ExportBars is a utility script for exporting bar history for any symbol and timeframe into a CSV ready for external analysis. The output is designed to load with a plain pandas.read_csv() call, without specifying encoding, separators, or date formats.

Default MQL5 file output creates friction: UTF-16 requires explicit encoding in pandas, timestamps come out as “YYYY.MM.DD HH:MM” and need a custom parser, and price formatting may vary by row if symbol digits are not enforced. ExportBars fixes these issues at the source.

The CSV is single-byte text, with one header row: time, open, high, low, close, tick_volume, spread, real_volume. Time is ISO 8601 “YYYY-MM-DD HH:MM:SS” in server time. Prices are formatted using SYMBOL_DIGITS and never in scientific notation. Rows are oldest-first, matching chart order.

Inputs include symbol, timeframe, last-N vs date-...

👉 Read | CodeBase | @mql5dev

A practical way to expand EURUSD D1 direction models beyond classic TA features is to derive deterministic nonlinear features by mapping OHLC onto an elliptic curve (secp256k1). Each price is hashed (SHA-256) and converted to a valid curve point via try-and-increment; the number of attempts (nonce) becomes a feature, alongside x-bit statistics and curve point arithmetic such as Open+Close and High+Low.

The study builds 96 features (EC, TA, and cross-features) over multiple lookbacks and trains CatBoost with a strict time split, evaluated by AUC. On 2,000 daily candles, EC+TA improves test AUC to 0.6508 vs 0.5992 for TA alone, with x_slope and oc_x ranking among the most useful additions.

The key constraint is regime dependence: cross-validation averages do not consistently beat the baseline. The actionable takeaway is gating EC features with a tre...

👉 Read | NeuroBook | @mql5dev

Most horizontal lines at prior highs are subjective. A higher-confidence level is a price band repeatedly validated by clustered pivots and repeated retests. This indicator aggregates recent swing highs/lows, groups nearby pivots into adaptive-width channels, assigns a score, and renders the strongest as background bands across the chart.

Pivots default to 10 bars left/right, taken from wicks or bodies, and remain eligible for 290 bars. Channel width is capped at 5% of the last 300 bars’ range, scaling with volatility. Scoring adds 20 points per pivot plus 1 point per bar whose high/low falls inside the band. Selection keeps the best, discards overlapping candidates, and repeats up to 10 channels, drawing the top 6 by default.

Channels update only on confirmed pivots; live ticks do not rewrite history. Bands switch role in real time based on current ...

👉 Read | Freelance | @mql5dev

A set of EA input defaults defines an EMA-based signal on M15 using closed bars. Fast and slow EMA periods are set to 10 and 30, with the signal timeframe fixed to M15.

Trading is restricted to a WIB session window from 19 to 22. Position sizing uses a fixed 0.01 lot.

Risk parameters specify 70 points stop loss and 200 points take profit. The system limits exposure to 1 maximum open position.

Execution and filtering settings include a spread cap of 100 points, with 0 disabling the filter. Order tracking uses magic number 20260909, and maximum slippage is set to 10.

👉 Read | CodeBase | @mql5dev

QCL Heikin Flow for MT5 implements a two-stage smoothing pipeline for Heikin Ashi output. Stage one applies a selectable MA (EMA/SMA/SMMA/LWMA) to the underlying OHLC series. Stage two rebuilds Heikin Ashi values and smooths them again using an independent period and method, reducing short-term oscillation in candle bodies and wicks.

The indicator separates rendering into three DRAW_CANDLES plots: bullish, bearish, and neutral, each with its own buffer set. Calculation buffers are kept distinct from display buffers, and arrays are indexed chronologically (0 as oldest) to simplify iterative MA state.

Parameter validation caps periods to 1..10000. The MovingAverage routine handles EMA and other methods with partial-window seeding to avoid undefined startup values.

👉 Read | AlgoBook | @mql5dev

A standalone market-structure indicator for SMC-style analysis, built on a pullback swing detector and extended with structure state, validated extremes, and event tracking.

Two layers are processed per closed bar: a non-repainting pullback zig-zag that outputs alternating confirmed swings, then a structure engine that maintains exactly one active high, one active low, and a trend state (None/Up/Down). Structure is seeded from the first pullback high/low; after that, pullbacks only provide references.

Events are derived from one rule: closes break levels (BoS or CHoCH depending on trend), while wicks create pending sweep candidates. A sweep (x) is only confirmed when the next break occurs on the opposite side, and can relocate the prior structure point. Extremes are confirmed via IDM: after a break, the latest qualifying pullback becomes the referenc...

👉 Read | NeuroBook | @mql5dev

Most momentum indicators rely on fixed lookbacks and constant smoothing, so the output reacts the same way in quiet ranges and during news-driven spikes. Volatility-Adjusted Momentum Decay Line (VAMD) addresses this by normalizing raw momentum (close change over InpMomentumPeriod) by ATR, expressing momentum in volatility units.

The normalized value is then passed through a recursive decay filter. The decay rate is adaptive: it scales with current ATR divided by ATR’s moving average over InpATRAvgPeriod. Higher-than-baseline volatility increases decay speed and forces faster convergence to new momentum; compressed volatility slows decay and preserves prior direction longer.

Interpretation is centered on a zero line. Persistent readings on one side suggest momentum with follow-through even when volatility expands. Rapid spikes away from zero followed ...

👉 Read | CodeBase | @mql5dev

DoEasy’s indicator layer is extended to cover the remaining complex MT5 standards: Ichimoku Kinko Hyo and Bill Williams’ Gator Oscillator, both usable as multi-symbol, multi-period objects.

Ichimoku support handles five plotted lines and adds two auxiliary histogram buffers to shade the area between Senkou Span A/B while preserving each line’s style and color. These “design buffers” are excluded from the Data Window, keeping output clean.

To manage compound indicators, buffer objects gain an “additional line number” plus a new enum for unambiguous line identification, avoiding conflicts from shared enum values while keeping unified handlers. Data preparation/clearing and buffer lookup were updated to handle extra buffers and Gator’s nonstandard buffer indexing.

Tests confirm H4-calculated indicators render correctly on an H1 chart and match terminal...

👉 Read | Docs | @mql5dev

Risk Calculator Panel is a position size calculator indicator for MetaTrader 5. Position sizing is done by dragging a Stop Loss line on the chart, with the panel updating lot size in real time for the selected risk. As an indicator, it does not open, close, or modify trades.

After attaching it to a chart, dashed SL and TP lines appear near the current price. Moving SL below price calculates a BUY from Ask; moving it above price calculates a SELL from Bid. Moving TP updates reward and the reward:risk ratio. Risk percentage can be edited directly in the panel without reopening inputs.

The panel shows entry direction and price, SL distance in points with minimum stop checks, target risk and rounded-down lot size by volume step, real risk after rounding, reward and R:R, plus margin when available. Calculations use tick size and tick value converted to ac...

👉 Read | Calendar | @mql5dev

A fractal-dimension regime filter can separate trend and range by measuring path efficiency instead of directional strength. The value stays between 1.0 and 2.0: readings near 1.0 indicate clean directional movement, while readings toward 2.0 indicate repeated backtracking with limited net displacement.

The calculation follows a simplified Katz method over InpFractalPeriod bars: sum the absolute bar-to-bar changes (total path length) and compare it to the maximum displacement from the window’s first price, then apply a logarithmic ratio to derive the dimension. An EMA with InpSmoothPeriod reduces noise.

Zone logic uses two thresholds: at or below InpTrendThreshold (default 1.40) is trending, at or above InpChopThreshold (default 1.65) is choppy, with a neutral band between. Typical use is gating entries from a directional tool only when the line is i...

👉 Read | VPS | @mql5dev

BotGuard is a lightweight monitoring Expert Advisor for VPS setups running trading robots. It does not open, close, or modify orders. Its role is terminal health reporting so outages are detected quickly.

Every 30 seconds it rewrites botguard_<login>.json in Terminal\Common\Files with UTC server time, login, server/company, connection and AutoTrading state, ping, balance/equity, margin level, open positions/orders, start-of-day equity, daily P/L %, and terminal build. It writes via temp file swap to avoid partial reads.

Every 5 minutes it appends botguard_<login>_log.csv (time, balance, equity, positions, connected) for equity curves and uptime checks. Push alerts and journal messages trigger on AutoTrading toggles, reconnection, and equity drawdown below a configured threshold.

External watchdogs can monitor file age and restart the terminal if updates stop. C...

👉 Read | Signals | @mql5dev

Prop Firm Equity Guard monitors account equity continuously and enforces common prop firm risk rules. When a threshold is breached it closes all open positions, deletes pending orders, and blocks further trading until the lock condition expires. It does not open trades on a live chart and can run alongside manual execution or other EAs.

Supported limits include daily loss (based on balance, equity, or the higher of both at day start), maximum loss (based on initial balance), and an optional profit target that liquidates exposure once reached. Early warnings can trigger messages and MT5 push notifications at a configurable usage level.

A chart panel shows lock state, equity, daily and maximum loss usage, profit target, and the captured day-start value. State persistence relies on terminal global variables to survive restarts. Controls include reset hour in s...

👉 Read | VPS | @mql5dev

Session High Low plots the Asia, London, and New York trading sessions as colored boxes from session open to close, covering each session’s high and low. After the close, optional dotted extensions project the high/low levels for a configurable number of hours to track breakouts and retests.

Ranges are derived from M5 data, keeping session highs/lows consistent across M1 through H1. The active session box updates in real time as new extremes print. Tooltips provide high, low, and range in points, with labels for session name and prices; the New York label is positioned to avoid overlap with London.

Configuration includes per-session enable switches, start/end times, and colors, plus days to draw, maximum timeframe visibility, label toggle, and extension duration. Sessions crossing midnight are handled automatically, and weekends/holidays are skipped....

👉 Read | Forum | @mql5dev

DailyPnLPct.mq5 adds an on-chart overlay that tracks today’s floating P&L as a percentage of a baseline balance and expresses daily-loss consumption in terms aligned with common prop firm rules.

The reset point is configurable via InpResetHour (server time). At each update, the script derives a reset timestamp, stores base_balance from ACCOUNT_BALANCE, then compares live ACCOUNT_EQUITY against that baseline to compute pnl_pct and “daily loss used”.

A single OBJ_LABEL is maintained and refreshed on OnCalculate plus a 30-second timer. Status is color-coded based on consumption thresholds: under 50% of the limit, under 80%, or above. The text line reports Day P&L, loss used versus InpLimitPct, and remaining room before breach.

👉 Read | Quotes | @mql5dev

ApexVelocity EA v1.0 targets volatility breakouts on XAUUSD with a fully dynamic parameter model rather than fixed point-based tuning. Execution logic is positioned as non-grid and non-martingale, built around price action, ATR-based volatility measures, and capital protection controls.

Broker-agnostic handling is implemented via ATR multipliers for buffers, break-even padding, trailing stops, and slippage tolerance, maintaining consistent behavior across 2/3-digit pricing. Risk sizing uses a TickSize/TickValue ratio approach to keep percentage risk aligned to account currency exposure.

Order management validates exits against SYMBOL_TRADE_STOPS_LEVEL to avoid invalid stop modifications during fast moves. Signal gating includes tick-volume acceleration, minimum ATR range, body-to-range quality filters, H1 MA-50 alignment, and session time windows. A peak-equi...

👉 Read | Docs | @mql5dev

An Expert Advisor implements an opening-range breakout variant for 24-hour markets, tuned by default for XAUUSD. The chart timeframe is irrelevant; logic reads M1 and D1 directly, with M1 mainly useful for visual testing.

At the configured session start (08:00 London by default, mapped to server time with DST handling), the open is captured and entry levels are set using either a “stretch” metric from recent sessions or a multiple of daily ATR. If yesterday’s candle passes the selected contraction filter, buy-stop and sell-stop orders are placed around the open with opposite-side stops, OCO behavior, and timed order cancellation.

Filters include NR4, NR7, inside day + NR4, 3-bar narrowest range, combined modes, plus optional skip-after wide-range days.

Risk and execution controls cover % risk sizing, daily loss limits, max fills, spread/offset constraints, b...

👉 Read | AppStore | @mql5dev

The article argues that profitable algorithmic trading starts with a measurable edge, not indicator stacking and optimizer-driven curve fitting. It proposes a scientific workflow: detect a price pattern, validate it across symbols and scales, then quantify expected payoff after real trading costs.

Using block charts (price quantized into fixed-point moves), the author finds a consistent tendency: after moving N points, price is slightly more likely to continue than reverse. This “trend bias” appears across FX, stocks, crypto, and commodities, but weakens at larger scales.

Key implementation risks are highlighted for MT5 robots: signals arrive only on 1‑minute closes, creating entry/exit slippage versus the block close, and spreads/commissions can erase the edge. The suggested fix is to measure continuation probability, slippage distribution, and av...

👉 Read | Calendar | @mql5dev

Manual Trade Pad for MT4 is a chart-based trading panel packaged as an Expert Advisor, focused on manual execution and position management from the chart. It consolidates order entry, sizing, SL/TP setup, and trade management without relying on terminal order dialogs, and supports both live trading and visual historical testing with the same workflow.

Order entry is limited to market BUY/SELL, with Stop Loss defined in points and Take Profit optionally derived from a Risk/Reward ratio. Position sizing supports fixed lots or risk-percentage sizing, with volume normalized to broker min/max and lot-step constraints.

Trade management includes break-even moves with an optional offset, partial close with volume constraints, and bulk closing by direction or all managed trades. Trade ownership is scoped by symbol and Magic Number to avoid interfering with other EAs...

👉 Read | Signals | @mql5dev

A combined momentum signal can be derived by tracking the slope direction of MACD, OsMA, AC, AO, and RVI at the same time.

When all five slopes are rising together, it indicates broad alignment across trend and momentum components, with reduced risk of acting on a single-indicator spike. When all five slopes are falling together, it suggests synchronized weakening across the same set.

Implementation typically requires consistent slope measurement per bar (e.g., current minus prior value), a shared lookback and timeframe, and strict handling of flat/near-zero changes to avoid noise. Confirmation rules should define whether “same time” means the current closed bar only or a multi-bar window.

👉 Read | Calendar | @mql5dev

A trend-following trading system can be built around ATR as a volatility-normalized control layer for entries, position sizing, and exits.

Signals typically combine a directional filter (moving average slope, breakout of recent highs/lows, or channel rules) with an ATR-based threshold to avoid noise. Stops can be set at N×ATR from entry and trailed using the same multiple, keeping risk proportional across regimes. Position size is commonly derived from account risk per trade divided by ATR distance to the stop.

Key implementation details include using consistent bar indexing, handling gaps, and separating signal generation from execution logic. Validation should cover walk-forward testing, transaction costs, and sensitivity to ATR period and multiplier.

👉 Read | NeuroBook | @mql5dev

A good trading system starts with a clearly defined edge, expressed as explicit entry and exit rules that can be executed without interpretation. Signals should be based on measurable conditions, with fixed handling for gaps, slippage, and spread to avoid distorted backtests.

Risk management is mandatory: position sizing, maximum loss per trade, daily and weekly drawdown limits, and rules for stopping after regime changes. Performance evaluation should include out-of-sample testing, forward testing, and robustness checks across instruments and timeframes.

Execution details matter. Order types, latency sensitivity, and broker constraints should be accounted for. Ongoing monitoring should focus on degradation of expectancy, variance shifts, and adherence to the plan, with changes controlled through versioned updates and repeatable validation.

👉 Read | VPS | @mql5dev