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.
549 documents
OverHedgeV2 is described as an expert advisor that manages a group of positions using aggregate and per-position profit thresholds. It closes positions opened by the advisor when the group reaches a total profit target, subject to a condition that no…
This VeighNa CTA example implements a two-sided grid that begins with equal long and short positions after its bar manager has initialized. It checks each completed 15-minute bar against a moving reference price, using a fixed distance between grid levels.…
This Python script launches a Rust grid-trading backtest for each symbol in a ticker configuration. It assembles daily market-data and latency-file paths for a specified date range, passes instrument and strategy settings to the backtest executable, and runs…
The document outlines an expert advisor that places grid orders using average true range values. Its inputs include a profit target tied to invested capital, a moving-average period intended to assess trend, a multiplier that scales each new order from the…
This tutorial adapts a GLFT-based grid market-making backtest to multiple futures assets. It normalizes order size to a common notional amount, sets inventory limits in units of that order size, estimates trade-arrival intensity and price volatility from…
This Chinese-language post introduces grid trading as a dynamic rebalancing approach for stocks. Its basic premise is that prices fluctuate, allowing an investor to seek gains by buying at lower prices and selling at higher ones. The post frames grid trading…
The Expert Advisor combines an initial buy or sell position with a protective stop order, then builds a grid of pending orders at set price intervals. It uses ADX on a configurable timeframe to choose the grid style: below 40 it places limit orders, while…
This document describes an Expert Advisor that maintains a grid of pending orders above and below the current market price. Users can configure the number of orders per side, spacing, order types, lot size, slippage allowance, take-profit distance, and a…
This Expert Advisor applies a martingale approach with a configurable delay between entries. After an initial position, it waits a chosen number of bars before opening another position when the price moves by the specified step and a new entry signal…
The document outlines a programming framework for grid and Martingale trading strategies. A shared base strategy holds parameters such as starting price, trade volume, take profit, and monetary stop loss. Specialized grid and Martingale classes provide their…
This live-account listing describes a grid strategy operating on the BNB USDT perpetual contract using a 30-minute candle period. It shows a long position and reports account balances, returns, drawdown figures, liquidation estimates, trade activity, and an…
The document outlines an automated grid approach that places equally spaced pending limit orders around the current market price. It places sell limits above price and buy limits below, with the trading range derived from weekly highs and lows. Once orders…
This Expert Advisor uses moving average and Envelopes indicators to place pending buy and sell orders. It operates only when a new bar appears and limits order placement to a configured time window. The system can maintain up to three pending orders in each…
The article explains grid trading as a rule-based method that places repeated buys as price falls and sells as it rises within a chosen range. Traders set grid spacing, boundaries, and position sizes, aiming to collect gains from repeated price oscillations…
This document describes a short-term automated trading system for five-minute charts, aimed at major forex pairs and Nasdaq stocks. Its stated signal uses two five-period exponential moving averages and acts on the current candle’s opening price. The…
This strategy places buy limit and sell limit orders in a grid at a configured start hour. Its premise is that after one or more orders activate, price will return to the open of the bar on which the grid was placed. The grid uses a starting distance from…
This update reports Hummingbot development milestones and planned tools for running algorithmic trading systems. Shipped items included an OHLCV candles feed, a position execution component, orchestration for managing multiple bots, revised deployment…
The document argues that grid trading works best in assets that fluctuate actively within a range, while persistent declines can leave a strategy holding losing positions with few ways to recover. It proposes screening for business or asset stability,…
The document describes an indicator that compares the total price range over a chosen lookback with the sum of the ranges of the candles in that period. It has a lookback-length setting and an optional display of horizontal lines marking the current range.…
The strategy starts from a flat account by opening equal-sized long and short positions. When price moves by a preset step, it adds a position in the direction opposite that move, using twice the initial lot size. If price moves another step, the system…
This promotional fireside-chat recap describes OctoBot’s use of AI to turn natural-language requests into crypto trading setups. Examples include selecting a crypto basket, creating a dollar-cost averaging plan, configuring a grid strategy, and generating a…
This guide describes Grid Strike, a Hummingbot controller that builds a long or short order grid across a chosen price range. Unlike a conventional grid designed to trade back and forth in a range, it can add long exposure as prices rise or short exposure as…
The document presents KCI Volatility Distance as an indicator intended to measure directional strength and market conditions. It describes using its output to confirm momentum, supply a feature to a machine learning model, adjust grid spacing, scan multiple…
This short Python example sketches a grid approach for ETC/USD using 15-minute data. It builds price levels by repeatedly increasing a starting level by five percent, locates the current price within those levels, and places an initial buy. The intended loop…