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.
4,613 documents
This essay argues that lasting trading improvement depends more on realistic expectations, self-awareness, and disciplined practice than on secret methods or automated systems. It contrasts professional focus on developing skill with emotional reactions to…
This article describes an MQL5 Expert Advisor that adds an interactive trade-control panel to MetaTrader 5’s Strategy Tester. On-chart buttons let a tester place buy or sell trades, adjust lot size and stop-loss or take-profit levels, confirm or cancel a…
The article explains how to build an MQL5 expert advisor that turns MetaTrader 5's visual Strategy Tester into a manual chart-replay workspace. On-chart buttons let a tester open buy or sell positions and close positions; configurable inputs set lot size,…
The article defines a way to scale strategy positions in a multi-strategy Expert Advisor using a normalized balance. First, test a fixed lot size over a chosen period, measure maximum equity drawdown, and set the fitted balance so that drawdown corresponds…
This article outlines an MQL5 Expert Advisor for a multi-level grid strategy. It organizes trades into independent baskets, each tracking direction, initial and current lot size, grid spacing, take-profit level and signal time. A moving average is used to…
This article describes restructuring a multi-strategy Expert Advisor so strategy instances track virtual positions instead of placing market orders independently. A receiver collects the strategies’ requested volumes by symbol and converts their combined…
In this interview, trader Leonid Velichkovsky reflects on using neural networks in automated trading and challenges the idea that they produce exceptional profits by themselves. He describes them as trading systems whose adaptive capacity can help detect…
This installment of a multi-currency Expert Advisor series outlines how to add a new strategy to an automated optimization workflow. It introduces SimpleCandles, a contrarian idea: after a configurable run of same-direction closed candles, open a position in…
This article proposes balancing position sizes across instruments using each symbol’s tick value and average daily volatility. It combines those inputs into an estimate of risk per standard contract, then scales position volume relative to the highest…
The article compares position-sizing rules derived from linear, exponential, and hyperbolic balance-growth models. It first argues that money management presupposes a strategy with stop-loss and take-profit levels and positive expected value; where results…
The document presents a five-stage framework for turning market structure, liquidity, and price behavior into a directional hypothesis and trade plan. It evaluates context across four configurable timeframes: broad bias, traded structure, setup conditions,…
The article describes a MetaTrader 5 and Python system that uses rolling price data to estimate market uncertainty and adjust trading decisions. It calculates Shannon entropy from returns and squared returns, adds volatility and trend features, and feeds the…
This lecture explains leverage as borrowing to increase the capital deployed in a trading strategy. It defines the leverage ratio and uses single-period examples to show how borrowed funds can amplify gains while interest reduces the benefit. Borrowing costs…
The document explains how spreading exposure across independent or weakly correlated bets can reduce portfolio volatility, while adding highly correlated assets may leave risk largely unchanged. It illustrates the principle first with simulated bets that…
This notebook demonstrates position-level exits and portfolio-level controls through constructed examples. Static rules include stop losses, profit targets and time exits; dynamic rules include trailing stops that follow prior highs, tightening trails, and…
This notebook tests whether standard portfolio allocation can improve an every-bar NASDAQ-100 trading strategy that is already burdened by transaction costs. It selects predictions using validation performance on the declared cost-feasible universe, then…
This notebook studies how position sizing affects FX backtests after the model has already selected which currency pairs to trade. It preserves the winning baseline’s predictions, signal mapping, costs, and execution settings, then varies allocation rules.…
This notebook applies position-level risk controls to leading ETF allocation combinations while keeping each underlying prediction, concentration, and allocator fixed. It compares stop-losses, trailing stops, and time exits with the original strategy,…
This chapter presents portfolio construction as the process of converting return forecasts, risk estimates, and constraints into weights, leverage, and rebalancing decisions. It lays out a research workflow for documenting allocator choices, avoiding…
This notebook explains how to evaluate position-level exits and combine them with portfolio-wide controls. Fixed stop-loss, take-profit, and time exits are contrasted with trailing and tightening stops; a scaled exit reduces a position at successive profit…
This notebook explains when a strategy is clearest as precomputed arrays and when it benefits from a sequential simulation that carries positions, fills, cash, realized profit and loss, or equity forward through time. Array-based backtests are attractive…
This tutorial derives the Kelly fraction for a binary wager by maximizing expected logarithmic wealth growth, then extends the idea to continuous returns and a multi-asset portfolio. It uses symbolic differentiation and simulations with shared coin-toss…
This chapter presents a research workflow for using predictive models in trading, where stable out-of-sample forecasts may matter more than unbiased coefficient estimates. It covers regularized regression methods such as Ridge, LASSO, and Elastic Net, along…
This notebook explains when a trading strategy is clearer to simulate bar by bar with evolving state than to express as precomputed signals or weights. It contrasts array-based backtests, which can be fast and convenient for parameter sweeps, with sequential…