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.
261 documents
The document examines Bitcoin return distributions and volatility, then outlines a modeling workflow using ARMA for returns and EGARCH for conditional volatility. It calculates log returns from closing prices and discusses descriptive statistics, quantile…
The article explains Kaufman’s Adaptive Moving Average (KAMA), which adjusts its responsiveness according to an efficiency ratio derived from net price direction relative to total price movement. The ratio is intended to be low in choppy markets and high in…
The article diagnoses four live-trading weaknesses in a leveraged grid on EWY: poor capital use when volatility is low, growing exposure in a persistent decline, profit giveback and trapped positions, and expensive inventory accumulated near the top. It…
This simple trend strategy uses price movement from a stored reference level instead of technical indicators. When price moves beyond a configurable percentage threshold, it places a buy or sell order in the direction of that move, then resets the reference…
This account of an automated liquidity provision strategy focuses on the practical risks that emerged while moving from simulation to live trading on V3 and V4 pools. Early trades encountered tokens that could not be sold or pools whose liquidity disappeared…
The guide explains how strategy interface parameters are defined and displayed alongside code. It covers numeric, string, dropdown, Boolean, and encrypted string fields, including how their selected or entered values are exposed to the strategy. Encrypted…
The document presents a channel strategy for crypto futures that combines a moving average with average true range. An upper band is formed by adding a multiple of ATR to the moving average, while a lower band subtracts it. The strategy enters positions when…
The document introduces the Aroon indicator, which measures how recently the highest high and lowest low occurred within a chosen lookback period. Its Up and Down lines range from zero to one hundred: a more recent extreme produces a higher reading. The…
The document explains how to adapt a market data collector so a backtesting system can read user supplied price data from a CSV file. A configuration flag selects CSV input, and a file path identifies the data file on the collector’s server. The service…
This tutorial explains how to derive Renko bricks and Heikin Ashi candles from ordinary price bars and display them for trend analysis. Renko construction advances by a fixed price displacement, suppressing smaller fluctuations; the article presents this as…
The article maps a three-part wealth-building concept—cash flow, core assets, and alpha—to a set of automated crypto trading components. It proposes a reserve floor to help avoid selling core holdings, scheduled dollar-cost averaging to accumulate those…
This tutorial develops a pairs trading approach around the idea that two related assets may have a stable long-run relationship even as their prices temporarily diverge. It distinguishes cointegration from correlation, uses a cointegration test to screen…
This guide explains how to inspect JavaScript strategy execution during an FMZ backtest using Chrome DevTools. Adding a debugger statement pauses execution at a chosen point when DevTools is open. From there, traders can inspect variable values, set…
This document shows how to encapsulate time-based triggers in reusable alarm-clock objects for trading strategies. Each object stores a trigger hour and minute, checks the current clock, and returns true once the scheduled minute has arrived. A per-day flag…
This note explains a basic trend-following strategy based on Donchian channels. The upper and lower bands are formed from the highest high and lowest low over a lookback window, with the middle line between them. Wider bands indicate a broader recent price…
This brief note examines how trading fees affect the spread available to a triangular hedging strategy. It points readers to two research notebooks: one using the default fee setting and another adjusted for a different fee rate. Its central lesson is that…
The article explains On Balance Volume (OBV), which cumulatively adds volume when a bar closes above the prior close, subtracts it when the close is lower, and leaves the value unchanged on a tie. It interprets OBV as a way to view volume direction and…
The article describes a beginner’s use of a trading platform and ChatGPT to learn strategy scripting, inspect example strategies, and run backtests. It includes an AI-generated moving-average crossover example with stop-loss exits, then illustrates asking…
This guide introduces a platform charting interface intended to simplify custom strategy visualization in JavaScript. It shows how to create a chart object, begin and close a drawing pass for each candle, and plot data such as volume. A more detailed example…
This tutorial outlines a data-mining approach to machine-learning signals, contrasting it with strategies that begin from an explicit market inefficiency such as trend following or mean reversion. It recommends defining the prediction target and evaluation…
This tutorial explains how to add several custom charts to a trading strategy, each using a different candle interval and indicator layout. Its example creates hourly, 15-minute, and daily charts, then retrieves each series and routes candle and indicator…
The article compares conventional candlestick backtests with more detailed approaches for high-frequency and multi-instrument strategies. It explains that bars omit the timing of intrabar extremes, bid and ask quotes, and queue priority, which can distort…
This tutorial develops an intraday pairs-trading example using SPY and IWM minute bars. It aligns the two price series, estimates a rolling linear-regression hedge ratio, forms a spread, and standardizes that spread as a z-score. The example opens a long…
This introduction explains how block-based visual programming can express trading logic without requiring the user to write conventional code. It demonstrates building a basic output action, then describes a digital-asset rebalancing example based on current…