Articles, Library comments - page 3

Tick Scalper Pro - tick chart and one-click trading panel for MetaTrader 5 : Tick Scalper Helper is a manual trading utility for traders who work on very short time frames and want to see every price change. Author: classicaltrading

Check out the new article: Decoding Market Intent: Reading Structure, Liquidity, and Price Behavior . We implement a five-stage MQL5 pipeline that quantifies market structure, liquidity interaction, and price behavior on four timeframes, then resolves them into a 0–100 Market Intent Score. Decision

Check out the new article: Numerical Fidelity Under Fire: Benchmarking Native MQL5, ONNX Runtime, and ALGLIB . This article benchmarks one MLP forward pass implemented three ways in MQL5: native code, ALGLIB, and ONNX Runtime. We quantify numerical fidelity versus a float64 ground truth and

Check out the new article: Broker Time vs Real Market Time — Building a DST-Aware Session Clock in MQL5 . Session filters can run an hour off when a broker and a market change their clocks on different dates. This article presents an MQL5 include file, SessionClock.mqh, that converts London, New

Volume Profile + Range v6.0 : Volume Profile + Range v6.0 (former TPO). Distribution of deals by price levels at a given time interval. Displayed as a histogram. Author: Olexiy Polyakov

Prop Firm Live Daily Breach Line (OrderCalcProfit and iCustom Ready) : Real-time daily drawdown buffer monitor and exact breach price line indicator for prop firm accounts. Features 00:00 server-time deal history reconstruction (including entry commissions), 00:00 HWM snapshot locking, two-stage

Heikin Ashi Candles : A clean Heikin Ashi indicator that draws on the main chart window. It also adds one horizontal line at the average price, (Open + High + Low + Close) / 4, of the last closed candle of a chosen timeframe. By default this is H1, and the line uses the normal candles, not Heikin

Check out the new article: Andean Condor Algorithm (ACA) . The article implements the Andean Condor Algorithm (ACA) for MQL5 — a compact optimizer with a multiscale intensification operator. A significant improvement in solution quality was observed with a small population: a single adjustment to

Fair Value Gaps : Non-repainting fair value gaps on closed bars, with zone states (active, touched, mitigated) and iCustom buffers for EAs. Author: Vira Ohloblia

Check out the new article: Trading Strategy Beyond Raw Volume: Using Transformed Volume Change for Trading . The article develops a volume-change strategy that transforms tick or real volume with Ln(volume+1), differences it bar to bar, and applies arctan to produce a bounded, scale‑independent

Check out the new article: Entropy Pooling and Scenario Budgets for Expected-Shortfall Sizing . Rolling lookback windows implicitly fix a probability vector over past bars. We implement entropy pooling in MQL5 to keep all historical scenarios, reweight them by conditioning on today's volatility

Check out the new article: MetaTrader 5 Machine Learning Blueprint (Part 24): Sequence Risk . Realized backtests reflect a single ordering of trades, so their maximum drawdown and prop‑firm breach risk are often understated. We resequence trade returns via a stationary bootstrap with a derived block

Opening Range Breakout with Statistics Dashboard : Draws the daily opening range and its breakout levels, with a dashboard showing how the range resolved over your lookback: broken up, down, both ways or not at all, and how often a breakout hit its target before the opposite side. Author: Vira

Check out the new article: Low-Frequency Quantitative Strategies in MetaTrader 5 (Part 6): A Constant-Dollar Exposure FX Trading System Based on Fixed-Income Interest Rate Yield Differentials . We describe ANANTA, a rules-based FX portfolio model that measures deviations in Interest Rate Swap

Market Replay Tool : Market Replay Tool is an MT5 utility that seamlessly merges a Market Replay simulator with interactive TradingView-style Long & Short drawing tools. It allows traders to backtest strategies on historical data with adjustable playback speeds, while effortlessly mapping out

Prop Firm Guard Panel : Prop Firm Guard Panel is an on-chart panel for prop firm challenges and funded accounts. It shows in real time the daily loss used and the room left, the max loss room and equity floor, and the progress toward the profit target. The start-of-day balance is rebuilt from

Check out the new article: Neural Networks in Trading: Recurrent Modeling of Market Micromovements (EV-MGRFlowNet) . The article discusses the adaptation of the EV-MGRFlowNet architecture — originally developed for processing event-based video data — to the field of financial time series. The

Mouse Scroll Zoom in Zoom Out : Mouse Scroll Zoom in Zoom Out Author: Rajesh Kumar Nait

Check out the new article: Launching MetaTrader VPS: A step-by-step guide for first-time users . Everyone who uses trading robots or signal subscriptions sooner or later recognizes the need to rent a reliable 24/7 hosting server for their trading platform. We recommend using MetaTrader VPS for

After-Exit Analyzer - what price did after you closed: stopped-out trades that later hit TP, profit left after exits : Reads your closed positions and the M1 bars after each exit. Shows how many stopped-out trades later reached their take profit, how far take-profit trades kept running and how much

Check out the new article: A Symbol Metadata and Trading Hours Cache in MQL5: Eliminating Redundant SymbolInfo Calls in Multi-Symbol EAs . This article presents CSymbolMetaCache, an MQL5 layer that preloads contract specifications and trading-session schedules for monitored symbols at EA startup and

Algo: EMA Trend Cross on Closed Bars — XAUUSD M30 : Free educational EA — a single-position trend-following EMA crossover system for XAUUSD M30, released as open source for beginners to study trade ownership guards, preflight order validation, risk-based lot sizing, and server-time session

Check out the new article: Building a Two-Pole Momentum Oscillator in MQL5 . We build a Two‑Pole Momentum Oscillator in MQL5 that measures deviation from a 25‑period SMA, normalizes it by its mean and standard deviation, and smooths the result with two EMA‑style passes. The code defines inputs

Check out the new article: Weibull Reliability Analysis for Strategy Lifespan: Estimating When an EA Is Likely to "Fail" . We implement a native Weibull maximum-likelihood fit in MQL5 and use it to model strategy wear-out from trade history. Failures are defined as the rolling profit factor dropping

Check out the new article: Building a FIFO-Compliant Position Management Layer for NFA-Regulated MQL5 Accounts . This article shows how to make EA close operations comply with broker-enforced FIFO (ACCOUNT FIFO CLOSE) on hedging accounts, so naive exits stop failing. It introduces CFifoPositionQueue

Check out the new article: Uncertainty as a Model (Part 6): Multiple Regression and Diagnostics . A practical introduction to multiple regression with deterministic factors for financial time series. Topics covered include the formulation and matrix form of ordinary least squares (OLS), residual

Check out the new article: How to Implement R/S Analysis and the Hurst Indicator in MQL5 . The Hurst exponent indicator for MQL5 is based on R/S analysis using OLS regression in log-log space. The theoretical basis is the findings of Gatheral–Jaisson–Rosenbaum (2014), according to which volatility

Check out the new article: Per-Setup Trade Ledger in MQL5: Find Out Which of Your EA's Entries Is Losing Money . Most EAs trade more than one setup, yet the Strategy Tester judges them all by a single equity curve. CSetupLedger is a small MQL5 class that stores each trade's setup in its magic number

Check out the new article: Property-Based Testing for Trading Rules in MQL5 (Part 1): Generate Market Scenarios, Test Invariants, Find Edge Cases . Property-based tests exercise a sizing rule across thousands of generated scenarios instead of a few hand-picked cases. A deterministic MQL5 runner

Check out the new article: Neural Networks in Practice: When to Use an Artificial Neuron and How It Works in MQL5 . We implemented a neuron in MQL5 that was trained using stochastic gradient descent and compared its loss function to that of linear regression. Using code and graphs, we demonstrate