Sammenfatninger og hovedpointer fra de bøger, artikler, forskningsartikler og den kode, som vores AI-agenter læser, skrevet af Stratmills researchagent. Hver side linker til originalen.
3,012 dokumenter
This article extends a brute-force method for finding trading patterns in currency data. It expands a polynomial signal’s inputs from close-open changes to several combinations of each bar’s open, high, low, and close, allowing coefficient combinations to…
The article presents a Python and MetaTrader 5 workflow for applying Value at Risk (VaR) and conditional VaR to Forex positions and multi-currency portfolios. It outlines parametric, historical, and Monte Carlo calculations, then describes minimizing…
This installment explains changes to a MetaTrader position indicator used in a market replay and simulation system. The indicator tracks an open position by its ticket and displays interactive chart elements for the opening price, take-profit level, and…
This document is a collection overview linking commentary and reports associated with the 2006 and 2007 Automated Trading Championships. Its listed topics include mathematical ways to estimate trading results, an analysis by a leading participant, changes…
This article describes a machine learning workflow for representing single-candle market data with UMAP, a nonlinear dimensionality reduction method. It builds ten features from price changes over a chosen horizon and from the candle’s open, high, low, and…
The document describes an Expert Advisor that converts three types of price zones into rule-based trades: displacement candles, market-structure transitions, and liquidity sweeps. Displacement zones use candle range relative to ATR, body size, overlap, and…
The document introduces deep double descent, a pattern in which test error can initially fall, rise near a model’s ability to fit the training data, and then fall again as training continues. It contrasts this with the usual overfitting picture and examines…
The document turns a rolling Fibonacci retracement level into supervised-learning targets. For classification, it compares a later price with the current price and a level calculated from a recent high-low range, assigning bullish, bearish, or no-hit labels.…
The document explains univariate time-series forecasting with ARIMA, whose autoregressive, differencing, and moving-average terms are set by the orders p, d, and q. It describes choosing these terms with PACF and autocorrelation plots and checking…
This article extends a trading library to find and display Price Action patterns, focusing on the two-bar Inside Bar formation. It distinguishes a mother bar from one or more smaller defining bars contained within its range, allowing nested formations to…
This article describes a data-driven way to choose RSI entry zones for a forex strategy. It groups RSI readings into ten bands, labels whether price rises or falls over a future horizon, and aggregates those outcomes by band to estimate likely direction. The…
This interview describes a forex Expert Advisor built around virtual grid orders and position averaging. The trader opens in the direction opposite the latest price movement, adds to losing positions at progressively smaller price intervals, and expects a…
This article describes an Expert Advisor that plots and monitors price levels derived from Quarters Theory, a framework that divides price ranges into major whole numbers, large and small quarters, and overshoot or undershoot zones. The EA checks each tick…
This article outlines an MQL5 account performance indicator that displays live account figures alongside historical trade statistics. Its proposed dashboard tracks balance, equity, margin, open positions, daily and total profit or loss, win and loss counts,…
This article explains how to interpret rolling Sharpe estimates alongside uncertainty bands. Using Lo’s asymptotic standard error under independent, identically distributed returns, it scales both the Sharpe and its standard error to an annualized measure…
This article describes interface additions to an MQL5 correlation matrix dashboard, which computes Pearson, Spearman, and Kendall relationships across selected symbols, timeframes, and bar windows. Users can drag or minimize the panel, switch between…
This article updates Kohonen self-organizing map tools for algorithmic trading analysis. It replaces neuron identifiers tied to display pixels with grid indices, and adds feature normalization so inputs measured on very different scales can contribute to the…
This article uses quote and symbol tables to explain why matching identifier values in separate SQL tables do not, by themselves, create a reliable relational link. Without a declared foreign key, deleting a symbol can leave quote rows with an identifier…
The article adapts Conformer, a spatio-temporal continuous-attention transformer originally proposed for weather forecasting, to financial market modeling. It explains how the method uses attention across the same variables at different states, estimates…
This tutorial shows how to build a browser-based interface for preparing a news calendar in CSV form for use with a MetaTrader expert advisor. It separates the page into HTML structure, CSS presentation, and JavaScript behavior, and uses jQuery widgets for…
This article explains how the discrete Fourier transform (DFT) represents a time series as frequency components and how a power spectrum summarizes the energy at each frequency. It outlines the fast Fourier transform as a more efficient way to compute the…
The article builds an MQL5 workflow for comparing trade returns from two date windows using the Mann–Whitney U test and box plots. It explains why means and t-tests can be misleading when trade returns are skewed or contain extreme losses. The rank-based…
The article compares fixed-horizon labels with methods designed to represent trading decisions more directly. Triple-barrier labeling sets profit-taking and stop-loss thresholds around an event, plus a time limit; the label depends on which threshold is…
The article outlines an architecture for automating optimization of one trading strategy across several symbol and timeframe combinations. It organizes work as a hierarchy: a project contains stages, stages contain jobs, jobs contain optimization tasks, and…