. It describes how these records let traders return to notable historical patterns, reversals, breakouts,…
This article proposes an empirical test of whether short-term market behavior differs by weekday, drawing on Larry Williams’ Trade Day of the Week concept. Its controlled setup uses a volatility-based entry level projected from the prior day’s range and…
This tutorial outlines a workflow for retrieving historical bars from MetaTrader 5, saving them to CSV, and preparing them in Python with pandas. The examples cover UTC time handling, inspecting file structure, parsing dates and times, checking for missing…
This article turns a normalized least-mean-squares (NLMS) adaptive filter into an MQL5 chart indicator called SAMA. It describes configurable input transformations using prices, differences, or returns; adaptive filter weights; and slope-based line coloring.…
The article explains how to build interactive button controls for a MetaTrader graphical interface. It develops simple buttons with configurable text, size, colors, pressed states, and availability, then extends the design to icon buttons and split buttons…
The article shows how to turn candle data returned by an external API into arrays that are easier to analyze in MQL5. After splitting the response into per-candle fields, it identifies the positions for opening time and OHLC prices, then groups comparable…
The article describes reusable time filters for controlling when an expert advisor may perform an action. It covers date ranges, selected days of the week, and timers with configurable durations. Filters can be activated or reversed, and a container can…
The article explains how a Kohonen self-organizing map (SOM) clusters input patterns without labeled targets. Each neuron competes to match an input vector, and the winning neuron and its neighbors adjust their weights. The learning rate and neighborhood…
This article modifies a Bollinger Band trading system by using logistic regression to estimate trade confidence and vary position size. The underlying rules sell when price moves above the upper band and buy when it falls below the lower band, with…
This article introduces DBSCAN as a way to cluster data for MQL5 Expert Advisor signal logic. Unlike k-means and agglomerative approaches that require a chosen cluster count, DBSCAN uses a neighborhood distance parameter and a minimum number of points to…
This article explains four historical volatility estimators that use different portions of each bar’s OHLC data: close-to-close, Parkinson, Garman-Klass, and Yang-Zhang. Close-to-close uses only closing prices, while the range-based alternatives incorporate…
This installment extends a web application for managing multiple MetaTrader 5 terminals. It introduces a configuration file to replace hard-coded terminal paths and adds an API route intended to return information for one terminal, including account number,…
The article explains volume as a market activity measure, noting that Forex platforms commonly show tick volume while exchange-traded instruments can report traded quantity. It presents simple ways to interpret volume: compare the current reading with the…
This article combines measurements from an earlier microstructure series into six session labels: Normal, Stressed, Noisy, Informed, Trending, and Mean-Reverting. A priority-ordered rule set applies empirical thresholds to volatility, noise, order flow,…