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.
9,660 documents
This brief indicator note explains how to construct an Ask-price line for a chart. It defines the plotted value as the bar’s Close price plus the spread value supplied to the calculation routine. The example identifies the calculation inputs, including price…
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…
This retrospective describes an early Bitcoin trading effort that began with cross-exchange price gaps and evolved into a statistical arbitrage strategy. Directly buying on one venue and transferring coins to another exposed traders to transfer delays and…
The panel description outlines tools for discretionary or automated trading execution. A position size calculator derives volume from a stop loss and a chosen risk percentage. A split-order feature divides an intended trade into two orders, with one assigned…
This short note describes a step chart that displays values as increments of a chosen step size. The step can be specified in fractional pips, and the chart can use common price types. This is a charting representation intended to show price movement in…
This brief troubleshooting post shows a trading order submission that failed with error -113. The accompanying Chinese error message indicates that no position was available. The logged request concerns selling 200 shares of a listed Chinese stock, and the…
This brief description outlines an Expert Advisor that combines a moving average, the Awesome Oscillator, and custom Laguerre indicators. It does not explain how those indicators are combined into entry or exit signals, so the trading logic cannot be…
This guide explains how FMZ’s template library feature lets users package reusable functions for strategies. It describes creating a library in JavaScript, Python, C++, or Blockly Visual mode, and shows how exported functions can be called from a strategy…
This post proposes screening Chinese stocks in a metaverse category using opening-price behavior. Its written rule requires the 9:25 gain to be below 6% and the auction change to lie between -2% and 5%. It supplies formula and Python examples, and briefly…
The article presents a four-stage account of how institutions might exploit retail traders in Chinese equities: identify market themes and likely stop levels from data, display large buy orders during the cancellable part of the opening auction, short shares…
The document describes a simple cryptocurrency spot trade-following bot. It treats one exchange account as the reference and periodically compares its current token balance, including frozen holdings, with the previous reading. An increase signals a buy and…
The document surveys ten cryptocurrency exchanges for automated trading and introduces basic bot setup. It compares venues through stated attributes such as available trading pairs, geographic availability, reputation, liquidity, fees, matching speed, and…
This MetaTrader Expert Advisor uses signals from the Karpenko oscillator. It opens a signal when a bar closes and the indicator cloud changes color, making the cloud transition the described entry trigger. The EA is presented for GBPUSD on a four-hour chart,…
The described expert advisor uses no indicators. At the start of a new bar, it opens two positions in opposite directions and then waits until both positions close through their stop-loss or take-profit levels before opening another pair. The approach relies…
This note collects operational details for trading BitZ contracts through its API, including contract identification, contract types, leverage behavior, margin modes, and closing orders. It distinguishes linear contracts from inverse contracts, noting that…
This guide explains how to use FMZ Trading Terminal plugins to support manual or semi-automated trading. A plugin runs a code snippet on a selected Docker instance and can return data tables or charts. The examples include displaying an exchange order-book…
This tutorial introduces FMZ Quant’s M language through a moving-average trend strategy. The example opens long positions when price and a short moving average are above a longer average that is rising, and opens short positions under corresponding bearish…
This brief forum exchange addresses how a VeighNa CTA strategy can read an account’s current position when it initializes. One participant asks whether a framework function exists, noting that calling the main engine’s position lookup directly did not seem…
The document explains dollar-cost averaging (DCA) as buying an asset at regular intervals or adding purchases after a price decline. It presents the approach as a way to build a position over time while reducing reliance on short-term market timing and…
This troubleshooting note describes a simulation failure in a single-stock AI ranking strategy: the pipeline reports that no data remains after missing values are removed, even though the strategy completes a backtest. It suggests checking whether the data…
This community post asks how to start a live or simulated trading strategy with positions already held in the account, rather than having the strategy assume it begins flat. It also raises a related backtesting question: a user supplied an initial-position…
This document explains a configuration option that adjusts bid and ask quote prices to account for exchange transaction costs. It describes percentage-based maker fees and fixed fees, and notes that enabling the option changes the proposed prices; it is…
This study tests whether investors can improve a diversified global equity factor portfolio by adjusting factor weights with time-series signals or cross-sectional characteristics. It applies parameterized portfolio policies to twenty long-short equity…
The document explains FMZ’s simulation-level backtest, where a strategy runs through repeated polling and receives market data through platform API calls. It distinguishes this approach from real market-level testing, which uses recorded tick data, and says…