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저의 작업은 개별 전략이 아닌 조율된 포트폴리오로 작동하는 Expert Advisor의 설계, 최적화 및 검증에 중점을 두고 있습니다. 상관관계 분석, 시간대 커버리지 매핑, 자산군 분산화를 적용하여 단일 상품이나 단일 접근 방식에 의존하지 않는 시스템을 구축합니다.
현재 외환, 지수, 귀금속, 에너지, 미국 주식을 아우르는 알고리즘 포트폴리오를 관리하고 있으며, 여러 세션과 타임프레임에서 동시에 운용하고 있습니다.
이 커뮤니티에서 기술 기사와 오픈소스 도구를 통해 제 경험을 공유하고 있습니다. "개별 EA 구축"에서 "포트폴리오 엔지니어링"으로의 전환이야말로 개인 투자자의 사고와 기관 투자자의 사고를 구분짓는 경계선이라 확신하며, 이 원칙이 제가 이곳에서 발행하는 모든 것의 지침이 됩니다.Has usado 75% de tu límit
Aggregate metrics alone do not reveal how a trade sequence manages risk. This MQL5 tool analyzes closed positions to flag four structural patterns: post-loss volume escalation, overlapping same-direction entries, asymmetric payoffs, and a classical risk-of-ruin figure. The results are merged into a configurable A-F grade with concise recommendations to guide further review.
Backtests often understate spread, commission, and slippage. This MQL5 analyzer loads closing deals and simulates rising execution costs to measure robustness. It computes the breakeven cost per deal, the cushion over an assumed cost, the net profit and profit factor at that cost, and how many winners turn into losers, then summarizes the result with an A+ to F grade and targeted guidance.
Net profit and win rate tell you how much a strategy made, not how the result is distributed. This article builds a native MQL5 script that reads your closed trades and measures profit concentration: the top-N trade share, the Gini coefficient of the winners, an outlier-dependence stress test that removes the best few winners, and the largest day against a prop-firm consistency limit. It combines these into one A+ to F score with recommendations, running inside MetaTrader 5.
I was in a forum thread today about trailing stops on XAUUSD, and it made me put into words something I've been building my whole approach around for a while: almost every trailing method traders compare — EMA cross, Chandelier, ATR multiples, swing-structure trails — gets judged on a single backtest run over one continuous chunk of history. The "best" multiplier or ladder step that wins that test isn't actually the best method. It's the method that happened to fit whatever mix of trend and chop was sitting in that sample.
The fix I use is simple to describe and annoying to implement properly: split the history into volatility regimes first (I use ATR percentile over a rolling window, expansion vs. compression), then optimize and validate each piece of logic separately per regime instead of once over the whole dataset. A structural trail wins clearly in expansion. In compression it just gets chopped up by noise, and something tighter does better there. Neither method is "the winner" — the regime decides which one applies.
That's the same principle I ended up building AbacuQuant around, just scaled up from one exit rule to an entire portfolio. Instead of one strategy tuned to look good on one backtest, the logic behind each strategy is walk-forward tested and optimized (genetic optimization, not a single curve-fit) across different market regimes and asset classes, forex, metals, indices, energy, ETFs, individual stocks — and then combined into a portfolio specifically to keep cross-asset correlation low (the current version sits under 0.4 correlation across most pairs in the book). The idea isn't "find the one strategy that beats the market." It's "find enough structurally different, regime-validated pieces that the portfolio doesn't fall apart when one regime ends," which is exactly the failure mode people are describing in that XAUUSD thread, just at the position level instead of the portfolio level.
It also runs entirely inside your own MetaTrader account nothing custodial, your funds never move to a third party and the newer version adds the drawdown/consistency rules prop firms check for, since that's become how a lot of people are actually trading it live.
If any of this is useful for how you're thinking about your own trailing logic or portfolio construction, happy to go deeper in the comments. And if you want to see what the regime-validated approach looks like applied across a full portfolio rather than one exit rule, it's at abacuquant.com.
Cristian David Castillo Arrieta
Maximum drawdown is one number that hides what really matters: how often an equity curve declines, how long it stays below a previous peak, and how quickly it recovers. This article builds a native MQL5 tool that reconstructs the underwater curve, breaks it into individual drawdown episodes (depth, duration, recovery time), computes the Ulcer Index, Pain Index, and Recovery Factor, and combines them into a single resilience grade with practical recommendations. No external libraries, no Python, no AI.
Most algo traders optimize Expert Advisors individually but never measure how they behave together on a single account. Correlated strategies amplify drawdowns instead of reducing them, and coverage gaps leave portfolios blind during entire trading sessions. This article builds a complete portfolio scorer in MQL5 that reads daily P&L from backtest CSV files, computes a full Pearson correlation matrix, maps trading activity by hour and weekday, evaluates asset class diversity, and outputs a composite grade from A+ to F. All source code is included; no external libraries are required.
ABQ Portfolio Correlation Scorer: Inteligencia Artificial de Grado Institucional para la Gestión de Riesgo La mayoría de los traders no fracasan por una mala estrategia de entrada, sino por una falla invisible en la arquitectura de su portafolio . El error más común es la sobreexposición por correlación: abrir múltiples posiciones pensando que se está diversificando, cuando en realidad se está multiplicando el riesgo sobre un mismo factor. ABQ Portfolio Correlation Scorer es un Copiloto de
ABQ Visual Risk Sizer - Institutional Risk & Trade Execution 카테고리: 유틸리티 / 리스크 관리 수동 로트 계산은 시간과 비용을 낭비하게 합니다. 현대 트레이딩, 특히 프랍 펌(Prop Firms) 계좌를 운영할 때 로트 계산 오류나 단 5초의 주문 지연은 일일 드로다운(Daily Drawdown) 규정 위반으로 이어지거나 최적의 진입 가격을 놓치는 원인이 됩니다. ABQ Visual Risk Sizer 는 이 문제를 완벽하게 해결하기 위해 설계된 기관급 도구입니다. 복잡한 리스크 수학 계산을 MetaTrader 5 차트 위에서 직접적이고 빠르며 100% 정확한 시각적 경험으로 변화시킵니다. 이제 외부 계산기나 엑셀 시트는 잊으십시오. 차트 위의 라인을 드래그하고 클릭 한 번으로 거래를 실행하기만 하면 됩니다. 왜 ABQ Visual Risk Sizer가 필요한가요? 프랍 펌을 위한 완벽한 보호: 모든 거래에서 사용자가 설정한